CN117688782B - Wear amount estimation method and device, electronic equipment and storage medium - Google Patents
Wear amount estimation method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN117688782B CN117688782B CN202410130218.2A CN202410130218A CN117688782B CN 117688782 B CN117688782 B CN 117688782B CN 202410130218 A CN202410130218 A CN 202410130218A CN 117688782 B CN117688782 B CN 117688782B
- Authority
- CN
- China
- Prior art keywords
- sub
- information
- vehicle
- simulation
- model
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000004088 simulation Methods 0.000 claims abstract description 158
- 229910000831 Steel Inorganic materials 0.000 claims abstract description 106
- 239000010959 steel Substances 0.000 claims abstract description 106
- 238000005260 corrosion Methods 0.000 claims abstract description 24
- 230000007797 corrosion Effects 0.000 claims abstract description 24
- 238000005070 sampling Methods 0.000 claims description 27
- 239000000463 material Substances 0.000 claims description 26
- 238000001595 flow curve Methods 0.000 claims description 23
- 230000002452 interceptive effect Effects 0.000 claims description 10
- 238000012876 topography Methods 0.000 claims description 4
- 238000004590 computer program Methods 0.000 claims description 3
- JEIPFZHSYJVQDO-UHFFFAOYSA-N iron(III) oxide Inorganic materials O=[Fe]O[Fe]=O JEIPFZHSYJVQDO-UHFFFAOYSA-N 0.000 claims description 2
- 230000000875 corresponding effect Effects 0.000 description 91
- 230000008569 process Effects 0.000 description 10
- 238000001514 detection method Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 238000005299 abrasion Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application relates to the field of logistics transportation technology, in particular to a loss amount estimation method, a loss amount estimation device, electronic equipment and a storage medium, wherein the method comprises the steps of obtaining topographic information and traffic flow information of alternative routes; acquiring weather information of an alternative route in a future period, and then establishing a simulation model in a simulation environment based on the terrain information, the traffic flow information and the weather information; configuring vehicle information in a simulation model to perform simulation so as to determine a first consumption amount of steel caused by collision friction and a second consumption amount of steel caused by corrosion, wherein the vehicle information comprises vehicle carrying space distribution information, a loading mode of the steel, the loading quantity of the steel and a wear coefficient of the steel, the simulation rate is greater than 1, and the simulation rate is a ratio of a time rate to a real time rate in a simulation environment; and determining the corresponding loss total amount of the steel based on the first loss amount and the second loss amount. The method and the device can determine the loss of the steel on the transportation route.
Description
Technical Field
The present disclosure relates to the field of logistics transportation technology, and in particular, to a wear amount estimating method, a wear amount estimating device, an electronic device, and a storage medium.
Background
Several alternative routes for the transportation of the steel are typically made before the transportation, and then appropriate choices are made based on the transportation speed of each route to determine the final destination route for transporting the steel to the destination within a specified transportation cycle.
However, the steel is worn out during transportation due to friction and collision, corrosion and rust, etc., and is generally prioritized based on the transportation speed when selecting the target route, and the wear of the steel on different transportation routes is ignored. Thus, how to determine the amount of wear in the transportation of steel in order to better determine the target route is a problem that needs to be solved.
Disclosure of Invention
In order to determine the wear on a transportation route of steel, the application provides a wear amount estimating method, a wear amount estimating device, electronic equipment and a storage medium.
In a first aspect, the present application provides a wear-leveling method, which adopts the following technical scheme:
a wear-leveling method, comprising:
obtaining topography information and traffic flow information of alternative routes;
acquiring weather information of an alternative route in a future period, wherein the future period is the same as the duration of a steel transportation period;
Establishing a simulation model in a simulation environment based on the terrain information, the traffic flow information and the weather information;
configuring vehicle information in a simulation model to perform simulation so as to determine a first consumption amount of steel caused by collision friction and a second consumption amount of steel caused by corrosion, wherein the vehicle information comprises vehicle carrying space distribution information, a loading mode of the steel, the loading quantity of the steel and a wear coefficient of the steel, the simulation rate is greater than 1, and the simulation rate is a ratio of a time rate to a real time rate in a simulation environment;
and determining the total loss amount corresponding to the steel based on the first loss amount and the second loss amount.
By adopting the technical scheme, the terrain information, traffic flow information and weather information of alternative routes are comprehensively considered to simulate factors influencing steel consumption, and meanwhile, vehicle information is combined, so that collision, friction and corrosion in the transportation process are conveniently simulated based on the vehicle carrying space distribution information, the loading mode, the loading quantity and the abrasion coefficient of the steel; by establishing a model in a simulation environment and simulating, the real transportation process can be simulated, so that the consumption of steel can be predicted more accurately; meanwhile, as the simulation rate is larger than 1, namely the time flow rate in the simulation environment is faster than the real time, a large amount of simulation can be completed in a short time, and the prediction efficiency is improved.
In one possible implementation, the alternative route includes a plurality of sub-segments, and the building a simulation model in a simulation environment based on the terrain information, the traffic flow information, and the weather information includes:
establishing a terrain model corresponding to each sub-road section based on the terrain information, wherein the terrain information comprises various terrain types corresponding to each sub-road section and terrain parameters corresponding to the various terrain types;
establishing a weather model corresponding to each sub-road section based on the weather information, wherein the weather information comprises a corresponding relation curve of weather parameters and time of each sub-road section, and the weather parameters comprise weather types, temperature and humidity;
establishing an interference vehicle model corresponding to each sub-road section based on a daily average flow curve corresponding to the sub-road section and the topographic information, wherein the traffic flow information comprises a daily average flow curve corresponding to each sub-road section, and the daily average flow curve comprises the average flow of the sub-road section in each unit period in a natural day;
and establishing a simulation model based on the terrain model, the weather model and the disturbance vehicle model corresponding to each sub-road section in the simulation environment.
In one possible implementation manner, the establishing an interference vehicle model corresponding to each sub-road section based on the daily average flow curve corresponding to the sub-road section and the terrain information includes:
Establishing an interference vehicle quantity generator based on a daily average flow curve corresponding to the sub-road section;
establishing an interfering vehicle dispenser based on the terrain type of the sub-section;
establishing an interference vehicle model of each sub-road section based on the interference vehicle number generator and the interference vehicle distributor so as to establish an interference vehicle model corresponding to each sub-road section;
the disturbance vehicle quantity generator determines the disturbance vehicle quantity based on the sampling frequency of the sub-road section, and the disturbance vehicle distributor determines the distribution density of the disturbance vehicles corresponding to each terrain type in the sub-road section based on the disturbance vehicle quantity.
In one possible implementation, determining a weather type for a transport vehicle passing through any sub-section includes:
determining the total duration of all the passed sub-road sections of the transport vehicle, and determining the arrival time corresponding to the arrival of the transport vehicle at any sub-road section based on the starting time of the transport vehicle;
and sampling the weather model of any sub-road section based on the sampling frequency of any sub-road section and the arrival time corresponding to the arrival of the transport vehicle at any sub-road section so as to determine weather parameters of the transport vehicle passing through any sub-road section.
In one possible implementation manner, the configuring the vehicle information in the simulation model to perform simulation to determine a first loss amount of the steel material due to collision friction and a second loss amount of the steel material due to corrosion includes:
Acquiring a mechanical collision model of a transport vehicle, and constructing an initial model of the transport vehicle of the vehicle in the mechanical collision model based on the vehicle information;
acquiring characteristic information of steel, wherein the characteristic information comprises corrosion speed curves of the steel at different temperatures and different humidities;
determining an exposed area of the steel based on the vehicle information;
adding the characteristic information and the exposed area of the steel material to the initial model to obtain a vehicle model
The vehicle model is configured in the simulation model to determine a first amount of wear due to collision friction and a second amount of wear due to corrosion of the steel.
In one possible implementation, the configuring the vehicle model in the simulation model includes:
the vehicle model is configured to simulate based on a simulation rate of the sub-road segment;
the simulation rate of the sub-road segment is determined based on the road class of the sub-road segment, and the simulation rate of the sub-road segment is configured to be in positive correlation with the sampling frequency of the sub-road segment, the road class of the sub-road segment characterizing the terrain complexity of the sub-road segment.
In a second aspect, the present application provides a wear-leveling estimation apparatus, which adopts the following technical scheme:
A wear-leveling estimation apparatus, comprising:
the first acquisition module is used for acquiring the topographic information and the traffic flow information of the alternative route;
the second acquisition module is used for acquiring weather information of the alternative route in a future period, wherein the duration of the future period is the same as that of a steel transportation period;
the simulation model building module is used for building a simulation model based on the terrain information, the traffic flow information and the weather information in a simulation environment;
the simulation module is used for configuring vehicle information in a simulation model to perform simulation so as to determine first consumption of steel materials caused by collision friction and second consumption of steel materials caused by corrosion, wherein the vehicle information comprises vehicle carrying space distribution information, loading modes of the steel materials, loading quantity of the steel materials and wear coefficients of the steel materials, the simulation rate is greater than 1, and the simulation rate is the ratio of time rate to real time rate in a simulation environment;
and the loss total amount determining module is used for determining the loss total amount corresponding to the steel based on the first loss amount and the second loss amount.
By adopting the technical scheme, the terrain information, traffic flow information and weather information of alternative routes are comprehensively considered to simulate factors influencing steel consumption, and meanwhile, vehicle information is combined, so that collision, friction and corrosion in the transportation process are conveniently simulated based on the vehicle carrying space distribution information, the loading mode, the loading quantity and the abrasion coefficient of the steel; by establishing a model in a simulation environment and simulating, the real transportation process can be simulated, so that the consumption of steel can be predicted more accurately; meanwhile, as the simulation rate is larger than 1, namely the time flow rate in the simulation environment is faster than the real time, a large amount of simulation can be completed in a short time, and the prediction efficiency is improved.
In one possible implementation manner, the alternative route includes a plurality of sub-segments, and the simulation model building module is specifically configured to, when building a simulation model in a simulation environment based on the terrain information, the traffic flow information, and the weather information:
establishing a terrain model corresponding to each sub-road section based on the terrain information, wherein the terrain information comprises various terrain types corresponding to each sub-road section and terrain parameters corresponding to the various terrain types;
establishing a weather model corresponding to each sub-road section based on the weather information, wherein the weather information comprises a corresponding relation curve of weather parameters and time of each sub-road section, and the weather parameters comprise weather types, temperature and humidity;
establishing an interference vehicle model corresponding to each sub-road section based on a daily average flow curve corresponding to the sub-road section and the topographic information, wherein the traffic flow information comprises a daily average flow curve corresponding to each sub-road section, and the daily average flow curve comprises the average flow of the sub-road section in each unit period in a natural day;
and establishing a simulation model based on the terrain model, the weather model and the disturbance vehicle model corresponding to each sub-road section in the simulation environment.
In one possible implementation manner, when the simulation model building module builds the interference vehicle model corresponding to each sub-road section based on the daily average flow curve corresponding to the sub-road section and the terrain information, the simulation model building module is specifically configured to:
establishing an interference vehicle quantity generator based on a daily average flow curve corresponding to the sub-road section;
establishing an interfering vehicle dispenser based on the terrain type of the sub-section;
establishing an interference vehicle model of each sub-road section based on the interference vehicle number generator and the interference vehicle distributor so as to establish an interference vehicle model corresponding to each sub-road section;
the disturbance vehicle quantity generator determines the disturbance vehicle quantity based on the sampling frequency of the sub-road section, and the disturbance vehicle distributor determines the distribution density of the disturbance vehicles corresponding to each terrain type in the sub-road section based on the disturbance vehicle quantity.
In one possible implementation, the simulation module, when determining the weather type of the transport vehicle passing through any sub-section, is specifically configured to:
determining the total duration of all the passed sub-road sections of the transport vehicle, and determining the arrival time corresponding to the arrival of the transport vehicle at any sub-road section based on the starting time of the transport vehicle;
and sampling the weather model of any sub-road section based on the sampling frequency of any sub-road section and the arrival time corresponding to the arrival of the transport vehicle at any sub-road section so as to determine weather parameters of the transport vehicle passing through any sub-road section.
In one possible implementation manner, the simulation module configures vehicle information in the simulation model to perform simulation, so as to determine a first loss amount of steel material due to collision friction and a second loss amount of steel material due to corrosion, and is specifically configured to:
acquiring a mechanical collision model of a transport vehicle, and constructing an initial model of the transport vehicle of the vehicle in the mechanical collision model based on the vehicle information;
acquiring characteristic information of steel, wherein the characteristic information comprises corrosion speed curves of the steel at different temperatures and different humidities;
determining an exposed area of the steel based on the vehicle information;
adding the characteristic information and the exposed area of the steel material to the initial model to obtain a vehicle model
The vehicle model is configured in the simulation model to determine a first amount of wear due to collision friction and a second amount of wear due to corrosion of the steel.
In one possible implementation, the simulation module is specifically configured to, when configuring the vehicle model in the simulation model:
the vehicle model is configured to simulate based on a simulation rate of the sub-road segment;
the simulation rate of the sub-road segment is determined based on the road class of the sub-road segment, and the simulation rate of the sub-road segment is configured to be in positive correlation with the sampling frequency of the sub-road segment, the road class of the sub-road segment characterizing the terrain complexity of the sub-road segment.
In a third aspect, the present application provides an electronic device, which adopts the following technical scheme:
an electronic device, the electronic device comprising:
at least one processor;
a memory;
at least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application configured to: executing the wear amount estimation method.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
a computer-readable storage medium, comprising: a computer program is stored that can be loaded by a processor and that performs the wear-leveling method described above.
In summary, the present application includes at least one of the following beneficial technical effects:
comprehensively considering the topographic information, traffic flow information and weather information of alternative routes to simulate factors influencing steel consumption, and combining the vehicle information, based on the vehicle carrying space distribution information, the loading mode, the loading quantity and the wear coefficient of the steel, so as to simulate the occurrence of collision, friction and corrosion in the transportation process; by establishing a model in a simulation environment and simulating, the real transportation process can be simulated, so that the consumption of steel can be predicted more accurately; meanwhile, as the simulation rate is larger than 1, namely the time flow rate in the simulation environment is faster than the real time, a large amount of simulation can be completed in a short time, and the prediction efficiency is improved.
Drawings
FIG. 1 is a flow chart of a wear-leveling method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of constructing a simulation model in an embodiment of the present application;
FIG. 3 is a schematic diagram of a wear-leveling device according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
The present application is described in further detail below in conjunction with fig. 1-4.
Modifications of the embodiments which do not creatively contribute to the invention may be made by those skilled in the art after reading the present specification, but are protected by patent laws only within the scope of claims of the present application.
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
The embodiment of the application provides a wear-leveling estimation method, which is executed by electronic equipment, wherein the electronic equipment comprises, but is not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), car terminals (e.g., car navigation terminals), and stationary terminals such as digital TVs, desktop computers, and the like, and servers and the like.
Referring to fig. 1, the method includes steps S11 to S15, wherein:
step S11, obtaining topographic information and traffic flow information of alternative routes;
and step S12, obtaining weather information of the alternative route in a future period, wherein the future period is the same as the duration of the steel transportation period.
The method steps in the embodiments of the present application may be performed for estimating the consumption amount of one alternative route, or may be performed for estimating the consumption amounts corresponding to each of a plurality of alternative routes, which in the embodiments of the present application are only illustrated by estimating the consumption amount of one alternative route. The alternative route is divided into a plurality of sub-road segments in advance, and the sub-road segments may be divided based on regions or may be divided based on continuous road types, which is not specifically limited in the embodiment of the present application.
Specifically, the terrain information comprises various terrain types corresponding to each sub-road section and terrain parameters corresponding to the various terrain types, the terrain information can be obtained through digital map analysis, for example, the terrain information of alternative routes is obtained through public digital map models of map and Google Maps through elevation information and terrain labeling of roads. The traffic flow information comprises a daily average flow curve corresponding to each sub-road section, wherein the daily average flow curve comprises the average flow of the sub-road sections in each unit period in a natural day; the unit period may be 1 hour or half an hour, which is not specifically limited in the embodiments of the present application. Traffic flow information may be obtained at public websites of traffic authorities. The weather information comprises a corresponding relation curve of weather parameters and time of each sub-road section, and the weather parameters comprise weather types, temperature and humidity.
Step S13, establishing a simulation model in a simulation environment based on the terrain information, the traffic flow information and the weather information;
s14, configuring vehicle information in a simulation model to carry out simulation so as to determine a first consumption amount of steel caused by collision friction and a second consumption amount of steel caused by corrosion, wherein the vehicle information comprises vehicle carrying space distribution information, a loading mode of the steel, the loading quantity of the steel and a wear coefficient of the steel, the simulation rate is greater than 1, and the simulation rate is a ratio of a time rate to a real time rate in a simulation environment;
And S15, determining the total loss amount corresponding to the steel based on the first loss amount and the second loss amount.
Specifically, when the simulation model is built, for each sub-road section, a model corresponding to the sub-road section is built based on the terrain information, the traffic flow information and the weather information corresponding to the sub-road section, so that the models corresponding to the sub-road sections are obtained, and the models corresponding to the sub-road sections are fused to obtain the simulation model. The distribution information of the vehicle carrying space in the vehicle information can be determined based on the three-dimensional model of the vehicle and the proportion of the model to reality, the three-dimensional data of the vehicle is obtained to establish the model of the vehicle, and steel materials and the quantity of the steel materials are distributed in the carrying space of the vehicle according to the actual transportation mode; the wear coefficient of the steel is determined based on the material properties of the steel, which need to be entered by a user.
Specifically, the total loss is the sum of the first loss and the second loss.
In the embodiment of the application, the terrain information, traffic flow information and weather information of alternative routes are comprehensively considered to simulate factors influencing steel consumption, and meanwhile, vehicle information is combined, so that collision, friction and corrosion in the transportation process are conveniently simulated based on vehicle carrying space distribution information, loading modes, loading quantity and wear coefficients of steel; by establishing a model in a simulation environment and simulating, the real transportation process can be simulated, so that the consumption of steel can be predicted more accurately; meanwhile, as the simulation rate is larger than 1, namely the time flow rate in the simulation environment is faster than the real time, a large amount of simulation can be completed in a short time, and the prediction efficiency is improved.
Further, referring to fig. 2, a simulation model is built in the simulation environment based on the terrain information, the traffic flow information, and the weather information, and specifically may include step S131 (not shown in the figure) -step S134 (not shown in the figure), where:
step S131, building a terrain model corresponding to each sub-road section based on terrain information, wherein the terrain information comprises various terrain types corresponding to each sub-road section and terrain parameters corresponding to the various terrain types.
Specifically, the terrain types at least comprise curves, uphill slopes, downhill slopes and other terrains, and can also comprise highways, province and county roads, national roads and other roads; the terrain parameters for each terrain type include at least length, road surface flatness, and maximum slope, slope direction distribution. Because the topographic information is collected based on the disclosed digital map, the topographic model corresponding to the sub-link can be directly extracted from the digital map as the topographic model of the sub-link.
Step S132, a weather model corresponding to each sub-road section is built based on weather information, wherein the weather information comprises a corresponding relation curve of weather parameters and time of each sub-road section, and the weather parameters comprise weather type, temperature and humidity.
Specifically, the input of the weather model is sampling time, and the output of the weather model is weather parameter determined based on the sampling time and a corresponding relation curve of the weather parameter and time.
Specifically, determining weather parameters of the vehicle model of the transport vehicle passing through any sub-road segment may specifically include: determining the total duration of all the passed sub-road sections of the transport vehicle, and determining the arrival time corresponding to the arrival of the transport vehicle at any sub-road section based on the starting time of the transport vehicle;
and sampling the weather model of any sub-road section based on the sampling frequency of any sub-road section and the arrival time corresponding to the arrival of the transport vehicle at any sub-road section so as to determine weather parameters of the transport vehicle passing through any sub-road section.
And step S133, establishing an interference vehicle model corresponding to each sub-road section based on traffic flow information and terrain information, wherein the traffic flow information comprises the average flow of each sub-road section in a history period.
Specifically, for one sub-section: and establishing an interference vehicle number generator based on the daily average flow curve corresponding to the sub-road section, establishing an interference vehicle distributor based on the terrain type of the sub-road section, and then establishing an interference vehicle model of the sub-road section based on the interference vehicle number generator and the interference vehicle distributor so as to establish an interference vehicle model corresponding to each sub-road section.
Specifically, the disturbance vehicle quantity generator determines the disturbance vehicle quantity based on the sampling frequency of the sub-road section, the disturbance vehicle distributor determines the distribution density of the disturbance vehicles corresponding to each terrain type in the sub-road section based on the disturbance vehicle quantity, and then the disturbance vehicles are arranged based on the distribution density of the disturbance vehicles corresponding to each terrain type; further, an interfering vehicle model corresponding to each sub-road section is established.
Specifically, the interfering vehicles in each terrain type are configured such that the following distance complies with preset driving rules, for example, the following distance is not more than 50m, and the interfering vehicles do not exceed the highest speed per hour defined by the terrain type in each terrain type. The driving rules can be acquired based on road traffic rules of sub-road sections and can be input by a user.
In particular, the distribution density characterizes the number of disturbing vehicles in the road corresponding to the terrain, in fact, since in some terrain types with greater difficulty of passing, the speed-limiting passing of the passing vehicles is required, the distribution density corresponding to the terrain type with greater difficulty of passing is greater. That is, the difficulty of traffic of a terrain type is positively correlated with the distribution density of interfering vehicles in the terrain type in the same sub-section.
More specifically, in one sub-road section, the traffic difficulty of each terrain type is determined based on the terrain parameter of each terrain type, and then the proportion of the disturbance vehicle type in each terrain type to the average traffic flow of the sub-road section is determined based on the traffic difficulty of each terrain type, and then the distribution density of the disturbance vehicles corresponding to each terrain type in each sub-road section is determined.
And step S134, establishing a simulation model based on the terrain model, the weather model and the disturbance vehicle model corresponding to each sub-road section in the simulation environment.
In particular, the simulation environment may employ any one of a Finite Element Analysis (FEA) model, a multi-body dynamics (MBD) model, and a vehicle dynamics model. And adding a corresponding terrain model and an interference vehicle model in the simulation environment, wherein the terrain model is a fixed parameter setting and does not change in the simulation process. The disturbance vehicle in the disturbance model is configured to travel along the path of the sub-road section, and when the disturbance vehicle reaches the end point of the sub-road section, the disturbance vehicle reaching the end point is deleted and regenerated at the start point of the sub-road section.
The weather model is based on a relation curve of weather parameters and time of a corresponding sub-road section as a function, the input result is sampling time in a simulation environment as an independent variable, the output result is the weather parameters obtained by sampling the sub-road section, and the real-time in the simulation environment and the real-time corresponding to the function curve are converted based on simulation rate and then correspond to each other.
Further, the vehicle information is configured in the simulation model to perform simulation, and specifically, the method may include a step of building a vehicle model and a step of configuring the vehicle model.
The step of building a vehicle model may specifically include: acquiring a mechanical collision model of the transport vehicle, and constructing an initial model of the transport vehicle of the vehicle in the mechanical collision model based on vehicle information; acquiring characteristic information of the steel, wherein the characteristic information comprises corrosion speed curves of the steel at different temperatures and different humidities, and determining the exposed area of the steel based on vehicle information; and then adding the characteristic information and the exposed area of the steel material into the initial model to obtain the vehicle model. The vehicle model is configured to adjust a driving state including a driving speed, a braking and an accelerating action based on an output of weather parameters of a sub-section on which the vehicle model is located. Meanwhile, the vehicle model is also configured to conform to the driving rules of the corresponding sub-road sections with the interfering vehicle.
Specifically, a mechanical collision model is determined based on a simulation environment, and a Finite Element Analysis (FEA) model can simulate stress and strain distribution due to vibration, jolt, emergency braking, and the like during transportation by discretizing the geometric shapes of vehicles and steels into a limited number of elements. If a Finite Element Analysis (FEA) model is used as the simulation environment, the model itself is a collision model without the need for additional building of the collision model. If other simulation environments are adopted, a boundary box collision detection (Bounding Box Collision Detection) model can be adopted as the mechanical collision model, and as each object in the boundary box collision detection model is surrounded by a rectangle (in 2D) or a cube (in 3D), whether the object is likely to collide can be rapidly determined by comparing whether the boundary boxes are intersected or not, and the corresponding cube environment is more in accordance with the shape and loading mode of steel materials, so that more accurate simulation results are conveniently obtained.
Specifically, a three-dimensional model of the transport vehicle is built based on vehicle information and configured in the three-dimensional model of the vehicle based on the loading manner of the steel material and the loading amount of the steel material, and the exposed area is obtained by identifying the surface area of the steel material by a detection edge algorithm.
The configuring step of the model specifically may include: the vehicle model is configured to simulate based on the simulation rate of the sub-road segment; the simulation rate of the sub-road segments is determined based on the road class of the sub-road segments, and the simulation rate of the sub-road segments is configured to be in positive correlation with the sampling frequency of the sub-road segments, and the simulation rate of each sub-road segment is greater than 1.
Specifically, the road level of the sub-link characterizes the terrain complexity of the sub-link, and the road level of the sub-link can be preset. The different topography grades of the sub-sections, the slower the simulation rate corresponding to the sub-sections, and further, the lower the sampling frequency of the sub-sections.
For example, for the a road segment and the B road segment, the terrain types of the a road segment are numerous and complex, and thus, the terrain level of the a road segment is higher than that of the B road segment, the simulation rate corresponding to the a road segment may be 7, and the anti-shake rate corresponding to the B road segment may be 10. That is, in the simulation environment, the vehicle model travels for 1 minute in the a segment corresponding to 7 minutes in reality, and the vehicle model travels for 1 minute in the B segment corresponding to 10 minutes in reality. Meanwhile, in the a section, weather parameters and average traffic flow may be acquired every 1 minute, and in the B section, weather parameters and average traffic flow may be acquired every 3 minutes.
In the simulation process, the lower the simulation rate is, the lower the sampling frequency is, and more accurate simulation results are easier to obtain. Further, if two different weather types are acquired in the same sub-section of the vehicle, the sampling frequency and the simulation rate of the sub-section are changed in real time to simulate so as to acquire more accurate results.
The foregoing embodiments describe a wear-leveling method from the perspective of a method flow, and the following embodiments describe a wear-leveling device from the perspective of a virtual module or a virtual unit, which is described in detail in the following embodiments.
An embodiment of the present application provides a wear-leveling device, as shown in fig. 3, which specifically may include a first obtaining module 301, a second obtaining module 302, a simulation model building module 303, a simulation module 304, and a wear-leveling module 305, where:
a first obtaining module 301, configured to obtain topographic information and traffic flow information of an alternative route;
a second obtaining module 302, configured to obtain weather information of the alternative route in a future period, where the future period is the same as a duration of a transportation period of the steel;
a simulation model building module 303, configured to build a simulation model in a simulation environment based on the terrain information, the traffic flow information, and the weather information;
The simulation module 304 is configured to perform simulation by configuring vehicle information in a simulation model to determine a first consumption amount of steel caused by collision friction and a second consumption amount of steel caused by corrosion, where the vehicle information includes vehicle carrying space distribution information, a loading mode of the steel, a loading quantity of the steel, and a wear coefficient of the steel, and a simulation rate is greater than 1, where the simulation rate is a ratio of a time rate to a real time rate in a simulation environment;
the wear amount determining module 305 is configured to determine a wear amount corresponding to the steel based on the first wear amount and the second wear amount.
In one possible implementation, the alternative route includes a plurality of sub-segments, and the simulation model building module 303 is specifically configured to, when building a simulation model in a simulation environment based on the terrain information, the traffic flow information, and the weather information:
establishing a terrain model corresponding to each sub-road section based on terrain information, wherein the terrain information comprises various terrain types corresponding to each sub-road section and terrain parameters corresponding to the various terrain types;
establishing a weather model corresponding to each sub-road section based on weather information, wherein the weather information comprises a corresponding relation curve of weather parameters and time of each sub-road section, and the weather parameters comprise weather types, temperature and humidity;
Establishing an interference vehicle model corresponding to each sub-road section based on a daily average flow curve corresponding to the sub-road section and terrain information, wherein the traffic flow information comprises a daily average flow curve corresponding to each sub-road section, and the daily average flow curve comprises the average flow of the sub-road section in each unit period in a natural day;
and establishing a simulation model based on the terrain model, the weather model and the disturbance vehicle model corresponding to each sub-road section in the simulation environment.
In one possible implementation manner, the simulation model building module 303 builds an interference vehicle model corresponding to each sub-road section based on the daily average flow curve and the terrain information corresponding to the sub-road section, which is specifically configured to:
establishing an interference vehicle quantity generator based on a daily average flow curve corresponding to the sub-road section;
establishing an interfering vehicle distributor based on the topography type of the sub-road section;
establishing an interference vehicle model of each sub-road section based on the interference vehicle number generator and the interference vehicle distributor so as to establish an interference vehicle model corresponding to each sub-road section;
the disturbance vehicle quantity generator determines the disturbance vehicle quantity based on the sampling frequency of the sub-road section, and the disturbance vehicle distributor determines the distribution density of the disturbance vehicles corresponding to each terrain type in the sub-road section based on the disturbance vehicle quantity.
In one possible implementation, the simulation module 304 is specifically configured to, when determining the weather type for the transport vehicle passing through any of the sub-segments:
determining the total duration of all the passed sub-road sections of the transport vehicle, and determining the arrival time corresponding to the arrival of the transport vehicle at any sub-road section based on the starting time of the transport vehicle;
and sampling the weather model of any sub-road section based on the sampling frequency of any sub-road section and the arrival time corresponding to the arrival of the transport vehicle at any sub-road section so as to determine weather parameters of the transport vehicle passing through any sub-road section.
In one possible implementation, the simulation module 304 configures the vehicle information in a simulation model to perform a simulation to determine a first amount of wear due to collision friction and a second amount of wear due to corrosion on the steel, specifically for:
acquiring a mechanical collision model of the transport vehicle, and constructing an initial model of the transport vehicle of the vehicle in the mechanical collision model based on vehicle information;
acquiring characteristic information of steel, wherein the characteristic information comprises corrosion speed curves of the steel at different temperatures and different humidities;
determining an exposed area of the steel based on the vehicle information;
adding characteristic information and exposed area of steel material in initial model to obtain vehicle model
A vehicle model is configured in the simulation model to determine a first amount of wear due to collision friction and a second amount of wear due to corrosion of the steel.
In one possible implementation, the simulation module 304 is specifically configured to, when configuring the vehicle model in the simulation model:
the vehicle model is configured to simulate based on the simulation rate of the sub-road segment;
the simulation rate of the sub-road segment is determined based on the road class of the sub-road segment, and the simulation rate of the sub-road segment is configured to be in positive correlation with the sampling frequency of the sub-road segment, the road class of the sub-road segment characterizing the terrain complexity of the sub-road segment.
In an embodiment of the present application, as shown in fig. 4, an electronic device 400 shown in fig. 4 includes: a processor 401 and a memory 403. Processor 401 is connected to memory 403, such as via bus 402. Optionally, the electronic device 400 may also include a transceiver 404. It should be noted that, in practical applications, the transceiver 404 is not limited to one, and the structure of the electronic device 400 is not limited to the embodiment of the present application.
The processor 401 may be a CPU (Central Processing Unit ), general purpose processor, DSP (Digital Signal Processor, data signal processor), ASIC (Application Specific Integrated Circuit ), FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic device, transistor logic device, hardware components, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules, and circuits described in connection with this disclosure. Processor 401 may also be a combination that implements computing functionality, such as a combination comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.
Bus 402 may include a path to transfer information between the components. Bus 402 may be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or EISA (Extended Industry Standard Architecture ) bus, among others. Bus 402 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in fig. 4, but not only one bus or one type of bus.
The Memory 403 may be, but is not limited to, a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory ) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory ), a CD-ROM (Compact Disc Read Only Memory, compact disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 403 is used for storing application program codes for executing the present application and is controlled to be executed by the processor 401. The processor 401 is arranged to execute application code stored in the memory 403 for implementing what is shown in the foregoing method embodiments.
Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. But may also be a server or the like. The electronic device shown in fig. 4 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.
The present application provides a computer readable storage medium having a computer program stored thereon, which when run on a computer, causes the computer to perform the corresponding method embodiments described above.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
The foregoing is only a partial embodiment of the present application and it should be noted that, for a person skilled in the art, several improvements and modifications can be made without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (9)
1. A wear-leveling method, comprising:
obtaining topography information and traffic flow information of alternative routes;
acquiring weather information of an alternative route in a future period, wherein the future period is the same as the duration of a steel transportation period;
establishing a simulation model in a simulation environment based on the terrain information, the traffic flow information and the weather information;
configuring vehicle information in a simulation model to perform simulation so as to determine a first consumption amount of steel caused by collision friction and a second consumption amount of steel caused by corrosion, wherein the vehicle information comprises vehicle carrying space distribution information, a loading mode of the steel, the loading quantity of the steel and a wear coefficient of the steel, the simulation rate is greater than 1, and the simulation rate is a ratio of a time rate to a real time rate in a simulation environment;
and determining the total loss amount corresponding to the steel based on the first loss amount and the second loss amount.
2. The method of estimating a wear level according to claim 1, wherein the alternative route includes a plurality of sub-segments, and the establishing a simulation model in a simulation environment based on the terrain information, the traffic flow information, and the weather information includes:
establishing a terrain model corresponding to each sub-road section based on the terrain information, wherein the terrain information comprises various terrain types corresponding to each sub-road section and terrain parameters corresponding to the various terrain types;
establishing a weather model corresponding to each sub-road section based on the weather information, wherein the weather information comprises a corresponding relation curve of weather parameters and time of each sub-road section, and the weather parameters comprise weather types, temperature and humidity;
establishing an interference vehicle model corresponding to each sub-road section based on a daily average flow curve corresponding to the sub-road section and the topographic information, wherein the traffic flow information comprises a daily average flow curve corresponding to each sub-road section, and the daily average flow curve comprises the average flow of the sub-road section in each unit period in a natural day;
and establishing a simulation model based on the terrain model, the weather model and the disturbance vehicle model corresponding to each sub-road section in the simulation environment.
3. The consumption estimating method according to claim 2, wherein the establishing an interfering vehicle model corresponding to each sub-road section based on the daily average flow curve corresponding to the sub-road section and the topographic information includes:
establishing an interference vehicle quantity generator based on a daily average flow curve corresponding to the sub-road section;
establishing an interfering vehicle dispenser based on the terrain type of the sub-section;
establishing an interference vehicle model of each sub-road section based on the interference vehicle number generator and the interference vehicle distributor so as to establish an interference vehicle model corresponding to each sub-road section;
the disturbance vehicle quantity generator determines the disturbance vehicle quantity based on the sampling frequency of the sub-road section, and the disturbance vehicle distributor determines the distribution density of the disturbance vehicles corresponding to each terrain type in the sub-road section based on the disturbance vehicle quantity.
4. The method of claim 2, wherein determining weather parameters for the transport vehicle passing through any sub-section comprises:
determining the total duration of all the passed sub-road sections of the transport vehicle, and determining the arrival time corresponding to the arrival of the transport vehicle at any sub-road section based on the starting time of the transport vehicle;
And sampling the weather model of any sub-road section based on the sampling frequency of any sub-road section and the arrival time corresponding to the arrival of the transport vehicle at any sub-road section so as to determine weather parameters of the transport vehicle passing through any sub-road section.
5. The method of estimating a wear level according to any one of claims 1 to 4, wherein said configuring the vehicle information in the simulation model to perform the simulation to determine the first wear level due to collision friction and the second wear level due to rust of the steel comprises:
acquiring a mechanical collision model of a transport vehicle, and constructing an initial model of the transport vehicle of the vehicle in the mechanical collision model based on the vehicle information;
acquiring characteristic information of steel, wherein the characteristic information comprises corrosion speed curves of the steel at different temperatures and different humidities;
determining an exposed area of the steel based on the vehicle information;
adding the characteristic information and the exposed area of the steel material to the initial model to obtain a vehicle model
The vehicle model is configured in the simulation model to determine a first amount of wear due to collision friction and a second amount of wear due to corrosion of the steel.
6. The method of estimating wear level according to claim 5, wherein said configuring said vehicle model in said simulation model comprises:
the vehicle model is configured to simulate based on a simulation rate of the sub-road segment;
the simulation rate of the sub-road segment is determined based on the road class of the sub-road segment, and the simulation rate of the sub-road segment is configured to be in positive correlation with the sampling frequency of the sub-road segment, the road class of the sub-road segment characterizing the terrain complexity of the sub-road segment.
7. A wear-leveling device, comprising:
the first acquisition module is used for acquiring the topographic information and the traffic flow information of the alternative route;
the second acquisition module is used for acquiring weather information of the alternative route in a future period, wherein the duration of the future period is the same as that of a steel transportation period;
the simulation model building module is used for building a simulation model based on the terrain information, the traffic flow information and the weather information in a simulation environment;
the simulation module is used for configuring vehicle information in a simulation model to perform simulation so as to determine first consumption of steel materials caused by collision friction and second consumption of steel materials caused by corrosion, wherein the vehicle information comprises vehicle carrying space distribution information, loading modes of the steel materials, loading quantity of the steel materials and wear coefficients of the steel materials, the simulation rate is greater than 1, and the simulation rate is the ratio of time rate to real time rate in a simulation environment;
And the loss total amount determining module is used for determining the loss total amount corresponding to the steel based on the first loss amount and the second loss amount.
8. An electronic device, comprising:
at least one processor;
a memory;
at least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application configured to: performing the wear level estimation method according to any one of claims 1-6.
9. A computer-readable storage medium, comprising: computer program stored with a memory capable of being loaded by a processor and executing the wear-leveling method according to any one of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410130218.2A CN117688782B (en) | 2024-01-31 | 2024-01-31 | Wear amount estimation method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410130218.2A CN117688782B (en) | 2024-01-31 | 2024-01-31 | Wear amount estimation method and device, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117688782A CN117688782A (en) | 2024-03-12 |
| CN117688782B true CN117688782B (en) | 2024-04-12 |
Family
ID=90135600
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410130218.2A Active CN117688782B (en) | 2024-01-31 | 2024-01-31 | Wear amount estimation method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117688782B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108319785A (en) * | 2018-02-05 | 2018-07-24 | 三峡大学 | A kind of cable run steel bracket selection method based on evaluation of life cycle cost |
| CN110164128A (en) * | 2019-04-23 | 2019-08-23 | 银江股份有限公司 | A kind of City-level intelligent transportation analogue system |
| CN111241168A (en) * | 2020-01-15 | 2020-06-05 | 中设设计集团股份有限公司 | Real-time online microscopic traffic simulation method and system |
| CN112733337A (en) * | 2020-12-28 | 2021-04-30 | 华南理工大学 | Method for evaluating urban road traffic efficiency under influence of rainstorm and waterlogging |
| CN115206103A (en) * | 2022-07-18 | 2022-10-18 | 山西省智慧交通研究院有限公司 | Variable speed-limiting control system based on parallel simulation system |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9650042B2 (en) * | 2014-09-11 | 2017-05-16 | Cummins Inc. | Systems and methods for route planning |
| US20230304896A1 (en) * | 2022-03-22 | 2023-09-28 | Jilin University | Method for evaluating performance of self-driving vehicle oriented to full parameter space of logical scenario |
-
2024
- 2024-01-31 CN CN202410130218.2A patent/CN117688782B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108319785A (en) * | 2018-02-05 | 2018-07-24 | 三峡大学 | A kind of cable run steel bracket selection method based on evaluation of life cycle cost |
| CN110164128A (en) * | 2019-04-23 | 2019-08-23 | 银江股份有限公司 | A kind of City-level intelligent transportation analogue system |
| CN111241168A (en) * | 2020-01-15 | 2020-06-05 | 中设设计集团股份有限公司 | Real-time online microscopic traffic simulation method and system |
| CN112733337A (en) * | 2020-12-28 | 2021-04-30 | 华南理工大学 | Method for evaluating urban road traffic efficiency under influence of rainstorm and waterlogging |
| CN115206103A (en) * | 2022-07-18 | 2022-10-18 | 山西省智慧交通研究院有限公司 | Variable speed-limiting control system based on parallel simulation system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117688782A (en) | 2024-03-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Souza et al. | Asfault: A low-cost system to evaluate pavement conditions in real-time using smartphones and machine learning | |
| CN109901567B (en) | Method and apparatus for outputting obstacle information | |
| Delling et al. | Navigation made personal: Inferring driving preferences from gps traces | |
| US9643511B2 (en) | Method and apparatus for estimating state of charge (SOC) of battery in electric vehicle | |
| US8738336B2 (en) | Systems and methods for enhanced cellular automata algorithm for traffic flow modeling | |
| EP3951321A1 (en) | Method and system for rapid generation of reference driving route, terminal and storage medium | |
| CN103630142B (en) | Method and apparatus to determine energy-conservation route are processed map datum | |
| EP2530433A1 (en) | Method of generating a database for a navigation device, method of outputting a three-dimensional map, and navigation device | |
| US11474529B2 (en) | System and method for motion planning of an autonomous driving machine | |
| US20130041642A1 (en) | Traffic simulation system and traffic simulation program | |
| US20230341240A1 (en) | Method and processor circuit for updating a digital road map | |
| US10571290B2 (en) | Method and system for vehicle speed profile generation | |
| CN105387844B (en) | Pavement behavior measurement system and pavement behavior assay method | |
| Khoury et al. | Assessing the risk in the design of passing sight distances | |
| CN117688782B (en) | Wear amount estimation method and device, electronic equipment and storage medium | |
| CN110470310A (en) | Automatic map generates | |
| JP7347974B2 (en) | Estimation device, estimation method, and estimation program | |
| WO2023215507A1 (en) | System and method for simulating an environment for autonomous vehicle testing | |
| CN110648008A (en) | Road condition prediction method and device | |
| WO2023083552A1 (en) | Generating greenhouse gas emissions estimations associated with logistics contexts using machine learning techniques | |
| JP7294660B2 (en) | Route planning device, route planning method, and program | |
| JP7070531B2 (en) | Urban structure design equipment and urban structure design program | |
| CN112820111B (en) | Abnormal vehicle identification method and device and electronic equipment | |
| WO2021140614A1 (en) | Driving assistance device and driving assistance method | |
| CN116664370B (en) | Data processing method and device, computer equipment and storage medium |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |