CN115185313B

CN115185313B - Trend tracking and early warning method and device for bearing bush temperature of hydroelectric generating set

Info

Publication number: CN115185313B
Application number: CN202210937015.5A
Authority: CN
Inventors: 王卫玉; 何葵东; 赵训新; 罗立军; 魏加达; 王思嘉; 张培; 李崇仕; 刘禹; 胡蝶; 莫凡; 金艳; 侯凯; 姜晓峰; 肖志怀
Original assignee: Hunan Wuling Power Technology Co Ltd; Wuling Power Corp Ltd
Current assignee: Hunan Wuling Power Technology Co Ltd; Wuling Power Corp Ltd
Priority date: 2022-08-05
Filing date: 2022-08-05
Publication date: 2024-08-16
Anticipated expiration: 2042-08-05
Also published as: CN115185313A

Abstract

The invention provides a trend tracking and early warning method and device for bearing bush temperature of a hydroelectric generating set, and relates to the technical field of hydroelectric generating sets. The method comprises the following steps: acquiring current equipment parameters and a corresponding healthy temperature rise curve of a hydroelectric generating set to be monitored; determining the state of the hydroelectric generating set based on the equipment parameters; under the condition that the state of the hydroelectric generating set is a starting running state, determining a first temperature value at the current moment, a second temperature value at the starting moment and a first duration, wherein the first duration is the duration between the current moment and the starting moment; and determining whether the temperature of the bearing tile of the hydroelectric generating set is normal or not based on the first temperature value at the current moment, the second temperature value and the first time length at the starting moment and the healthy temperature rise curve. Therefore, based on the comparison result of the first temperature rise value obtained by the healthy temperature rise curve and the temperature rise value in actual operation, whether the temperature of the bearing tile is abnormal or not can be determined, and therefore the accuracy and the reliability of the temperature of the bearing tile of the hydroelectric generating set are improved.

Description

Trend tracking and early warning method and device for bearing bush temperature of hydroelectric generating set

Technical Field

The disclosure relates to the technical field of hydroelectric generating sets, in particular to a trend tracking and early warning method and device for bearing bush temperature of a hydroelectric generating set.

Background

The hydroelectric generating set is used as core equipment for energy conversion of a hydropower station, and the constituent parts of the hydroelectric generating set are mutually coupled, so that the development trend of complexity and high integration is presented. Meanwhile, as the running environment of the hydroelectric generating set is bad and is influenced by coupling factors such as waterpower, machinery, electromagnetism and the like, the safety risks such as abnormal vibration, coupling faults, fatigue degradation and even structural damage of equipment are possibly caused, and the running environment is increasingly outstanding.

The bearing tile of the hydroelectric generating set is one of key equipment for ensuring the normal operation of the hydroelectric generating set, if the temperature of the bearing bush abnormally fluctuates due to some reasons and is even increased sharply, the bearing bush surface can be burnt, and even the whole set can be forced to stop, so that the normal power generation and operation safety of the hydroelectric generating set are seriously affected. Therefore, how to monitor the temperature of the bearing tiles to ensure the safe operation of the hydroelectric generating set is very important.

Disclosure of Invention

The present disclosure aims to solve, at least to some extent, one of the technical problems in the related art.

An embodiment of a first aspect of the present disclosure provides a trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set, including:

Acquiring current equipment parameters and a corresponding healthy temperature rise curve of a hydroelectric generating set to be monitored;

determining a state of the hydroelectric generating set based on the device parameter;

under the condition that the state of the hydroelectric generating set is a starting running state, determining a first temperature value at the current moment, a second temperature value at the starting moment and a first duration, wherein the first duration is the duration between the current moment and the starting moment;

And determining whether the temperature of the bearing tile of the hydroelectric generating set is normal or not based on the first temperature value at the current moment, the second temperature value at the starting moment, the first duration and the healthy temperature rise curve.

Optionally, the obtaining the current equipment parameters and the corresponding healthy temperature rise curves of the hydroelectric generating set to be monitored includes:

and determining a healthy temperature rise curve from a preset temperature rise curve library based on the type of the hydroelectric generating set.

Optionally, before determining the healthy temperature rise curve from the preset temperature rise curve library, the method further includes:

inputting each moment in the running period of any type of hydroelectric generating set into a trained neural network model to obtain a reference Wen Shengzhi corresponding to each moment in the running period;

adding a margin value to each reference Wen Shengzhi to obtain a corresponding health temperature rise value;

Fitting each health temperature rise value according to each moment in the running period to generate a health temperature rise curve.

Optionally, before inputting each time in the running period of the hydroelectric generating set of any type into the trained neural network model, the method further comprises:

acquiring a historical data set, wherein the historical data set comprises labeled temperature rise values corresponding to various moments after any type of hydroelectric generating set is started and operated;

inputting each moment into an initial network model to obtain a preset temperature rise value corresponding to each moment;

and correcting the initial network model according to the difference between each preset temperature rise value and the labeling temperature rise value to generate a trained neural network model.

Optionally, the determining whether the temperature of the bearing tile of the hydroelectric generating set is normal based on the first temperature value at the current moment, the second temperature value at the startup moment, the first duration and the healthy temperature rise curve includes:

Determining a first temperature rise value corresponding to the first time length in the healthy temperature rise curve;

Fusing the second temperature value with the first temperature rise value to obtain a third temperature value;

determining that the hydroelectric generating set bearing tile temperature is abnormal under the condition that the first temperature value is larger than the third temperature value;

And under the condition that the first temperature value is smaller than or equal to the third temperature value, determining that the hydroelectric generating set bearing tile is normal in temperature.

Optionally, after said determining whether the hydroelectric generating set bearing tile temperature is normal, further comprising:

And under the condition that the temperature of the bearing tile of the hydroelectric generating set is abnormal, carrying out abnormal early warning.

Optionally, after the determining the first temperature value at the current time, the second temperature value at the start-up time and the first time length, the method further includes:

acquiring real-time temperature values corresponding to the hydropower unit at all moments in the first time period;

and generating a corresponding actual temperature rise curve based on the difference value between each real-time temperature value and the second temperature value.

Optionally, the determining whether the hydroelectric generating set bearing tile is normal in temperature includes:

under the condition that the actual temperature rise curve is positioned below the healthy temperature rise curve, determining that the temperature of the bearing tile of the hydroelectric generating set is normal;

and determining that the temperature of the bearing tile of the hydroelectric generating set is abnormal under the condition that the intersection exists between the actual temperature rise curve and the healthy temperature rise curve or the actual temperature rise curve is positioned above the healthy temperature rise curve.

An embodiment of a second aspect of the present disclosure provides a trend tracking and early warning device for bearing bush temperature of a hydroelectric generating set, including:

The acquisition module is used for acquiring current equipment parameters and corresponding healthy temperature rise curves of the hydroelectric generating set to be monitored.

The first determining module is used for determining the state of the hydroelectric generating set based on the equipment parameters;

The second determining module is used for determining a first temperature value at the current moment, a second temperature value at the starting moment and a first duration when the state of the hydroelectric generating set is a starting running state, wherein the first duration is the duration between the current moment and the starting moment;

and the third determining module is used for determining whether the temperature of the bearing tile of the hydroelectric generating set is normal or not based on the first temperature value at the current moment, the second temperature value and the first time length at the starting moment and the healthy temperature rise curve.

Optionally, the acquiring module is specifically configured to:

Optionally, the acquiring module is further specifically configured to:

Optionally, the third determining module is specifically configured to:

Optionally, the third determining module is further configured to:

Optionally, the method further comprises a generating module for:

Optionally, the third determining module is specifically configured to:

Embodiments of a third aspect of the present disclosure provide a computer device comprising: the system comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein when the processor executes the program, the trend tracking and early warning method for the bearing bush temperature of the hydroelectric generating set is realized.

An embodiment of a fourth aspect of the present disclosure proposes a non-transitory computer readable storage medium storing a computer program, which when executed by a processor implements a trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set as proposed in the embodiment of the first aspect of the present disclosure.

An embodiment of a fifth aspect of the present disclosure proposes a computer program product, which when executed by an instruction processor in the computer program product, performs the trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set according to the embodiment of the first aspect of the present disclosure.

According to the trend tracking and early warning method, device, computer equipment and storage medium for the bearing bush temperature of the hydroelectric generating set, the current equipment parameters and the corresponding healthy temperature rise curves of the hydroelectric generating set to be monitored can be obtained firstly, then the state of the hydroelectric generating set can be determined based on the equipment parameters, under the condition that the state of the hydroelectric generating set is in a starting running state, a first temperature value at the current moment, a second temperature value at the starting moment and a first duration are determined, wherein the first duration is the duration between the current moment and the starting moment, and then whether the bearing bush temperature of the hydroelectric generating set is normal can be determined based on the first temperature value at the current moment, the second temperature value at the starting moment and the first duration and the healthy temperature rise curves. Therefore, based on the time length between the current moment and the starting moment, the corresponding first temperature rise value can be obtained from the healthy temperature rise curve, the temperature rise value corresponding to the current moment is determined according to the temperature value of the current moment and the temperature value of the starting moment of the hydroelectric generating set, and then the temperature rise value is compared with the first temperature rise value, so that whether the temperature of the bearing tile of the hydroelectric generating set at the current moment is abnormal or not can be determined, and the accuracy and the reliability of the temperature of the bearing tile of the hydroelectric generating set are improved.

Additional aspects and advantages of the disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the disclosure.

Drawings

The foregoing and/or additional aspects and advantages of the present disclosure will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

Fig. 1 is a schematic flow chart of a trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set according to an embodiment of the disclosure;

fig. 2 is a schematic flow chart of a trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set according to another embodiment of the disclosure;

Fig. 2A is a schematic diagram of a trend tracking and early warning process of bearing bush temperature of a hydroelectric generating set according to an embodiment of the disclosure;

fig. 3 is a schematic flow chart of a trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set according to another embodiment of the disclosure;

FIG. 3A is a schematic diagram of a trend tracking and early warning process for bearing bush temperature of a hydroelectric generating set according to an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of a trend tracking and early warning device for bearing bush temperature of a hydroelectric generating set according to an embodiment of the present disclosure;

Fig. 5 illustrates a block diagram of an exemplary computer device suitable for use in implementing embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present disclosure and are not to be construed as limiting the present disclosure.

The following describes a trend tracking and early warning method, a device, computer equipment and a storage medium for bearing bush temperature of a hydroelectric generating set according to an embodiment of the disclosure with reference to the accompanying drawings.

The embodiment of the disclosure is exemplified by the fact that the trend tracking and early warning method for the bearing shoe temperature of the hydroelectric generating set is configured in a trend tracking and early warning device for the bearing shoe temperature of the hydroelectric generating set, and the trend tracking and early warning device for the bearing shoe temperature of the hydroelectric generating set can be applied to any computer equipment, so that the computer equipment can execute the trend tracking and early warning function for the bearing shoe temperature of the hydroelectric generating set.

The computer device may be a personal computer (Personal Computer, abbreviated as PC), a cloud device, a mobile device, etc., and the mobile device may be, for example, a mobile phone, a tablet computer, a personal digital assistant, a wearable device, a vehicle-mounted device, etc., which have various hardware devices including an operating system, a touch screen, and/or a display screen.

Fig. 1 is a schematic flow chart of a trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set according to an embodiment of the disclosure.

As shown in FIG. 1, the trend tracking and early warning method for the bearing bush temperature of the hydroelectric generating set can comprise the following steps:

Step 101, acquiring current equipment parameters and corresponding healthy temperature rise curves of the hydroelectric generating set to be monitored.

The hydroelectric generating set may be any type of hydroelectric generating set, such as a mixed flow hydroelectric generating set, an axial flow hydroelectric generating set, etc., which is not limited in this disclosure.

The device parameter may be a parameter value of any component in the hydroelectric generating set to be detected, for example, may be a rotation speed of the hydroelectric generating set, and the disclosure is not limited thereto.

In addition, the temperature rise may be understood as a temperature difference value, a temperature change value, or the like; the healthy temperature rise curve may be understood as a temperature change curve, which may be a standard curve set in advance, or the like, which is not limited in the present disclosure.

Step 102, determining the state of the hydroelectric generating set based on the equipment parameters.

The state of the hydroelectric generating set may be various, for example, may be a start-up running state, or may be a stop state, an unoperated state, etc., which is not limited in this disclosure.

For example, in the case where the device parameter is the rotation speed, if the rotation speed is zero, it may be determined that the state of the hydroelectric generating set is: stopping the machine in an unoperated state; or if the rotation speed of the hydroelectric generating set is n1, determining that the current state of the hydroelectric generating set is: boot-up running state, etc. The present disclosure is not limited in this regard.

Step 103, under the condition that the state of the hydroelectric generating set is a starting running state, determining a first temperature value at the current moment, a second temperature value at the starting moment and a first duration, wherein the first duration is the duration between the current moment and the starting moment.

Optionally, the state of the hydroelectric generating set can be monitored, when the rotation speed of the hydroelectric generating set is a non-zero value, the hydroelectric generating set can be determined to be started at the moment, and then a second temperature value at the moment of starting the hydroelectric generating set can be obtained. For example, the temperature value of the hydroelectric generating set can be obtained by a temperature sensor or the like.

For example, if the current time is t1 and the rotation speed of the hydro-power generating unit is n2, it may be determined that the hydro-power generating unit is in the start-up operation, and the first temperature value at this time is: a1; if the starting time of the hydroelectric generating set is t2, the second temperature value corresponding to the t2 is as follows: a2, the first duration from the starting time to the current time can be determined as follows: t2-t1, etc., to which the present disclosure is not limited.

And 104, determining whether the temperature of the bearing tile of the hydroelectric generating set is normal or not based on the first temperature value at the current moment, the second temperature value and the first time length at the starting moment and the healthy temperature rise curve.

For example, after the first time period is obtained to be determined, a first temperature rise value corresponding to the first time period can be found in the healthy temperature rise curve, a second temperature rise value between the first temperature value and the second temperature value can be determined, and the normal temperature of the bearing tile of the hydroelectric generating set can be determined under the condition that the second temperature rise value is smaller than or equal to the first temperature rise value; and under the condition that the second temperature rise value is larger than the first temperature rise value, determining that the temperature of the bearing tile of the hydroelectric generating set is abnormal.

In general, the temperature values of the bearing tiles of the hydroelectric generating set may change in different seasons, and if only a single temperature value is used, the temperature judgment of the bearing tiles may be inaccurate. Therefore, in the embodiment of the disclosure, trend tracking and early warning of the bearing tile temperature of the hydroelectric generating set can be performed by using the temperature rise value and the temperature rise curve, so that inaccurate temperature judgment caused by environmental reasons can be avoided as much as possible, and the accuracy and reliability of determining the bearing tile temperature of the hydroelectric generating set are improved.

According to the embodiment of the disclosure, the current equipment parameters and the corresponding healthy temperature rise curve of the hydroelectric generating set to be monitored can be obtained first, then the state of the hydroelectric generating set can be determined based on the equipment parameters, under the condition that the state of the hydroelectric generating set is a starting running state, a first temperature value at the current moment, a second temperature value at the starting moment and a first time length are determined, wherein the first time length is the time length between the current moment and the starting moment, and then whether the temperature of the bearing tile of the hydroelectric generating set is normal can be determined based on the first temperature value at the current moment, the second temperature value at the starting moment and the first time length and the healthy temperature rise curve. Therefore, based on the time length between the current moment and the starting moment, the corresponding first temperature rise value can be obtained from the healthy temperature rise curve, the temperature rise value corresponding to the current moment is determined according to the temperature value of the current moment and the temperature value of the starting moment of the hydroelectric generating set, and then the temperature rise value is compared with the first temperature rise value, so that whether the temperature of the bearing tile of the hydroelectric generating set at the current moment is abnormal or not can be determined, and the accuracy and the reliability of the temperature of the bearing tile of the hydroelectric generating set are improved.

Fig. 2 is a schematic flow chart of a trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set according to an embodiment of the disclosure.

As shown in FIG. 2, the trend tracking and early warning method for the bearing bush temperature of the hydroelectric generating set can comprise the following steps:

Step 201, current equipment parameters of the hydroelectric generating set to be monitored and corresponding healthy temperature rise curves are obtained.

Alternatively, the healthy temperature rise curve may be determined from a preset temperature rise curve library based on the type of the hydroelectric generating set.

In the temperature rise curve library, a plurality of temperature rise curves can be stored, each temperature rise curve can correspond to the type of the hydroelectric generating set, and the like, and the temperature rise curve library is not limited by the present disclosure.

Therefore, in the embodiment of the disclosure, the preset temperature rise curve library may be traversed based on the type of the hydroelectric generating set, so as to obtain a temperature rise curve corresponding to the type of the hydroelectric generating set from the temperature rise curve library, and the temperature rise curve is determined to be a healthy temperature rise curve.

It can be understood that the historical operation data of the hydroelectric generating set can be processed to generate a temperature rise curve, and the temperature rise curve is added to a temperature rise curve library, so that in the actual use process, a corresponding healthy temperature rise curve can be obtained from the temperature rise curve library according to the type of the hydroelectric generating set.

Optionally, each time in the running period of any type of hydroelectric generating set may be input to the trained neural network model to obtain reference temperature rise values corresponding to each time in the running period, then a margin value may be added to each reference temperature rise value to obtain corresponding healthy temperature rise values, and then each healthy temperature rise value is fitted according to each time in the running period to generate a healthy temperature rise curve.

It can be understood that any time value in the running period of any type of hydroelectric generating set can be input into the neural network model after training, and the reference temperature rise value corresponding to any time value can be output through the processing of the neural network model.

In addition, the margin value may be set in advance, or may be adjusted according to the actual situation, or the like, which is not limited in the present disclosure.

Therefore, in the embodiment of the disclosure, after the reference temperature rise value is obtained, a margin value can be added on the basis of each reference temperature rise value, so that a healthy temperature rise value corresponding to each reference temperature rise value is obtained. For example, if the margin value is 1, if the reference temperature rise values are respectively: 7. 10, 12, then the resulting rise in health temperature after adding the margin value may be: 8. 11, 13, etc., to which the present disclosure is not limited.

It will be appreciated that after the healthy temperature rise values are obtained, each healthy temperature rise value may be fitted at various times during the operating cycle to generate a healthy temperature rise curve. The fitting may be performed by a least square method, or may also be performed by software or the like, so as to obtain a healthy temperature rise curve, which is not limited in the present disclosure.

It will be appreciated that the training of the initial model may be performed to generate a trained neural network model.

Optionally, a historical data set may be obtained first, where the historical data set includes labeled temperature rise values corresponding to each time after the hydroelectric generating set of any type is started and operated, then each time may be input into an initial network model to obtain a predicted temperature rise value corresponding to each time, then the initial network model may be corrected according to a difference between each predicted temperature rise value and the labeled temperature rise value, so as to generate a trained neural network model, then each time in an operation period of the hydroelectric generating set of any same type may be input into the trained neural network model, so as to obtain a reference temperature rise value corresponding to each time in the operation period, and then each reference temperature rise value may be fitted according to each time in the operation period, so as to generate a healthy temperature rise curve.

The temperature value corresponding to each moment after the starting-up operation of each water motor unit can be obtained, and then the difference value between the temperature value of each moment and the temperature value of the starting-up moment after the starting-up operation of any water motor unit can be determined as the marked temperature rise value corresponding to each moment after the starting-up operation.

It can be understood that the temperature rise values of the labeling at various moments after the startup of different hydroelectric generating sets under the same type can be obtained according to the types of the hydroelectric generating sets.

In addition, the initial network model may be any neural network model, for example, may be a multi-layer feedforward neural network based on a Back Propagation (BP) algorithm, or may also be any other neural network, etc., which is not limited in this disclosure.

It can be understood that after the same type of hydroelectric generating set is started, each time value is input into the initial network model, so that the preset temperature rise value corresponding to each time can be output after the processing of the initial network model. And then, determining the loss value according to the difference between the preset temperature rise value and the marked temperature rise value which are respectively corresponding to each moment. The initial network model may then be modified based on the loss values to generate a trained neural network model.

Step 202, determining the state of the hydroelectric generating set based on the equipment parameters.

Step 203, determining a first temperature value at the current moment, a second temperature value at the starting moment and a first duration when the state of the hydroelectric generating set is the starting running state, wherein the first duration is the duration between the current moment and the starting moment.

It should be noted that, the specific content and implementation manner of step 202 and step 203 may refer to the descriptions of other embodiments of the present disclosure, and will not be repeated herein.

Step 204, determining a first temperature rise value corresponding to the first time length in the healthy temperature rise curve.

It can be understood that the healthy temperature rise curve may include a temperature rise value corresponding to each moment, and the starting point of the healthy temperature rise curve may be the starting moment of the hydro-power generating unit, so that each moment value in the healthy temperature rise curve, that is, a time length corresponding to the starting moment of the hydro-power generating unit, and the like, and the disclosure is not limited to this.

For example, if the first duration is 5 minutes, the temperature rise value corresponding to the position "5 minutes" from the starting time of the water turbine set, that is, the first temperature rise value, may be found in the healthy temperature rise curve.

Or if the current time of the hydroelectric generating set is: and (6) minutes, then the temperature rise value corresponding to '6 minutes' can be directly found in the healthy temperature rise curve, namely the first temperature rise value.

The above examples are merely illustrative, and are not intended to limit the first temperature rise value or the like in the embodiments of the present disclosure.

Optionally, for the health temperature rise curve, a certain margin value may be set first, and then a first temperature rise value corresponding to the first time length may be obtained therefrom, which is not limited in this disclosure.

In step 205, the second temperature value is fused with the first temperature rise value to obtain a third temperature value.

And adding the second temperature value and the first temperature rise value, wherein the second temperature value is a temperature value corresponding to the starting time of the water motor unit, and the obtained result is a third temperature value, namely a temperature value corresponding to the current moment under a healthy temperature rise curve.

For example, if the second temperature value corresponding to the startup time of the hydroelectric generating set is: 20 ℃ and if the first time length from the starting time of the hydroelectric generating set at the current time is: 10 minutes, determining a first temperature rise value corresponding to 10 minutes based on a healthy temperature rise curve as follows: 5 ℃, then according to the healthy temperature rise curve, the third temperature value corresponding to the current moment can be determined as follows: 25 c, etc., which is not limited by the present disclosure.

And 206, determining that the bearing tile of the hydroelectric generating set is normal in temperature under the condition that the first temperature value is smaller than or equal to the third temperature value.

For example, if the first temperature value at the current time is 15 ℃, the determined third temperature value is 20 ℃ based on the healthy temperature rise curve and the second temperature value at the start-up time, and since 15 ℃ is less than 20 ℃, it can be determined that the temperature of the bearing tile of the hydroelectric generating set at the current time is normal, and the disclosure is not limited thereto.

And step 207, determining that the temperature of the bearing tile of the hydroelectric generating set is abnormal under the condition that the first temperature value is larger than the third temperature value.

For example, if the first temperature value at the current time is 30 ℃, the determined third temperature value is 20 ℃ based on the healthy temperature rise curve and the second temperature value at the start-up time, and since the 30 ℃ is greater than 20 ℃, it can be determined that the temperature of the bearing tile of the hydroelectric generating set is abnormal at the current time, which is not limited in this disclosure.

And step 208, carrying out abnormality early warning under the condition that the temperature of the bearing tiles of the hydroelectric generating set is abnormal.

It can be understood that, because the bearing tile of the hydroelectric generating set is a key device for ensuring the normal operation of the hydroelectric generating set, if the temperature of the bearing bush abnormally fluctuates for some reason or even rises sharply, the bearing bush surface can be burnt, and even the whole generating set can be forced to stop, so that the normal power generation and operation safety of the hydroelectric generating set are seriously affected. Therefore, in the embodiment of the disclosure, when the temperature of the bearing tile of the hydroelectric generating set is abnormal, abnormal early warning can be carried out.

The abnormal early warning mode is various, for example, sound reminding can be carried out, or the abnormal early warning can be realized by flashing an indicator lamp, for example, the flashing red light of the indicator lamp can be used for representing the occurrence of the abnormality; or can also be displayed on a display interface; or can also send a notification, such as a short message, a mail form, etc., to the terminal device associated with the staff; or may also be pushed by an associated terminal device, etc., which is not limited by the present disclosure.

Optionally, after the healthy temperature rise curve is obtained, a certain margin value can be set, a second temperature value at the starting time is added on the basis of the healthy temperature rise curve to obtain a standard temperature curve, and then the actual temperature rise curve can be matched with the standard temperature curve to determine the temperature condition of the bearing tiles of the hydroelectric generating set.

For example, if the actual temperature rise curve is below the standard temperature curve, as shown in FIG. 2A, then the hydroelectric generating set bearing tile may be determined to be normal. If the actual temperature rise curve is above the standard temperature curve, or there is an intersection, then the hydroelectric generating set bearing tile temperature anomaly may be determined, etc., as not limited by the present disclosure.

According to the method and the device for monitoring the temperature rise of the hydroelectric generating set, the current equipment parameters and the corresponding healthy temperature rise curve of the hydroelectric generating set to be monitored can be obtained, then the state of the hydroelectric generating set can be determined based on the equipment parameters, under the condition that the state of the hydroelectric generating set is a starting operation state, a first temperature value at the current moment, a second temperature value at the starting moment and a first time length are determined, wherein the first time length is the time length between the current moment and the starting moment, then the first temperature rise value corresponding to the first time length in the healthy temperature rise curve can be determined, the second temperature value and the first temperature rise value are fused to obtain a third temperature value, under the condition that the first temperature value is smaller than or equal to the third temperature value, the temperature of a bearing tile of the hydroelectric generating set is determined to be normal, or under the condition that the first temperature value is larger than the third temperature value, the temperature of the bearing tile of the hydroelectric generating set is determined to be abnormal, and abnormal early warning is carried out. Therefore, the corresponding first temperature rise value can be obtained from the healthy temperature rise curve based on the time between the current moment and the starting moment, the third temperature rise value obtained after the fusion of the temperature value of the current moment and the first temperature rise value of the hydroelectric generating set is matched with the third temperature value and the first temperature value of the current moment, and the temperature condition of the bearing tile of the hydroelectric generating set at the current moment can be determined according to the matching result, so that the accuracy and the reliability of the temperature of the bearing tile of the hydroelectric generating set are improved.

Fig. 3 is a schematic flow chart of a trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set according to an embodiment of the disclosure.

As shown in FIG. 3, the trend tracking and early warning method for the bearing bush temperature of the hydroelectric generating set can comprise the following steps:

Step 301, current equipment parameters and corresponding healthy temperature rise curves of the hydroelectric generating set to be monitored are obtained.

Step 302, determining the state of the hydroelectric generating set based on the device parameters.

Step 303, determining a first temperature value at the current moment, a second temperature value at the starting moment and a first duration when the state of the hydroelectric generating set is the starting running state, wherein the first duration is the duration between the current moment and the starting moment.

It should be noted that, the specific content and implementation manner of the steps 301 to 303 may refer to the descriptions of other embodiments of the disclosure, and are not repeated herein.

And step 304, acquiring real-time temperature values corresponding to all moments of the hydroelectric generating set in a first duration.

For example, if the current time is "10 minutes", that is, 10 minutes from the startup of the hydro-power generating unit, the real-time temperature values corresponding to the respective times within "10 minutes" of the startup of the hydro-power generating unit may be obtained. For example, the values of the temperature sensors at various moments can be obtained, and the present disclosure is not limited thereto.

Step 305, generating a corresponding actual temperature rise curve based on the difference between each real-time temperature value and the second temperature value.

The second temperature value is a temperature value at the starting time of the hydroelectric generating set, each real-time temperature value is a temperature value corresponding to each time after the hydroelectric generating set is started, each real-time temperature value and the second temperature value are respectively differenced to obtain each difference value, and the difference values are connected or fitted according to each time to generate a corresponding actual temperature rise curve.

It can be understood that the actual temperature rise curve can be used for representing the temperature rise value corresponding to each moment respectively from the starting moment to the current moment in the actual operation process of the hydroelectric generating set.

And 306, determining that the temperature of the bearing tile of the hydroelectric generating set is normal under the condition that the actual temperature rise curve is positioned below the healthy temperature rise curve.

It can be understood that if the actual temperature rise curve is always located below the healthy temperature rise curve, the temperature change trend of the bearing tiles of the hydroelectric generating set in actual operation can be considered to be smaller than the temperature change trend corresponding to the healthy temperature rise curve, and then the temperature of the bearing tiles of the hydroelectric generating set can be considered to be normal.

For example, if the actual temperature rise curve and the healthy temperature rise curve are located below the healthy temperature rise curve as shown in fig. 3A, it may be determined that the hydroelectric generating set bearing tile is normal, and so on, which is not limited by the present disclosure.

And step 307, determining that the temperature of the bearing tile of the hydroelectric generating set is abnormal under the condition that the intersection exists between the actual temperature rise curve and the healthy temperature rise curve or the actual temperature rise curve is positioned above the healthy temperature rise curve.

It is understood that if the actual temperature rise curve and the healthy temperature rise curve intersect, it is considered that the temperature change of the bearing tile may be too large at a certain moment or in a certain period of time in the actual operation process of the hydroelectric generating set, and the temperature change of the bearing tile exceeds the temperature change of the bearing tile in the healthy temperature rise curve, and then it is considered that the temperature of the bearing tile of the hydroelectric generating set may be abnormal.

Or if the actual temperature rise curve is located above the healthy temperature rise curve, the temperature change trend of the bearing tiles of the hydroelectric generating set in actual operation can be considered, the temperature change trend corresponding to the healthy temperature rise curve is different, the abnormal situation can occur, and the temperature of the bearing tiles of the hydroelectric generating set can be considered abnormal.

Optionally, for the healthy temperature rise curve, after a certain margin value may be added, the healthy temperature rise curve is compared with the actual temperature rise curve, which is not limited in the disclosure.

Optionally, after the real-time temperature values corresponding to the respective moments of the hydroelectric generating set in the first duration are obtained, differences between the real-time temperature values and the second temperature values corresponding to the respective moments can be determined, then the health temperature rise values of the respective moments in the health temperature rise curve can be obtained, and then the differences corresponding to the respective moments can be compared with the health temperature rise values of the respective moments. If the difference value corresponding to the moment is smaller than or equal to the health temperature rise value at the same moment, the temperature of the bearing tile of the hydroelectric generating set can be considered to be normal; if the corresponding difference value at a certain moment is larger than the corresponding healthy temperature rise value, the temperature of the bearing tile of the hydroelectric generating set can be considered to be abnormal, and the like.

For example, after the hydroelectric generating set is started and operated for 60 minutes, if the difference between the real-time temperature value and the second temperature value is 30 ℃ at the time of 60 minutes, and the healthy temperature rise value corresponding to 60 minutes is 24 ℃ and is greater than 24 ℃ from the healthy temperature rise curve, the abnormal temperature of the bearing tile of the hydroelectric generating set can be determined. Or if the hydroelectric generating set is started and operated for 100 minutes, if the difference between the real-time temperature value and the second temperature value is 25 ℃ in the 100 th minute, and the healthy temperature rise value corresponding to the 100 th minute is determined to be 40 ℃ from the healthy temperature rise curve, and the temperature of the bearing tile of the hydroelectric generating set is determined to be normal if the healthy temperature rise value is less than 40 ℃ in the 25 th minute.

It should be noted that the above examples are illustrative only and should not be taken as limiting the manner in which the temperature conditions of the hydroelectric generating set bearing tiles are determined in the embodiments of the present disclosure.

And 308, carrying out abnormality early warning under the condition that the temperature of the bearing tile of the hydroelectric generating set is abnormal.

According to the embodiment of the disclosure, the current equipment parameters and the corresponding healthy temperature rise curves of the hydroelectric generating set to be monitored can be obtained first, then the state of the hydroelectric generating set can be determined based on the equipment parameters, under the condition that the state of the hydroelectric generating set is a starting operation state, a first temperature value at the current moment, a second temperature value at the starting moment and a first time length are determined, wherein the first time length is the time length between the current moment and the starting moment, then the real-time temperature values of the hydroelectric generating set corresponding to each moment in the first time length can be obtained, a corresponding actual temperature rise curve is generated based on the difference value between each real-time temperature value and the second temperature value, under the condition that the actual temperature rise curve is located below the healthy temperature rise curve, the bearing tile temperature of the hydroelectric generating set is determined to be normal, and under the condition that the actual temperature rise curve and the healthy temperature rise curve are intersected, or the actual temperature rise curve is located above the healthy temperature rise curve, the bearing tile temperature of the hydroelectric generating set is determined to be abnormal. Therefore, an actual temperature rise curve can be generated based on the difference value between the real-time temperature value and the second temperature value at each moment in the current moment and the starting moment, and then the temperature condition of the bearing tile of the hydroelectric generating set at the current moment can be determined according to the matching condition of the actual temperature rise curve and the healthy temperature rise curve, so that the accuracy and the reliability of the temperature of the bearing tile of the hydroelectric generating set are improved.

In order to achieve the embodiment, the disclosure further provides a trend tracking and early warning device for bearing bush temperature of the hydroelectric generating set.

Fig. 4 is a schematic structural diagram of a trend tracking and early warning device for bearing bush temperature of a hydroelectric generating set according to an embodiment of the disclosure.

As shown in fig. 4, the trend tracking and early warning device 100 for bearing bush temperature of a hydroelectric generating set may include: the acquisition module 110, the first determination module 120, the second determination module 130, and the third determination module 140.

The acquiring module 110 is configured to acquire current equipment parameters and a corresponding healthy temperature rise curve of the hydroelectric generating set to be monitored.

A first determining module 120 for determining a state of the hydroelectric generating set based on the device parameter;

a second determining module 130, configured to determine, when the state of the hydro-power generating unit is a startup running state, a first temperature value at a current time, a second temperature value at a startup time, and a first duration, where the first duration is a duration between the current time and the startup time;

And the third determining module 140 is configured to determine whether the temperature of the bearing tile of the hydroelectric generating set is normal based on the first temperature value at the current moment, the second temperature value and the first duration at the startup moment, and the healthy temperature rise curve.

Optionally, the acquiring module 110 is specifically configured to:

Optionally, the obtaining module 110 is further specifically configured to:

Optionally, the third determining module 140 is specifically configured to:

Optionally, the third determining module 140 is further configured to:

Optionally, the method further comprises a generating module for:

Optionally, the third determining module 140 is specifically configured to:

The functions and specific implementation principles of the foregoing modules in the embodiments of the present disclosure may refer to the foregoing method embodiments, and are not repeated herein.

The trend tracking and early warning device for the bearing bush temperature of the hydroelectric generating set can acquire current equipment parameters and corresponding healthy temperature rise curves of the hydroelectric generating set to be monitored, can determine the state of the hydroelectric generating set based on the equipment parameters, and can determine whether the bearing bush temperature of the hydroelectric generating set is normal or not based on the first temperature value at the current moment, the second temperature value at the starting moment and the first time length under the condition that the state of the hydroelectric generating set is the starting running state, wherein the first time length is the time length between the current moment and the starting moment, and can determine whether the bearing bush temperature of the hydroelectric generating set is normal or not based on the first temperature value at the current moment, the second temperature value at the starting moment and the first time length and the healthy temperature rise curves. Therefore, based on the time length between the current moment and the starting moment, the corresponding first temperature rise value can be obtained from the healthy temperature rise curve, the temperature rise value corresponding to the current moment is determined according to the temperature value of the current moment and the temperature value of the starting moment of the hydroelectric generating set, and then the temperature rise value is compared with the first temperature rise value, so that whether the temperature of the bearing tile of the hydroelectric generating set at the current moment is abnormal or not can be determined, and the accuracy and the reliability of the temperature of the bearing tile of the hydroelectric generating set are improved.

To achieve the above embodiments, the present disclosure further proposes a computer device including: the system comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the trend tracking and early warning method for the bearing bush temperature of the hydroelectric generating set according to the embodiment of the disclosure when executing the program.

In order to achieve the above embodiments, the present disclosure further provides a non-transitory computer readable storage medium storing a computer program, where the computer program when executed by a processor implements a trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set according to the foregoing embodiments of the present disclosure.

In order to implement the above embodiments, the present disclosure further provides a computer program product, which when executed by an instruction processor in the computer program product, performs the trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set according to the foregoing embodiments of the present disclosure.

Fig. 5 illustrates a block diagram of an exemplary computer device suitable for use in implementing embodiments of the present disclosure. The computer device 12 shown in fig. 5 is merely an example and should not be construed as limiting the functionality and scope of use of the disclosed embodiments.

As shown in FIG. 5, the computer device 12 is in the form of a general purpose computing device. Components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.

Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include industry Standard architecture (Industry Standard Architecture; hereinafter ISA) bus, micro channel architecture (Micro Channel Architecture; hereinafter MAC) bus, enhanced ISA bus, video electronics standards Association (Video Electronics Standards Association; hereinafter VESA) local bus, and peripheral component interconnect (PERIPHERAL COMPONENT INTERCONNECTION; hereinafter PCI) bus.

Computer device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by computer device 12 and includes both volatile and nonvolatile media, removable and non-removable media.

Memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (Random Access Memory; hereinafter: RAM) 30 and/or cache memory 32. The computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, commonly referred to as a "hard disk drive"). Although not shown in fig. 5, a disk drive for reading from and writing to a removable nonvolatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable nonvolatile optical disk (e.g., a compact disk read only memory (Compact Disc Read Only Memory; hereinafter CD-ROM), digital versatile read only optical disk (Digital Video Disc Read Only Memory; hereinafter DVD-ROM), or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the various embodiments of the disclosure.

A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods in the embodiments described in this disclosure.

The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the computer device 12, and/or any devices (e.g., network card, modem, etc.) that enable the computer device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Moreover, the computer device 12 may also communicate with one or more networks such as a local area network (Local Area Network; hereinafter: LAN), a wide area network (Wide Area Network; hereinafter: WAN) and/or a public network such as the Internet via the network adapter 20. As shown, network adapter 20 communicates with other modules of computer device 12 via bus 18. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with computer device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.

The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, for example, implementing the methods mentioned in the foregoing embodiments.

According to the technical scheme, the current equipment parameters and the corresponding healthy temperature rise curves of the hydroelectric generating set to be monitored can be obtained first, then the state of the hydroelectric generating set can be determined based on the equipment parameters, under the condition that the state of the hydroelectric generating set is a starting running state, a first temperature value at the current moment, a second temperature value at the starting moment and a first duration are determined, wherein the first duration is the duration between the current moment and the starting moment, and then whether the temperature of the bearing tile of the hydroelectric generating set is normal or not can be determined based on the first temperature value at the current moment, the second temperature value at the starting moment and the first duration and the healthy temperature rise curves. Therefore, based on the time length between the current moment and the starting moment, the corresponding first temperature rise value can be obtained from the healthy temperature rise curve, the temperature rise value corresponding to the current moment is determined according to the temperature value of the current moment and the temperature value of the starting moment of the hydroelectric generating set, and then the temperature rise value is compared with the first temperature rise value, so that whether the temperature of the bearing tile of the hydroelectric generating set at the current moment is abnormal or not can be determined, and the accuracy and the reliability of the temperature of the bearing tile of the hydroelectric generating set are improved.

In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.

Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present disclosure, the meaning of "a plurality" is at least two, such as two, three, etc., unless explicitly specified otherwise.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present disclosure in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present disclosure.

Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.

It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.

Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.

Furthermore, each functional unit in the embodiments of the present disclosure may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.

The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like. Although embodiments of the present disclosure have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the present disclosure, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the present disclosure.

Claims

1. A trend tracking and early warning method for bearing bush temperature of a hydroelectric generating set is characterized by comprising the following steps:

acquiring current equipment parameters and a corresponding healthy temperature rise curve of a hydroelectric generating set to be monitored, wherein the temperature rise is a temperature change value;

Determining whether the temperature of the bearing tile of the hydroelectric generating set is normal or not based on a first temperature value at the current moment, a second temperature value and a first duration at the starting moment and the healthy temperature rise curve;

the method for acquiring the current equipment parameters and the corresponding healthy temperature rise curves of the hydroelectric generating set to be monitored comprises the following steps: based on the type of the hydroelectric generating set, determining a healthy temperature rise curve from a preset temperature rise curve library;

before the health temperature rise curve is determined from the preset temperature rise curve library, the method further comprises the following steps:

Fitting each healthy temperature rise value according to each moment in the running period to generate a healthy temperature rise curve;

the determining whether the temperature of the bearing tile of the hydroelectric generating set is normal based on the first temperature value at the current moment, the second temperature value at the starting moment, the first duration and the healthy temperature rise curve comprises the following steps:

2. The method of claim 1, further comprising, prior to said inputting each time within the operational cycle of any type of hydroelectric generating set into the trained neural network model:

3. The method of claim 1, further comprising, after said determining if said hydroelectric power unit bearing tile temperature is normal:

4. A trend tracking and early warning device for bearing bush temperature of a hydroelectric generating set is characterized by comprising:

The acquisition module is used for acquiring current equipment parameters of the hydroelectric generating set to be monitored and a corresponding healthy temperature rise curve, wherein the temperature rise is a temperature change value;

the third determining module is used for determining whether the temperature of the bearing tile of the hydroelectric generating set is normal or not based on the first temperature value at the current moment, the second temperature value and the first duration at the starting moment and the healthy temperature rise curve;

5. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements a trend tracking and early warning method for bearing shoe temperature of a hydroelectric generating set as claimed in any one of claims 1 to 3 when the program is executed by the processor.