CN109767027A - Reservoir water percolating capacity prediction technique and device - Google Patents
Reservoir water percolating capacity prediction technique and device Download PDFInfo
- Publication number
- CN109767027A CN109767027A CN201811456717.1A CN201811456717A CN109767027A CN 109767027 A CN109767027 A CN 109767027A CN 201811456717 A CN201811456717 A CN 201811456717A CN 109767027 A CN109767027 A CN 109767027A
- Authority
- CN
- China
- Prior art keywords
- water
- reservoir
- percolating capacity
- water percolating
- height
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Computational Linguistics (AREA)
- Development Economics (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Game Theory and Decision Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention provides a kind of reservoir water percolating capacity prediction technique, comprising: obtains the expection weather information of the reservoir attribute and the purpose reservoir of purpose reservoir from current time to the object time；The expected weather information is input to default precipitation prediction model, obtains the purpose reservoir from the current time to precipitation during the expection of the object time；The expection height of water level of the purpose reservoir is calculated by the current level height of precipitation, the reservoir attribute of the purpose reservoir and the purpose reservoir during the expection；According to water percolating capacity and height of water level and the relational model of time and the expected height of water level, the expection water percolating capacity of the purpose reservoir described in the object time is determined；If the expected water percolating capacity reaches the first water percolating capacity threshold value, early warning information is sent.The present invention can rapidly predict the water percolating capacity of reservoir, be conducive to the infiltration situation for understanding reservoir in time.
Description
Technical field
The present invention relates to hydraulic engineering technical field more particularly to a kind of reservoir water percolating capacity prediction technique and devices.
Background technique
Reservoir is the water conservancy structure of a kind of flood retention water storage and adjusting water flow, can be used to irrigate, generate electricity and control flood.
The problem of reservoir leakage (i.e. reservoir infiltration) commonly encounters when being operational management, reservoir leakage gently then causes water flow to lose, so that
Reservoir function can not bring into normal play benefit, heavy then jeopardize dam safety, wherein dam is also referred to as dam, refers to the water blocking of reservoir
Building, dam are a part of reservoir.In the prior art, water percolating capacity is observed often through isotope, mineral quality detection, mill weir
The methods of infiltration situation and then predict water percolating capacity to obtain, these methods need to expend more time and manpower, inefficient.
Summary of the invention
In view of the foregoing, it is necessary to a kind of reservoir water percolating capacity prediction technique and device are provided, it can be rapidly to reservoir
Water percolating capacity is predicted, the infiltration situation for understanding reservoir in time is conducive to.
The present invention provides a kind of reservoir water percolating capacity prediction technique, which comprises
Obtain the expected meteorological letter of the reservoir attribute and the purpose reservoir of purpose reservoir from current time to the object time
Breath；
The expected weather information is input to default precipitation prediction model, obtains the purpose reservoir from described current
Precipitation during the expection of time to the object time；
Pass through the current water of precipitation, the reservoir attribute of the purpose reservoir and the purpose reservoir during the expection
Position height calculates the expection height of water level of the purpose reservoir；
According to water percolating capacity and height of water level and the relational model of time and the expected height of water level, determine in the mesh
Mark the expection water percolating capacity of purpose reservoir described in the time；
If the expected water percolating capacity reaches the first water percolating capacity threshold value, early warning information is sent.
In alternative embodiment of the present invention, the method also includes:
Obtain the relational model of the water percolating capacity Yu height of water level and time, comprising:
The purpose reservoir is obtained in the history water percolating capacity and corresponding history height of water level of historical time；
Data fitting is carried out to the historical time, the history water percolating capacity and the history height of water level, is obtained described
The relational model of water percolating capacity and height of water level and time.
In alternative embodiment of the present invention, the relational model of the water percolating capacity and height of water level and time are as follows:
Wherein, the Q is the expection water percolating capacity of the purpose reservoir, and the h is that the expection water level of the purpose reservoir is high
Degree, l are the level of dead water height of the purpose reservoir, and the t is the object time, and the object time is month.
In alternative embodiment of the present invention, if the expected water percolating capacity reaches the first water percolating capacity threshold value, early warning is sent
Message includes:
If the expected water percolating capacity reaches the first water percolating capacity threshold value, the leakage cause of the purpose reservoir is sent as dam body infiltration
The early warning information of leakage.
In alternative embodiment of the present invention, the method also includes:
If the expected water percolating capacity is not up to the first water percolating capacity threshold value, judge whether the expected water percolating capacity reaches
Two water percolating capacity threshold values；
If so, adjustment carries out the frequency of water percolating capacity prediction to the purpose reservoir.
The present invention also provides a kind of reservoir water percolating capacity prediction meanss, described device includes:
Module is obtained, the reservoir attribute and the purpose reservoir for obtaining purpose reservoir are from current time to the object time
Expection weather information；
Input module obtains the target for the expected weather information to be input to default precipitation prediction model
Reservoir is from the current time to precipitation during the expection of the object time；
First computing module, for passing through precipitation, the reservoir attribute of the purpose reservoir and institute during the expection
The current level height for stating purpose reservoir calculates the expection height of water level of the purpose reservoir；
Second computing module, for according to water percolating capacity and height of water level and the relational model of time and the expected water level
Highly, the expection water percolating capacity of the purpose reservoir described in the object time is determined；
Warning module sends early warning information if reaching the first water percolating capacity threshold value for the expected water percolating capacity.
In alternative embodiment of the present invention, described device further include model obtain module, for obtain the water percolating capacity with
The relational model of height of water level and time；
The model obtains module and is specifically used for:
The purpose reservoir is obtained in the history water percolating capacity and corresponding history height of water level of historical time；
Data fitting is carried out to the historical time, the history water percolating capacity and the history height of water level, is obtained described
The relational model of water percolating capacity and height of water level and time.
In alternative embodiment of the present invention, the relational model of the water percolating capacity and height of water level and time are as follows:
Wherein, the Q is the expection water percolating capacity of the purpose reservoir, and the h is that the expection water level of the purpose reservoir is high
Degree, l are the level of dead water height of the purpose reservoir, and the t is the object time, and the object time is month.
In alternative embodiment of the present invention, the warning module is specifically used for:
If the expected water percolating capacity reaches the first water percolating capacity threshold value, the leakage cause of the purpose reservoir is sent as dam body infiltration
The early warning information of leakage.
In alternative embodiment of the present invention, described device further includes adjustment module, and the adjustment module is used for:
If the expected water percolating capacity is not up to the first water percolating capacity threshold value, judge whether the expected water percolating capacity reaches
Two water percolating capacity threshold values；
If so, adjustment carries out the frequency of water percolating capacity prediction to the purpose reservoir.
The present invention also provides a kind of computer readable storage mediums, which is characterized in that the computer readable storage medium
It is stored at least one instruction, at least one described instruction realizes that reservoir described in any embodiment seeps when being executed by processor
Water prediction technique.
Found out by above technical scheme, the present invention is by the reservoir attribute for obtaining purpose reservoir and the purpose reservoir from working as
The expection weather information of preceding time to object time；The expected weather information is input to default precipitation prediction model, is obtained
To the purpose reservoir from the current time to precipitation during the expection of the object time；By being dropped during the expection
The current level height of water, the reservoir attribute of the purpose reservoir and the purpose reservoir calculates the pre- of the purpose reservoir
Phase height of water level；According to water percolating capacity and height of water level and the relational model of time and the expected height of water level, determine described
The expection water percolating capacity of purpose reservoir described in object time；If the expected water percolating capacity reaches the first water percolating capacity threshold value, early warning is sent
Message.The present invention obtains the expection height of water level by the end of the object time by precipitation during being expected, and based on expected water
Position height obtains expected water percolating capacity, the expection water percolating capacity for obtaining purpose reservoir in the object time is realized, without manually being seen
Mineral quality detection is surveyed or carried out, the purpose rapidly predicted the leakage of reservoir is realized, is reached in expected water percolating capacity
Reminded when to the first water percolating capacity threshold value, be conducive to water conservancy personnel and understand the leakage situation of reservoir in time, so take it is suitable
Precautionary measures.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 is a kind of flow chart of reservoir water percolating capacity prediction technique provided in an embodiment of the present invention；
Fig. 2 is the module map of reservoir water percolating capacity prediction meanss provided in an embodiment of the present invention；
Fig. 3 is the structural representation of the computer installation for the preferred embodiment that the present invention realizes reservoir water percolating capacity prediction technique
Figure.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention is described in further detail.
As shown in FIG. 1, FIG. 1 is a kind of flow charts of reservoir water percolating capacity prediction technique provided in an embodiment of the present invention.According to
Different demands, the sequence of step can change in the flow chart, and certain steps can be omitted.
S10 obtains the expection gas of the reservoir attribute and the purpose reservoir of purpose reservoir from current time to the object time
Image information.
In the present embodiment, purpose reservoir is the reservoir of water percolating capacity prediction to be carried out, and the reservoir attribute of purpose reservoir can be with
It is including but not limited to following one or more: the length of the cross-sectional area of reservoir, the water level of reservoir and PRESSURE-VOLUME RELATION curve, reservoir
Degree, the dam bottom width degree of the width at dam crest of reservoir, reservoir, the height of dam of reservoir, reservoir capacity.
The time that current time is got in real time, object time refer to the time to be predicted.Purpose reservoir is from current time
Expection weather information to the object time is that the location of purpose reservoir is expected meteorological from current time to the object time
Information.
In the present embodiment, the object time can be a period (such as certain season, certain moon, certain week, certain day).Example
Such as, if will be predicted in the water percolating capacity in March purpose reservoir, the object time is March；Alternatively, to purpose reservoir
Water percolating capacity after half a year is predicted that then the object time is that current time adds six months.
In the present embodiment, it is contemplated that weather information can include but is not limited to following one or more: temperature, humidity, day
Gas, wind direction, weather duration.
The expected weather information is input to default precipitation prediction model by S20, obtains the purpose reservoir from described
Current time to the object time expection during precipitation.
In the present embodiment, presetting precipitation prediction model can be the mould for being used to predict precipitation obtained by training
Type, precipitation refers to the liquid or solid-state (after melting) water that ground is dropped to from sky, without evaporation, leakage, loss in water
The depth gathered in plane.
The slave current time obtained through this embodiment to the object time expection during precipitation can be current time
To the accumulative possible precipitation of object time, that is, indicate possible precipitation is how many in total from current time to the object time,
For example, current time be January 1, it is contemplated that the time be 2 months No. 1, then be expected during precipitation can indicate January to 2 months the moon drop
Water.
Alternatively, being also possible to current time to the object time from current time to precipitation during the expection of object time
It is expected that practical accumulative precipitation, that is, indicate from the current time value object time in total possible precipitation through pervaporation, be lost it
Accumulative precipitation during the period afterwards.
Precipitation prediction model can be obtained by the following method:
(1) the precipitation prediction model pre-established is obtained, the precipitation prediction model is according to neural network model
It establishes；
Wherein, neural network model can be reverse transmittance nerve network (back propagation networdk, BP
Neural network).
The precipitation prediction model pre-established is the functional expression comprising unknown parameter.
(2) training set for training the precipitation prediction model is obtained；
Wherein, training set can be the multi-group data set that output data is corresponded to comprising input data.For example, reservoir attribute
History weather information with reservoir in certain a period of time (such as A time to B time) is input data, and reservoir is in the time (when such as A
Between to the B time) accumulative practical precipitation be that (data can pass through in history meteorological data obtains cut-off to B to output data
Time, actual precipitation obtained)/or accumulative possible precipitation (when the data can be by obtaining this section in history meteorological data
Between precipitation be added to obtain), according to the available multiple groups of history meteorological data in different times include input data pair
Answer the data acquisition system of output data.
By the different data of training, model can carry out different predictions.For example, when the output data in training data
To add up practical precipitation, then precipitation is pre- during the expection of the current time of precipitation prediction model prediction to object time
Phase practical accumulative precipitation；When the output data in training data adds up possible precipitation, the prediction of precipitation prediction model is worked as
Precipitation is accumulative possible precipitation during the expection of preceding time to object time.
(3) the precipitation prediction model is trained using the training set and Learning Algorithm, is obtained
The precipitation prediction model trained.
Trained process is exactly to be carried out according to training set and neural network model learning algorithm (for example, gradient descent algorithm)
Operation solves the value of unknown parameter in the precipitation prediction model pre-established, the precipitation prediction trained obtained from
Model.
S30 passes through precipitation, the reservoir attribute of the purpose reservoir and working as the purpose reservoir during the expection
Preceding height of water level calculates the expection height of water level of the purpose reservoir.
The current level height of the purpose reservoir can be got according to real-time detection, and the current level of purpose reservoir is high
Degree is the actual height of water level of purpose reservoir.
In the present embodiment, in the reservoir attribute and target of the practical reservoir height, purpose reservoir that obtain purpose reservoir
During the expection of reservoir after precipitation, the cross section for the reservoir that can included according to practical reservoir height and reservoir attribute
The cross-sectional area that product determines current level height (including the cross-sectional area in different height), further according to precipitation during expection and
The cross-sectional area of current level height, calculate according to precipitation during expection it is available how much the volume of Xin Zeng water, finally
The water level and PRESSURE-VOLUME RELATION curve that reservoir attribute is included are searched, determines that the volume of newly-increased water can make water level reach more
Less to get the expection height of water level for arriving purpose reservoir.
The expection height of water level obtained through this embodiment is the expected purpose reservoir when object time
Height of water level.
S40 is determined according to water percolating capacity and height of water level and the relational model of time and the expected height of water level in institute
State the expection water percolating capacity of purpose reservoir described in the object time.
In the present embodiment, water percolating capacity is also possible to the model pre-established with height of water level and the relational model of time.
Further, the relational model of the water percolating capacity Yu height of water level and time can also be obtained by the following method:
(1) purpose reservoir is obtained in the history water percolating capacity and corresponding history height of water level of historical time；
(2) data fitting is carried out to the historical time, the history water percolating capacity and the history height of water level, is seeped
The relational model of water and height of water level and time.
The history water percolating capacity can in the past 5 years perhaps the water percolating capacity of in every month, 10 and in the past 5 years or 10 years
Every month corresponding height of water level；Alternatively, history water percolating capacity be can be over 2 years daily/weekly water percolating capacities, and past
2 years daily/per week corresponding heights of water level.
Carrying out data fitting to historical time, history water percolating capacity and history height of water level may is that through graphic plotting journey
Sequence draws rectangular coordinate system, obtains multiple discrete data in plane right-angle coordinate, for example, rectangular coordinate system is with the time
Horizontal axis, height of water level be the longitudinal axis, according to discrete data (the different heights of water level of different time) multiple in rectangular coordinate system into
The first function relationship of height of water level and time are established in row fitting；And so on, it establishes water percolating capacity and the second function of time is closed
System is based on first function relationship and second function relationship, establishes height of water level, time, the third functional relation between water percolating capacity,
The third functional relation is the relational model of water percolating capacity Yu height of water level and time.
The relational model of the water percolating capacity obtained through this embodiment and height of water level and time is passed through by historical data
What the method for mathematical statistics obtained, there is certain accuracy.
Preferably, if obtaining water percolating capacity and the progress data fitting of corresponding height of water level, gained by chronomere of month
The water percolating capacity that arrives and height of water level and the relational model of time can be with are as follows:
Wherein, Q described in formula (1) is the expection water percolating capacity of the purpose reservoir, and the h is the pre- of the purpose reservoir
Phase height of water level, l are the level of dead water height of the purpose reservoir, and the t is the object time, and the object time is the moon
Part.
Wherein, target level of dead water refers under normal application, the lowest water level for allowing purpose reservoir water level to reduce.It is logical
Ordinary water library generally cannot be below level of dead water, its level of dead water of different reservoirs is different, and therefore, the value of l can in normal use
To preset according to the actual situation.
S50 sends early warning information if the expected water percolating capacity reaches the first water percolating capacity threshold value.
Wherein, the first water percolating capacity threshold value can be preset according to actual needs, and the first water percolating capacity threshold value is for sentencing
Whether the expection water percolating capacity of disconnected purpose reservoir is excessive.When expected water percolating capacity relatively reaches the first water percolating capacity threshold value, show target water
The expection water percolating capacity in library may be more, when expected water percolating capacity is not up to the first water percolating capacity threshold value, shows the expection of purpose reservoir
Water percolating capacity in the reasonable scope, will not generate harm and be influenced on reservoir.
In embodiments of the present invention, early warning information can be sent to communication apparatus such as mobile phone, the computers of hydraulic engineering personnel,
With this, to remind hydraulic engineering personnel according to the situation for the excessive water percolating capacity being likely to occur to take the precautionary measures, (such as enhancing is anti-
Shield).
Further, in an alternative embodiment of the invention, if the expected water percolating capacity reaches the first water percolating capacity threshold value,
Sending early warning information includes:
If the expected water percolating capacity reaches the first water percolating capacity threshold value, the leakage cause of the purpose reservoir is sent as dam body infiltration
The early warning information of leakage.
In the present embodiment, it when expected water percolating capacity reaches the first water percolating capacity threshold value, is provided to hydraulic engineering personnel more
Valuable warning information is conducive to improve the efficiency that engineering staff in water handles problem.
Since expected water percolating capacity is calculated by expected height of water level, show that water percolating capacity and height of water level exist centainly
Correlation, and there are positive correlations with height of water level for the water percolating capacity of purpose reservoir.The water percolating capacity of purpose reservoir is deposited with height of water level
Refer in positive correlation, when height of water level increases, water percolating capacity increases, and when height of water level reduces, water percolating capacity is reduced.For example, if mesh
The water percolating capacity model for marking reservoir is formula (1), when time consistency, if expected height of water level h increases, and the expection of purpose reservoir
Water percolating capacity Q increases.
Embankment seepage, leakage of dam foundation, dam abutment leakage are broadly divided into due to reservoir leakage, when height of water level changes
When, the water for contacting dam body directly changes, and water percolating capacity changes at this time, therefore, if variation and the water level of water percolating capacity
It is highly related, determine therefore the reason of infiltration occurs mainly in dam body, i.e. reservoir leakage can send target for dam body reason
The leakage cause of reservoir is the early warning information of embankment seepage.
Further, since dam body is usually to carry out antiseep by panel antiseep system, also transmittable opposite
The early warning information that plate antiseep system is handled.
Further, in an alternative embodiment of the invention, the method also includes:
If the expected water percolating capacity is not up to the first water percolating capacity threshold value, judge whether the expected water percolating capacity reaches
Two water percolating capacity threshold values；
If so, adjustment carries out the frequency of water percolating capacity prediction to the purpose reservoir.
In the present embodiment, adjust to purpose reservoir carry out water percolating capacity prediction frequency be specifically increase to purpose reservoir into
The frequency of row water percolating capacity prediction, that is, shorten the time detected to target water percolating capacity.For example, being originally used at interval of 6 months
The water percolating capacity of purpose reservoir is predicted, if expected water percolating capacity is greater than the second water percolating capacity threshold value and less than the first water percolating capacity threshold
Value, then be adjusted to predict the expection water percolating capacity of purpose reservoir at interval of 3 months.
Wherein, the second water percolating capacity threshold value can be set according to actual needs, and the second water percolating capacity threshold value is less than the first water percolating capacity
Threshold value.
Optionally, the second water percolating capacity threshold value can be the presupposition multiple of current water percolating capacity (multiple can be according to actual needs
Depending on), the second water percolating capacity threshold value can be used for judging whether expected water percolating capacity compares big more of current water percolating capacity, if so, showing
There may be the excessive risks of seeping water for purpose reservoir, then adjust the frequency that water percolating capacity prediction is carried out to purpose reservoir, be conducive to and
Whether the water percolating capacity of Shi Faxian purpose reservoir more than the first water percolating capacity threshold value and then carries out early warning.
In the present embodiment, the frequency that water percolating capacity prediction is carried out to purpose reservoir is adjusted and then predicting water percolating capacity
Rate, which can establish, improves reservoir infiltration early warning mechanism, improves the stability and safety when reservoir operation.
The reservoir attribute and the target water that reservoir water percolating capacity prediction technique provided by the invention passes through acquisition purpose reservoir
Expection weather information of the library from current time to the object time；The expected weather information is input to default precipitation prediction mould
Type obtains the purpose reservoir from the current time to precipitation during the expection of the object time；Pass through the expection
The current level height of period precipitation, the reservoir attribute of the purpose reservoir and the purpose reservoir calculates the target water
The expection height of water level in library；According to water percolating capacity and height of water level and the relational model of time and the expected height of water level, determine
The expection water percolating capacity of the purpose reservoir described in the object time；If the expected water percolating capacity reaches the first water percolating capacity threshold value, hair
Send early warning information.The present invention obtains the expection height of water level by the end of the object time by precipitation during being expected, and is based on
It is expected that height of water level obtains expected water percolating capacity, the expection water percolating capacity for obtaining purpose reservoir in the object time is realized, without carrying out
Artificial observation carries out mineral quality detection, realizes the purpose rapidly predicted the leakage of reservoir, seeps expected
Water is reminded when reaching the first water percolating capacity threshold value, is conducive to water conservancy personnel and is understood the leakage situation of reservoir in time, and then adopts
Take suitable precautionary measures.
As shown in Fig. 2, Fig. 2 is the functional block diagram of reservoir water percolating capacity prediction meanss provided in an embodiment of the present invention.It is described
Reservoir water percolating capacity prediction meanss include obtaining module 210, input module 220, the first computing module 230, the second computing module 240
With warning module 250.The so-called module of the present invention refers to that one kind can be by the processor institute of computer installation (such as server)
The series of computation machine program segment that executes and can complete fixed function, is stored in the memory of computer installation.?
In the present embodiment, the function about each module will be described in detail in subsequent embodiment.
Module 210 is obtained, the reservoir attribute and the purpose reservoir for obtaining purpose reservoir are from current time to target
The expection weather information of time.
In the present embodiment, purpose reservoir is the reservoir of water percolating capacity prediction to be carried out, and the reservoir attribute of purpose reservoir can be with
It is including but not limited to following one or more: the length of the cross-sectional area of reservoir, the water level of reservoir and PRESSURE-VOLUME RELATION curve, reservoir
Degree, the dam bottom width degree of the width at dam crest of reservoir, reservoir, the height of dam of reservoir, reservoir capacity.
The time that current time is got in real time, object time refer to the time to be predicted.Purpose reservoir is from current time
Expection weather information to the object time is that the location of purpose reservoir is expected meteorological from current time to the object time
Information.In the present embodiment, the object time can be a period (such as certain season, certain moon, certain week, certain day).For example, if
Purpose reservoir will be predicted in the water percolating capacity in March, then the object time is March；Alternatively, to after to purpose reservoir half a year
Water percolating capacity predicted, then the object time be current time add six months.
In the present embodiment, it is contemplated that weather information can include but is not limited to following one or more: temperature, humidity, day
Gas, wind direction, weather duration.
Input module 220 obtains the mesh for the expected weather information to be input to default precipitation prediction model
Reservoir is marked from the current time to precipitation during the expection of the object time.
In the present embodiment, presetting precipitation prediction model can be the precipitation for being used to predict reservoir obtained by training
The model of amount, precipitation refers to the liquid or solid-state (after melting) water that ground is dropped to from sky, without evaporation, leakage, stream
Lose the depth gathered in the horizontal plane.
The slave current time obtained through this embodiment to the object time expection during precipitation can be current time
To the accumulative possible precipitation of object time, that is, indicate possible precipitation is how many in total from current time to the object time,
For example, current time be January 1, it is contemplated that the time be 2 months No. 1, then be expected during precipitation can indicate January to 2 months the moon drop
Water.
Alternatively, being also possible to current time to the object time from current time to precipitation during the expection of object time
It is expected that practical accumulative precipitation, that is, indicate from the current time value object time in total possible precipitation through pervaporation, be lost it
Accumulative precipitation during the period afterwards.
Precipitation prediction model can be obtained by following model building module (indicating not in the drawings), the model is built
Formwork erection block is used for:
(1) the precipitation prediction model pre-established is obtained, the precipitation prediction model is according to neural network model
It establishes；
Wherein, neural network model can be reverse transmittance nerve network (back propagation networdk, BP
Neural network).
The precipitation prediction model pre-established is the functional expression comprising unknown parameter.
(2) training set for training the precipitation prediction model is obtained；
Wherein, training set can be the multi-group data set that output data is corresponded to comprising input data.For example, reservoir attribute
History weather information with reservoir in certain a period of time (such as A time to B time) is input data, and reservoir is in the time (when such as A
Between to the B time) accumulative practical precipitation be that (data can pass through in history meteorological data obtains cut-off to B to output data
Time, actual precipitation obtained)/or accumulative possible precipitation (when the data can be by obtaining this section in history meteorological data
Between precipitation be added to obtain), according to the available multiple groups of history meteorological data in different times include input data pair
Answer the data acquisition system of output data.
By the different data of training, model can carry out different predictions.For example, when the output data in training data
To add up practical precipitation, then precipitation is pre- during the expection of the current time of precipitation prediction model prediction to object time
Phase practical accumulative precipitation；When the output data in training data adds up possible precipitation, the prediction of precipitation prediction model is worked as
Precipitation is accumulative possible precipitation during the expection of preceding time to object time.
(3) the precipitation prediction model is trained using the training set and Learning Algorithm, is obtained
The precipitation prediction model trained.
Trained process is exactly to be carried out according to training set and neural network model learning algorithm (for example, gradient descent algorithm)
Operation solves the value of unknown parameter in the precipitation prediction model pre-established, the precipitation prediction trained obtained from
Model.
First computing module 230, for by precipitation during the expection, the purpose reservoir reservoir attribute and
The current level height of the purpose reservoir calculates the expection height of water level of the purpose reservoir.
The current level height of the purpose reservoir can be got according to real-time detection, and the current level of purpose reservoir is high
Degree is the actual height of water level of purpose reservoir.
In the present embodiment, in the reservoir attribute and target of the practical reservoir height, purpose reservoir that obtain purpose reservoir
During the expection of reservoir after precipitation, the cross section for the reservoir that can included according to practical reservoir height and reservoir attribute
The cross-sectional area that product determines current level height (including the cross-sectional area in different height), further according to precipitation during expection and
The cross-sectional area of current level height, calculate according to precipitation during expection it is available how much the volume of Xin Zeng water, finally
The water level and PRESSURE-VOLUME RELATION curve that reservoir attribute is included are searched, determines that the volume of newly-increased water can make water level reach more
Less to get the expection height of water level for arriving purpose reservoir.
The expection height of water level obtained through this embodiment is the expected purpose reservoir when object time
Height of water level.
Second computing module 240, for according to water percolating capacity and height of water level and the relational model of time and the expected water
Position height, determines the expection water percolating capacity of the purpose reservoir described in the object time.
In the present embodiment, water percolating capacity is also possible to the model pre-established with height of water level and the relational model of time.
Further, module (indicating not in the drawings) can also be obtained by model obtains the water percolating capacity and water level height
The relational model of degree and time, the model obtain module and are used for:
The purpose reservoir is obtained in the history water percolating capacity and corresponding history height of water level of historical time；And
Data fitting is carried out to the historical time, the history water percolating capacity and the history height of water level, is seeped water
The relational model of amount and height of water level and time.
The history water percolating capacity can in the past 5 years perhaps the water percolating capacity of in every month, 10 and in the past 5 years or 10 years
Every month corresponding height of water level；Alternatively, history water percolating capacity be can be over 2 years daily/weekly water percolating capacities, and past
2 years daily/per week corresponding heights of water level.
Carrying out data fitting to historical time, history water percolating capacity and history height of water level may is that through graphic plotting journey
Sequence draws rectangular coordinate system, obtains multiple discrete data in plane right-angle coordinate, for example, rectangular coordinate system is with the time
Horizontal axis, height of water level be the longitudinal axis, according to discrete data (the different heights of water level of different time) multiple in rectangular coordinate system into
The first function relationship of height of water level and time are established in row fitting；And so on, it establishes water percolating capacity and the second function of time is closed
System is based on first function relationship and second function relationship, establishes height of water level, time, the third functional relation between water percolating capacity,
The third functional relation is the relational model of water percolating capacity Yu height of water level and time.
The relational model of the water percolating capacity obtained through this embodiment and height of water level and time is passed through by historical data
What the method for mathematical statistics obtained, there is certain accuracy.
Preferably, if obtaining water percolating capacity and the progress data fitting of corresponding height of water level, gained by chronomere of month
The relational model of the water percolating capacity and height of water level and time that arrive are as follows:
Wherein, Q described in formula (1) is the expection water percolating capacity of the purpose reservoir, and the h is the pre- of the purpose reservoir
Phase height of water level, l are the level of dead water height of the purpose reservoir, and the t is the object time, and the object time is the moon
Part.
Wherein, target level of dead water refers under normal application, the lowest water level for allowing purpose reservoir water level to reduce.It is logical
Ordinary water library generally cannot be below level of dead water, its level of dead water of different reservoirs is different, and therefore, the value of l can in normal use
To preset according to the actual situation.
Warning module 250 sends early warning information if the expected water percolating capacity reaches the first water percolating capacity threshold value.
Wherein, the first water percolating capacity threshold value can be preset according to actual needs, and the first water percolating capacity threshold value is for sentencing
Whether the expection water percolating capacity of disconnected purpose reservoir is excessive.When expected water percolating capacity relatively reaches the first water percolating capacity threshold value, show target water
The expection water percolating capacity in library may be more, when expected water percolating capacity is not up to the first water percolating capacity threshold value, shows the expection of purpose reservoir
Water percolating capacity in the reasonable scope, will not generate harm and be influenced on reservoir.
In embodiments of the present invention, early warning information can be sent to communication apparatus such as mobile phone, the computers of hydraulic engineering personnel,
With this, to remind hydraulic engineering personnel according to the situation for the excessive water percolating capacity being likely to occur to take the precautionary measures, (such as enhancing is anti-
Shield).
Further, in an alternative embodiment of the invention, the warning module is specifically used for:
If the expected water percolating capacity reaches the first water percolating capacity threshold value, the leakage cause of the purpose reservoir is sent as dam body infiltration
The early warning information of leakage.
In the present embodiment, it when expected water percolating capacity reaches the first water percolating capacity threshold value, is provided to hydraulic engineering personnel more
Valuable warning information is conducive to improve the efficiency that engineering staff in water handles problem.
Since expected water percolating capacity is calculated by expected height of water level, show that water percolating capacity and height of water level exist centainly
Correlation, and there are positive correlations with height of water level for the water percolating capacity of purpose reservoir.The water percolating capacity of purpose reservoir is deposited with height of water level
Refer in positive correlation, when height of water level increases, water percolating capacity increases, and when height of water level reduces, water percolating capacity is reduced.For example, if mesh
The water percolating capacity model for marking reservoir is formula (1), when time consistency, if expected height of water level h increases, and the expection of purpose reservoir
Water percolating capacity Q increases.
Embankment seepage, leakage of dam foundation, dam abutment leakage are broadly divided into due to reservoir leakage, when height of water level changes
When, the water for contacting dam body directly changes, and water percolating capacity changes at this time, therefore, if variation and the water level of water percolating capacity
It is highly related, it can determine that the reason of infiltration occurs mainly in dam body, i.e. reservoir leakage is therefore dam body reason can be sent
The leakage cause of purpose reservoir is the early warning information of embankment seepage.
Further, since dam body is usually to carry out antiseep by panel antiseep system, also transmittable opposite
The early warning information that plate antiseep system is handled.
Further, in an alternative embodiment of the invention, described device further includes adjustment module (indicating not in the drawings),
The adjustment module is used for:
If the expected water percolating capacity is not up to the first water percolating capacity threshold value, judge whether the expected water percolating capacity reaches
Two water percolating capacity threshold values；
If so, adjustment carries out the frequency of water percolating capacity prediction to the purpose reservoir.
In the present embodiment, adjust to purpose reservoir carry out water percolating capacity prediction frequency be specifically increase to purpose reservoir into
The frequency of row water percolating capacity prediction, that is, shorten the time detected to target water percolating capacity.For example, being originally used at interval of 6 months
The water percolating capacity of purpose reservoir is predicted, if expected water percolating capacity is greater than the second water percolating capacity threshold value and less than the first water percolating capacity threshold
Value, then be adjusted to predict the expection water percolating capacity of purpose reservoir at interval of 3 months.
Wherein, the second water percolating capacity threshold value can be set according to actual needs, and the second water percolating capacity threshold value is less than the first water percolating capacity
Threshold value.
Optionally, the second water percolating capacity threshold value can be the presupposition multiple of current water percolating capacity (multiple can be according to actual needs
Depending on), the second water percolating capacity threshold value can be used for judging whether expected water percolating capacity compares big more of current water percolating capacity, if so, showing
There may be the excessive risks of seeping water for purpose reservoir, then adjust the frequency that water percolating capacity prediction is carried out to purpose reservoir, be conducive to and
Whether the water percolating capacity of Shi Faxian purpose reservoir more than the first water percolating capacity threshold value and then carries out early warning.
In the present embodiment, the frequency that water percolating capacity prediction is carried out to purpose reservoir is adjusted and then predicting water percolating capacity
Rate, which can establish, improves reservoir infiltration early warning mechanism, improves the stability and safety when reservoir operation.
Reservoir water percolating capacity prediction meanss provided by the invention obtain reservoir attribute and the institute of purpose reservoir by obtaining module
State expection weather information of the purpose reservoir from current time to the object time；The expected weather information is input to by input module
Default precipitation prediction model, obtains the purpose reservoir from the current time to precipitation during the expection of the object time
Amount；First computing module passes through precipitation during the expection, the reservoir attribute and the purpose reservoir of the purpose reservoir
Current level height calculate the expection height of water level of the purpose reservoir；Second computing module is according to water percolating capacity and height of water level
With the relational model and the expected height of water level of time, the expected infiltration of the purpose reservoir described in the object time is determined
Amount；If the warning module expected water percolating capacity reaches the first water percolating capacity threshold value, early warning information is sent.The present invention passes through during being expected
Precipitation obtains the expection height of water level by the end of the object time, and obtains expected water percolating capacity based on expected height of water level, real
Show the expection water percolating capacity for obtaining purpose reservoir in the object time, it is real without carrying out artificial observation or carrying out mineral quality detection
The purpose rapidly predicted the leakage of reservoir is showed, has been mentioned when expected water percolating capacity reaches the first water percolating capacity threshold value
It wakes up, is conducive to water conservancy personnel and understands the leakage situation of reservoir in time, and then take suitable precautionary measures.
As shown in figure 3, Fig. 3 is the computer installation for the preferred embodiment that the present invention realizes reservoir water percolating capacity prediction technique
Structural schematic diagram.The computer installation includes at least one sending device 31, at least one processor 32, at least one processing
Device 33, at least one reception device 34 and at least one communication bus.Wherein, the communication bus is for realizing these components
Between connection communication.
The computer installation be it is a kind of can according to the instruction for being previously set or store, it is automatic carry out numerical value calculate with/
Or the equipment of information processing, hardware include but is not limited to microprocessor, specific integrated circuit (Application Specific
Integrated Circuit, ASIC), programmable gate array (Field-Programmable Gate Array, FPGA), number
Word processing device (Digital Signal Processor, DSP), embedded device etc..The computer installation may also include net
Network equipment and/or user equipment.Wherein, the network equipment includes but is not limited to single network server, multiple network services
The server group of device composition or being made of a large amount of hosts or network server based on cloud computing (Cloud Computing)
Cloud, wherein cloud computing is one kind of distributed computing, a super virtual meter consisting of a loosely coupled set of computers
Calculation machine.
The computer installation may be, but not limited to, any one and can be set with user by keyboard, touch tablet or acoustic control
The modes such as standby carry out the electronic product of human-computer interaction, for example, tablet computer, smart phone, personal digital assistant (Personal
Digital Assistant, PDA), intellectual wearable device, picture pick-up device, the terminals such as monitoring device.
Network locating for the computer installation includes, but are not limited to internet, wide area network, Metropolitan Area Network (MAN), local area network, virtual
Dedicated network (Virtual Private Network, VPN) etc..
Wherein, the reception device 34 and the sending device 31 can be wired sending port, or wirelessly set
It is standby, for example including antenna assembly, for carrying out data communication with other equipment.
The memory 32 is for storing program code.The memory 32, which can be, does not have physical form in integrated circuit
The circuit with store function, such as RAM (Random-Access Memory, random access memory), FIFO (First In
First Out, first-in first-out register) etc..Alternatively, the memory 32 is also possible to the memory with physical form, such as
Memory bar, TF card (Trans-flash Card), smart media card (smart media card), safe digital card (secure
Digital card), storage facilities such as flash memory cards (flash card) etc..
The processor 33 may include one or more microprocessor, digital processing unit.The processor 33 is adjustable
With the program code stored in memory 32 to execute relevant function.For example, each unit described in Fig. 3 is stored in institute
The program code in memory 32 is stated, and as performed by the processor 33, to realize a kind of reservoir water percolating capacity prediction technique.Institute
It states processor 33 and is also known as central processing unit (CPU, Central Processing Unit), be one block of ultra-large integrated electricity
Road is arithmetic core (Core) and control core (Control Unit).
In several embodiments provided by the present invention, it should be understood that disclosed system, device and method can be with
It realizes by another way.For example, the apparatus embodiments described above are merely exemplary, for example, the module
It divides, only a kind of logical function partition, there may be another division manner in actual implementation.
The module as illustrated by the separation member may or may not be physically separated, aobvious as module
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.Some or all of the modules therein can be selected to realize the mesh of this embodiment scheme according to the actual needs
's.
It, can also be in addition, each functional module in each embodiment of the present invention can integrate in one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of hardware adds software function module.
It is obvious to a person skilled in the art that invention is not limited to the details of the above exemplary embodiments, Er Qie
In the case where without departing substantially from spirit or essential attributes of the invention, the present invention can be realized in other specific forms.Therefore, no matter
From the point of view of which point, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the present invention is by appended power
Benefit requires rather than above description limits, it is intended that all by what is fallen within the meaning and scope of the equivalent elements of the claims
Variation is included in the present invention.Any attached associated diagram label in claim should not be considered as right involved in limitation to want
It asks.Furthermore, it is to be understood that one word of " comprising " does not exclude other units or steps, odd number is not excluded for plural number.It is stated in system claims
Multiple units or device can also be implemented through software or hardware by a unit or device.Second equal words are used to table
Show title, and does not indicate any particular order.
Finally it should be noted that the above examples are only used to illustrate the technical scheme of the present invention and are not limiting, although reference
Preferred embodiment describes the invention in detail, those skilled in the art should understand that, it can be to of the invention
Technical solution is modified or equivalent replacement, without departing from the spirit and scope of the technical solution of the present invention.
Claims (10)
1. a kind of reservoir water percolating capacity prediction technique, which is characterized in that the described method includes:
Obtain the expection weather information of the reservoir attribute and the purpose reservoir of purpose reservoir from current time to the object time；
The expected weather information is input to default precipitation prediction model, obtains the purpose reservoir from the current time
Extremely precipitation during the expection of the object time；
It is high by the current level of precipitation, the reservoir attribute of the purpose reservoir and the purpose reservoir during the expection
Degree calculates the expection height of water level of the purpose reservoir；
According to water percolating capacity and height of water level and the relational model of time and the expected height of water level, determine in the target
Between the purpose reservoir expection water percolating capacity；
If the expected water percolating capacity reaches the first water percolating capacity threshold value, early warning information is sent.
2. reservoir water percolating capacity prediction technique as described in claim 1, which is characterized in that the method also includes:
Obtain the relational model of the water percolating capacity Yu height of water level and time, comprising:
The purpose reservoir is obtained in the history water percolating capacity and corresponding history height of water level of historical time；
Data fitting is carried out to the historical time, the history water percolating capacity and the history height of water level, obtains the infiltration
The relational model of amount and height of water level and time.
3. reservoir water percolating capacity prediction technique as described in claim 1, which is characterized in that the water percolating capacity and height of water level and when
Between relational model are as follows:
Wherein, the Q is the expection water percolating capacity of the purpose reservoir, and the h is the expection height of water level of the purpose reservoir, l
For the level of dead water height of the purpose reservoir, the t is the object time, and the object time is month.
4. reservoir water percolating capacity prediction technique as claimed any one in claims 1 to 3, which is characterized in that if described pre-
Phase water percolating capacity reaches the first water percolating capacity threshold value, sends early warning information and includes:
If the expected water percolating capacity reaches the first water percolating capacity threshold value, the leakage cause for sending the purpose reservoir is embankment seepage
Early warning information.
5. reservoir water percolating capacity prediction technique as claimed any one in claims 1 to 3, which is characterized in that the method is also wrapped
It includes:
If the expected water percolating capacity is not up to the first water percolating capacity threshold value, judge whether the expected water percolating capacity reaches the second infiltration
Water threshold value；
If so, adjustment carries out the frequency of water percolating capacity prediction to the purpose reservoir.
6. a kind of reservoir water percolating capacity prediction meanss, which is characterized in that described device includes:
Module is obtained, the reservoir attribute and the purpose reservoir for obtaining purpose reservoir are pre- from current time to the object time
Phase weather information；
Input module obtains the purpose reservoir for the expected weather information to be input to default precipitation prediction model
From the current time to precipitation during the expection of the object time；
First computing module, for the reservoir attribute and the mesh by precipitation during the expection, the purpose reservoir
The current level height of mark reservoir calculates the expection height of water level of the purpose reservoir；
Second computing module, for according to water percolating capacity and height of water level and the relational model of time and the expected height of water level,
Determine the expection water percolating capacity of the purpose reservoir described in the object time；
Warning module sends early warning information if reaching the first water percolating capacity threshold value for the expected water percolating capacity.
7. reservoir water percolating capacity prediction meanss as claimed in claim 6, which is characterized in that described device further includes that model obtains mould
Block, for obtaining the relational model of the water percolating capacity Yu height of water level and time；
The model obtains module and is specifically used for:
The purpose reservoir is obtained in the history water percolating capacity and corresponding history height of water level of historical time；
Data fitting is carried out to the historical time, the history water percolating capacity and the history height of water level, obtains the infiltration
The relational model of amount and height of water level and time.
8. reservoir water percolating capacity prediction meanss as claimed in claim 6, which is characterized in that the water percolating capacity and height of water level and when
Between relational model are as follows:
Wherein, the Q is the expection water percolating capacity of the purpose reservoir, and the h is the expection height of water level of the purpose reservoir, l
For the level of dead water height of the purpose reservoir, the t is the object time, and the object time is month.
9. the reservoir water percolating capacity prediction meanss as described in any one of claim 6 to 8, which is characterized in that the warning module
It is specifically used for:
If the expected water percolating capacity reaches the first water percolating capacity threshold value, the leakage cause for sending the purpose reservoir is embankment seepage
Early warning information.
10. the reservoir water percolating capacity prediction meanss as described in any one of claim 6 to 8, described device further includes adjustment module,
The adjustment module is used for:
If the expected water percolating capacity is not up to the first water percolating capacity threshold value, judge whether the expected water percolating capacity reaches the second infiltration
Water threshold value；
If so, adjustment carries out the frequency of water percolating capacity prediction to the purpose reservoir.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811456717.1A CN109767027A (en) | 2018-11-30 | 2018-11-30 | Reservoir water percolating capacity prediction technique and device |
| PCT/CN2019/118595 WO2020108319A1 (en) | 2018-11-30 | 2019-11-14 | Reservoir water seepage prediction method and device, computer device and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811456717.1A CN109767027A (en) | 2018-11-30 | 2018-11-30 | Reservoir water percolating capacity prediction technique and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109767027A true CN109767027A (en) | 2019-05-17 |
Family
ID=66450338
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811456717.1A Pending CN109767027A (en) | 2018-11-30 | 2018-11-30 | Reservoir water percolating capacity prediction technique and device |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN109767027A (en) |
| WO (1) | WO2020108319A1 (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110399638A (en) * | 2019-06-15 | 2019-11-01 | 湖南闲暇科技有限公司 | A method of flood and overflow time of origin are calculated according to meteorological data |
| WO2020108319A1 (en) * | 2018-11-30 | 2020-06-04 | 深圳春沐源控股有限公司 | Reservoir water seepage prediction method and device, computer device and storage medium |
| CN111737640A (en) * | 2020-08-17 | 2020-10-02 | 深圳江行联加智能科技有限公司 | Water level prediction method, device and computer readable storage medium |
| CN112628612A (en) * | 2020-12-07 | 2021-04-09 | 山东潍微科技股份有限公司 | Pipe network leakage big data detection method for predicting leakage-simulated data |
| CN113034854A (en) * | 2021-03-06 | 2021-06-25 | 杭州自动桌信息技术有限公司 | Intelligent identification and alarm method and system for dam leakage points and storage medium |
| CN113468464A (en) * | 2021-06-30 | 2021-10-01 | 国能黄骅港务有限责任公司 | Method and device for predicting water level of regulation and storage lake and reservoir, computer equipment and storage medium |
| CN113515507A (en) * | 2021-03-12 | 2021-10-19 | 中电建电力检修工程有限公司 | Method and system applied to dam seepage detection |
| CN116882215A (en) * | 2023-09-07 | 2023-10-13 | 北京国信华源科技有限公司 | Multi-element self-excitation early warning method |
| CN118071158A (en) * | 2024-04-22 | 2024-05-24 | 中铁水利信息科技有限公司 | Intelligent hydraulic engineering early warning system based on intelligent sensing and data fusion |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112799154B (en) * | 2020-12-28 | 2023-05-16 | 恒瑞通（福建）信息技术有限公司 | Ecological environment big data prediction and early warning method and terminal |
| CN114997548B (en) * | 2022-08-05 | 2022-10-18 | 武九铁路客运专线湖北有限责任公司 | Water movement geological seepage real-time early warning method based on genetic neural network |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012012907A (en) * | 2010-07-05 | 2012-01-19 | Chubu Electric Power Co Inc | Dam measurement data evaluation method and dam measurement data evaluation system |
| CN105527198A (en) * | 2016-01-20 | 2016-04-27 | 王昌益 | Measurement method of seepage flow movement rule |
| CN106370802A (en) * | 2016-08-16 | 2017-02-01 | 华南理工大学 | Method for determining water loss of reservoir by using hydrogen and oxygen isotopes |
| CN108492530A (en) * | 2018-03-09 | 2018-09-04 | 深圳市宏电技术股份有限公司 | A kind of reservoir spillway warning information dissemination method, apparatus and system |
| CN108681848A (en) * | 2018-08-25 | 2018-10-19 | 黄河水利委员会黄河水利科学研究院 | One kind " Trinity " small reservoir or silt arrester flood season method for early warning |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3693089B2 (en) * | 1998-08-04 | 2005-09-07 | 富士電機システムズ株式会社 | Flow prediction method in dam |
| CN102509433A (en) * | 2011-10-31 | 2012-06-20 | 中国瑞林工程技术有限公司 | Tailing pond numerical simulation and on-line monitoring integral emergency early-warning system |
| CN104281920A (en) * | 2014-09-29 | 2015-01-14 | 中南大学 | Tailing pond layered index safety assessment and early-warning method and system |
| CN106769783A (en) * | 2017-02-10 | 2017-05-31 | 水利部交通运输部国家能源局南京水利科学研究院 | The monitoring diagnosis device and method of a kind of earth and rockfill dam barrier performance deterioration |
| CN109767027A (en) * | 2018-11-30 | 2019-05-17 | 深圳春沐源控股有限公司 | Reservoir water percolating capacity prediction technique and device |
-
2018
- 2018-11-30 CN CN201811456717.1A patent/CN109767027A/en active Pending
-
2019
- 2019-11-14 WO PCT/CN2019/118595 patent/WO2020108319A1/en active Application Filing
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012012907A (en) * | 2010-07-05 | 2012-01-19 | Chubu Electric Power Co Inc | Dam measurement data evaluation method and dam measurement data evaluation system |
| CN105527198A (en) * | 2016-01-20 | 2016-04-27 | 王昌益 | Measurement method of seepage flow movement rule |
| CN106370802A (en) * | 2016-08-16 | 2017-02-01 | 华南理工大学 | Method for determining water loss of reservoir by using hydrogen and oxygen isotopes |
| CN108492530A (en) * | 2018-03-09 | 2018-09-04 | 深圳市宏电技术股份有限公司 | A kind of reservoir spillway warning information dissemination method, apparatus and system |
| CN108681848A (en) * | 2018-08-25 | 2018-10-19 | 黄河水利委员会黄河水利科学研究院 | One kind " Trinity " small reservoir or silt arrester flood season method for early warning |
Non-Patent Citations (1)
| Title |
|---|
| 刘鸣等: "牙塘水库大坝渗流监测分析及安全评价", 《长江科学院院报》 * |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020108319A1 (en) * | 2018-11-30 | 2020-06-04 | 深圳春沐源控股有限公司 | Reservoir water seepage prediction method and device, computer device and storage medium |
| CN110399638A (en) * | 2019-06-15 | 2019-11-01 | 湖南闲暇科技有限公司 | A method of flood and overflow time of origin are calculated according to meteorological data |
| CN111737640A (en) * | 2020-08-17 | 2020-10-02 | 深圳江行联加智能科技有限公司 | Water level prediction method, device and computer readable storage medium |
| CN112628612A (en) * | 2020-12-07 | 2021-04-09 | 山东潍微科技股份有限公司 | Pipe network leakage big data detection method for predicting leakage-simulated data |
| CN112628612B (en) * | 2020-12-07 | 2023-01-31 | 山东潍微科技股份有限公司 | Pipe network leakage big data detection method for predicting leakage-simulated data |
| CN113034854A (en) * | 2021-03-06 | 2021-06-25 | 杭州自动桌信息技术有限公司 | Intelligent identification and alarm method and system for dam leakage points and storage medium |
| CN113515507A (en) * | 2021-03-12 | 2021-10-19 | 中电建电力检修工程有限公司 | Method and system applied to dam seepage detection |
| CN113515507B (en) * | 2021-03-12 | 2024-02-02 | 中电建电力检修工程有限公司 | Method and system applied to dam water seepage detection |
| CN113468464A (en) * | 2021-06-30 | 2021-10-01 | 国能黄骅港务有限责任公司 | Method and device for predicting water level of regulation and storage lake and reservoir, computer equipment and storage medium |
| CN113468464B (en) * | 2021-06-30 | 2023-04-18 | 国能黄骅港务有限责任公司 | Method and device for predicting water level of regulation and storage lake and reservoir, computer equipment and storage medium |
| CN116882215A (en) * | 2023-09-07 | 2023-10-13 | 北京国信华源科技有限公司 | Multi-element self-excitation early warning method |
| CN116882215B (en) * | 2023-09-07 | 2023-12-29 | 北京国信华源科技有限公司 | Multi-element self-excitation early warning method |
| CN118071158A (en) * | 2024-04-22 | 2024-05-24 | 中铁水利信息科技有限公司 | Intelligent hydraulic engineering early warning system based on intelligent sensing and data fusion |
| CN118071158B (en) * | 2024-04-22 | 2024-07-05 | 中铁水利信息科技有限公司 | Intelligent hydraulic engineering early warning system based on intelligent sensing and data fusion |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2020108319A1 (en) | 2020-06-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109767027A (en) | Reservoir water percolating capacity prediction technique and device | |
| Mandli et al. | Adaptive mesh refinement for storm surge | |
| CN109061776B (en) | Short-time approaching numerical weather forecasting system and method | |
| Westoby et al. | Numerical modelling of glacial lake outburst floods using physically based dam-breach models | |
| CN112257352A (en) | Coupling method and system of one-dimensional hydrodynamic model and two-dimensional hydrodynamic model | |
| Adamson et al. | Bivariate extreme value distributions: an application of the Gibbs sampler to the analysis of floods | |
| CN103516912B (en) | A kind of mobile terminal location electricity saving method | |
| CN112697197A (en) | GIS (geographic information System) and BIM (building information modeling) fusion technology based porous flood gate visual management system and method | |
| CN111666314B (en) | Multi-factor-based storm surge vulnerability assessment method and device and computer equipment | |
| Han et al. | Numerical simulation for run-out extent of debris flows using an improved cellular automaton model | |
| CN114492233A (en) | Basin water simulation method based on webGIS platform and considering comprehensive utilization requirements | |
| CN107423912A (en) | A kind of method and system for becoming dynamic mesh dynamic division based on personnel | |
| WO2023278458A1 (en) | Coupled pluvial, fluvial, and urban flood tool | |
| Dahm et al. | Next generation flood modelling using 3Di: A case study in Taiwan | |
| CN112816663B (en) | Method and device for monitoring soil water content of yellow river dam in flood control project | |
| CN110210774A (en) | Landslide risk evaluation method and system | |
| CN114235082A (en) | Intelligent metering method based on sand production monitoring system | |
| CN111191372B (en) | Large-scale flood scene simulation early warning interaction method and system based on two-dimensional hydrodynamics | |
| CN115758890B (en) | Sponge city intelligent monitoring method and system | |
| JP7220276B1 (en) | Inundation simulation device, inundation simulation method and program | |
| CN117973131A (en) | Finite element model-based power transmission tower geological disaster failure prediction method and system | |
| CN115130935B (en) | Ecological seawall disaster prevention and reduction efficiency analysis method and device, electronic equipment and medium | |
| CN111079298A (en) | Power system dynamic hybrid simulation method and system based on ice wind weather conditions | |
| JP2021033915A (en) | Computer program, dam inflow prediction program, and dam inflow prediction system | |
| Jeong | A study on simulation of flood inundation in a coastal urban area using a two-dimensional well-balanced finite volume model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190517 |
|
| RJ01 | Rejection of invention patent application after publication |