An operation and maintenance method, system and medium for a comprehensive electric test vehicle management system

Abstract

The present invention relates to an operation and maintenance method, system, and medium for an integrated electric test vehicle management system, and belongs to the technical field of electric test vehicles. The present invention obtains historical service data information of the electric test vehicle, and constructs a fault prediction model based on the historical service data information of the electric test vehicle. The fault prediction model predicts the fault information of each electric test vehicle, and finally redistributes the work allocation results of the electric test vehicle based on the fault information of each electric test vehicle, obtains the operation and maintenance results of the electric test vehicle, and transmits the operation and maintenance results of the electric test vehicle to the electric test vehicle control terminal through the integrated electric test vehicle management system. The present invention fully considers the phenomenon of electromagnetic interference during the operation of the electric test vehicle, and thus distributes the work of the electric test vehicle through the integrated electric test vehicle management system according to the electromagnetic interference situation, making the work allocation of the electric test vehicle more reasonable.

Description

Technical Field

[0001] The present invention relates to the technical field of electric test vehicles, and in particular to an operation and maintenance method, system and medium of an integrated electric test vehicle management system. Background Art

[0002] The electric power test vehicle was designed and developed in accordance with the "DL / T596-1996 Preventive Test Procedure for Electric Power Equipment" and other equipment testing requirements for pre-commissioning and periodic preventive testing of power equipment in major substations across China. It is suitable for engineering acceptance testing and in-service preventive testing of high-voltage electrical equipment, such as substations, railway traction substations, and switchgear, installed and operating in the power, railway electrification, metallurgy, and coal mining industries. This test vehicle offers new insights and methods for equipment management, data management, data transmission, data security, report generation, field test operation, and control. All test equipment within the vehicle can be tested without moving it. This not only standardizes the management of test equipment, test processes, and data recording and analysis, but also significantly improves field testing efficiency, shortens test time, and reduces economic losses caused by power outages. This intelligent, intensive test vehicle utilizes digital monitoring and network communications, and is designed for centralized testing and emergency repairs in substations, power stations, and other power supply departments with specialized requirements. This test vehicle, for which multiple patents have been applied, has been widely used in the power industry because it can be configured in various configurations to meet user requirements and can complete most on-site power prevention tests. Furthermore, all required test equipment and devices are centrally located on the dedicated test vehicle, allowing for direct transportation to the test site and then back to the warehouse afterward, making it very convenient. However, current power test vehicles are susceptible to electromagnetic interference during testing, which can result in data being collected, potentially preventing it from being collected, or even incomplete data being collected. Summary of the Invention

[0003] The present invention overcomes the deficiencies of the prior art and provides an operation and maintenance method, system and medium for a comprehensive electric test vehicle management system.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is:

[0005] A first aspect of the present invention provides an operation and maintenance method for an integrated electric test vehicle management system, comprising the following steps:

[0006] Acquiring environmental data of the area to be repaired in the target area, and acquiring electromagnetic characteristic data of a position of the electric power test vehicle in the area to be repaired in the target area based on the environmental data of the area to be repaired in the target area;

[0007] Acquire electromagnetic anti-interference capability data of the electric test vehicle, and initialize a work assignment result of the electric test vehicle based on the electromagnetic characteristic data of the location of the electric test vehicle in the area to be repaired in the target area and the electromagnetic anti-interference capability data of the electric test vehicle;

[0008] Acquiring historical service data information of the electric test vehicle, and building a fault prediction model based on the historical service data information of the electric test vehicle, and predicting fault information of each electric test vehicle using the fault prediction model;

[0009] The work distribution results of the electric test vehicle are redistributed according to the fault information of each electric test vehicle, and the operation and maintenance results of the electric test vehicle are obtained. The operation and maintenance results of the electric test vehicle are transmitted to the electric test vehicle control terminal through the integrated electric test vehicle management system.

[0010] Furthermore, in this method, environmental data of the area to be repaired in the target area is obtained, and electromagnetic characteristic data of the area to be repaired in the target area is obtained based on the environmental data of the area to be repaired in the target area, specifically:

[0011] Obtain environmental data that affects electromagnetic signature data, and use big data to retrieve the attenuation ratio of electromagnetic data under different environmental data. Graph neural networks are introduced, with environmental data as the first graph node and the attenuation ratio as the second graph node.

[0012] Connecting the first graph node and the second graph node to construct a topology graph, performing matrix representation on the topology graph to obtain an adjacency matrix, constructing a database, inputting the adjacency matrix one by one into a storage space of the database, and configuring a query address;

[0013] Obtaining environmental data of the area to be repaired in the target area, inputting the environmental data of the area to be repaired in the target area into the database for data query, and obtaining an attenuation ratio of electromagnetic data under the environmental data of the area to be repaired in the target area;

[0014] Acquire electromagnetic data of the area to be repaired, the location of the electric test vehicle during maintenance, and the location of the area to be repaired through an electromagnetic sensor, and calculate a Euclidean distance value based on the location of the electric test vehicle during maintenance and the location of the area to be repaired;

[0015] The electromagnetic characteristic data of the position of the electric test vehicle in the target area to be repaired is calculated based on the Euclidean distance value, the attenuation ratio of the electromagnetic data under the environmental data of the area to be repaired in the target area, and the electromagnetic data of the area to be repaired.

[0016] Furthermore, in this method, the electromagnetic anti-interference capability data of the electric test vehicle is obtained, and the work allocation result of the electric test vehicle is initialized according to the electromagnetic characteristic data of the location of the electric test vehicle in the area to be repaired in the target area and the electromagnetic anti-interference capability data of the electric test vehicle, which specifically includes:

[0017] Obtaining electromagnetic anti-interference capability data of the electric test vehicles, randomly selecting a combination of electric test vehicles, and randomly assigning them to each area to be repaired, and obtaining electromagnetic characteristic data of the location where each electric test vehicle in the combination of electric test vehicles is located during maintenance;

[0018] Determining whether electromagnetic characteristic data of the location where each electric test vehicle in the combination of electric test vehicles is located during maintenance is less than electromagnetic anti-interference capability data of the electric test vehicle;

[0019] When the electromagnetic characteristic data of the location where each electric test vehicle in the combination of the electric test vehicles is located during maintenance is less than the electromagnetic anti-interference capability data of the electric test vehicle, the combination of the electric test vehicles is output, and work allocation is performed according to the combination of the electric test vehicles to generate a work allocation result for the electric test vehicles;

[0020] When the electromagnetic characteristic data of the location where each electric test vehicle in the combination of the electric test vehicles is located during maintenance is not all smaller than the electromagnetic anti-interference capability data of the electric test vehicle, the combination of the electric test vehicles is reallocated.

[0021] Furthermore, in this method, historical service data information of the electric test vehicle is obtained, and a fault prediction model is constructed based on the historical service data information of the electric test vehicle, specifically including:

[0022] Acquiring historical service data information of the electric test vehicle, constructing a training set based on the historical service data information of the electric test vehicle, constructing a fault prediction model based on a deep neural network, and inputting the training set into the fault prediction model for training;

[0023] After the loss function of the fault prediction model converges to a preset value, the model parameters of the fault prediction model are saved, the training of the fault prediction model is completed, and the fault prediction model is output.

[0024] Furthermore, in this method, the fault information of each electric test vehicle is predicted by the fault prediction model, specifically:

[0025] Acquiring service data information of the electric test vehicle within a preset time, and inputting the service data information of the electric test vehicle within the preset time into the fault prediction model to perform fault prediction;

[0026] The fault time and fault type of each electric test vehicle are obtained through prediction, and the fault information of each electric test vehicle is generated according to the fault time and fault type of each electric test vehicle.

[0027] Furthermore, in this method, the work allocation results of the electric test vehicles are redistributed according to the fault information of each electric test vehicle to obtain the operation and maintenance results of the electric test vehicle, which specifically includes:

[0028] Obtain the maintenance type of each maintenance area, and construct a search tag based on the maintenance type of the maintenance area. Search through big data based on the search tag to obtain the average maintenance time of each maintenance area;

[0029] Determine whether there is an electric test vehicle whose fault time in the fault information is equal to the average maintenance time in the maintenance area;

[0030] When there is an electric test vehicle whose fault time in the fault information is within the average maintenance time of the maintenance area, the work allocation result of the electric test vehicle is reallocated, and the operation and maintenance result of the electric test vehicle is calculated based on the reallocated work allocation result;

[0031] When there is no electric test vehicle whose fault time in the fault information is within the average maintenance time of the maintenance area, an operation and maintenance result of the electric test vehicle is generated based on the work allocation result of the electric test vehicle.

[0032] A second aspect of the present invention provides an operation and maintenance system for an integrated electric test vehicle management system. The system includes a memory and a processor. The memory includes an operation and maintenance method program for the integrated electric test vehicle management system. When the operation and maintenance method program for the integrated electric test vehicle management system is executed by the processor, the following steps are implemented:

[0033] Acquiring environmental data of the area to be repaired in the target area, and acquiring electromagnetic characteristic data of a position of the electric power test vehicle in the area to be repaired in the target area based on the environmental data of the area to be repaired in the target area;

[0034] Acquire electromagnetic anti-interference capability data of the electric test vehicle, and initialize a work assignment result of the electric test vehicle based on the electromagnetic characteristic data of the location of the electric test vehicle in the area to be repaired in the target area and the electromagnetic anti-interference capability data of the electric test vehicle;

[0035] Acquiring historical service data information of the electric test vehicle, and building a fault prediction model based on the historical service data information of the electric test vehicle, and predicting fault information of each electric test vehicle using the fault prediction model;

[0036] The work distribution results of the electric test vehicle are redistributed according to the fault information of each electric test vehicle, and the operation and maintenance results of the electric test vehicle are obtained. The operation and maintenance results of the electric test vehicle are transmitted to the electric test vehicle control terminal through the integrated electric test vehicle management system.

[0037] The third aspect of the present invention provides a computer-readable storage medium, which includes an operation and maintenance method program of an integrated electric test vehicle management system. When the operation and maintenance method program of the integrated electric test vehicle management system is executed by a processor, the steps of any one of the operation and maintenance methods of the integrated electric test vehicle management system are implemented.

[0038] The present invention solves the defects existing in the background technology and has the following beneficial effects:

[0039] The present invention obtains environmental data of the target area to be repaired, obtains electromagnetic characteristic data of the location of the electric test vehicle in the target area to be repaired based on the environmental data of the target area to be repaired, and then obtains the electromagnetic anti-interference capability data of the electric test vehicle. The electromagnetic characteristic data of the location of the electric test vehicle in the target area to be repaired and the electromagnetic anti-interference capability data of the electric test vehicle are initialized according to the electromagnetic characteristic data of the location of the electric test vehicle in the target area to be repaired and the electromagnetic anti-interference capability data of the electric test vehicle, thereby obtaining historical service data information of the electric test vehicle, and constructing a fault prediction model based on the historical service data information of the electric test vehicle. The fault prediction model predicts the fault information of each electric test vehicle, and finally redistributes the work allocation results of the electric test vehicle according to the fault information of each electric test vehicle, obtains the operation and maintenance results of the electric test vehicle, and transmits the operation and maintenance results of the electric test vehicle to the electric test vehicle control terminal through the integrated electric test vehicle management system based on the operation and maintenance results of the electric test vehicle. The present invention fully considers the phenomenon of electromagnetic interference during the operation of the electric test vehicle, and thus allocates the work of the electric test vehicle through the integrated electric test vehicle management system according to the electromagnetic interference situation, making the work allocation of the electric test vehicle more reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, without paying any creative work, they can also obtain drawings of other embodiments based on these drawings.

[0041] Figure 1 A flow chart showing the overall method of operation and maintenance of the integrated electric test vehicle management system;

[0042] Figure 2A first method flow chart of the operation and maintenance method of the integrated electric test vehicle management system is shown;

[0043] Figure 3 A second method flow chart of the operation and maintenance method of the integrated electric test vehicle management system is shown;

[0044] Figure 4 The system block diagram of the operation and maintenance system of the integrated electric test vehicle management system is shown. DETAILED DESCRIPTION

[0045] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of the present application and the features therein can be combined with each other.

[0046] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0047] like Figure 1 As shown, the first aspect of the present invention provides an operation and maintenance method of an integrated electric test vehicle management system, comprising the following steps:

[0048] S102: Acquire environmental data of the area to be repaired in the target area, and acquire electromagnetic characteristic data of the position of the electric test vehicle in the area to be repaired in the target area based on the environmental data of the area to be repaired in the target area;

[0049] S104: Acquire electromagnetic anti-interference capability data of the electric test vehicle, and initialize a work assignment result of the electric test vehicle based on the electromagnetic characteristic data of the location of the electric test vehicle in the area to be repaired in the target area and the electromagnetic anti-interference capability data of the electric test vehicle;

[0050] S106: Acquire historical service data information of the electric test vehicle, and build a fault prediction model based on the historical service data information of the electric test vehicle, and predict fault information of each electric test vehicle using the fault prediction model;

[0051] S108: Redistribute the work distribution results of the electric test vehicle according to the fault information of each electric test vehicle, obtain the operation and maintenance results of the electric test vehicle, and transmit the operation and maintenance results of the electric test vehicle to the electric test vehicle control terminal through the integrated electric test vehicle management system.

[0052] It should be noted that the present invention fully considers the phenomenon of electromagnetic interference during the operation of the electric test vehicle, and thus distributes the work of the electric test vehicle through the integrated electric test vehicle management system according to the electromagnetic interference situation, making the work distribution of the electric test vehicle more reasonable.

[0053] Furthermore, in this method, environmental data of the area to be repaired in the target area is obtained, and electromagnetic characteristic data of the area to be repaired in the target area is obtained based on the environmental data of the area to be repaired in the target area, specifically:

[0054] Obtain environmental data that affects electromagnetic signature data, and use big data to retrieve the attenuation ratio of electromagnetic data under different environmental data. Graph neural networks are introduced, with environmental data as the first graph node and the attenuation ratio as the second graph node.

[0055] Connecting the first graph node and the second graph node to construct a topology graph, performing matrix representation on the topology graph to obtain an adjacency matrix, constructing a database, inputting the adjacency matrix one by one into a storage space of the database, and configuring a query address;

[0056] Obtaining environmental data of the area to be repaired in the target area, inputting the environmental data of the area to be repaired in the target area into the database for data query, and obtaining an attenuation ratio of electromagnetic data under the environmental data of the area to be repaired in the target area;

[0057] Acquire electromagnetic data of the area to be repaired, the location of the electric test vehicle during maintenance, and the location of the area to be repaired through an electromagnetic sensor, and calculate a Euclidean distance value based on the location of the electric test vehicle during maintenance and the location of the area to be repaired;

[0058] The electromagnetic characteristic data of the position of the electric test vehicle in the target area to be repaired is calculated based on the Euclidean distance value, the attenuation ratio of the electromagnetic data under the environmental data of the area to be repaired in the target area, and the electromagnetic data of the area to be repaired.

[0059] It should be noted that since electric test vehicles often need to collect data in the maintenance area, different environmental data (temperature, humidity, visibility, etc.) will cause electromagnetic transmission to be affected, resulting in delays or interference in the collected data. Under the environmental data, the larger the Euclidean distance value, the greater the attenuation ratio, which causes abnormalities in the collected data. Through this method, the electromagnetic characteristic data of the electric test vehicle's location in the target area to be repaired can be calculated. The attenuation ratio ranges from 0 to 1. The worse the environmental data, the greater the attenuation ratio, which can more accurately predict the interference electromagnetic wave data at the location where the electric test vehicle is being repaired. Electromagnetic data includes data such as the type, wavelength, and frequency of the electromagnetic wave.

[0060] like Figure 2 As shown, further, in this method, the electromagnetic anti-interference capability data of the electric test vehicle is obtained, and the work allocation result of the electric test vehicle is initialized according to the electromagnetic characteristic data of the location of the electric test vehicle in the area to be repaired in the target area and the electromagnetic anti-interference capability data of the electric test vehicle, which specifically includes:

[0061] S202: Acquire electromagnetic anti-interference capability data of the electric test vehicles, randomly select a combination of electric test vehicles, and randomly assign them to each area to be repaired, and obtain electromagnetic characteristic data of the location where each electric test vehicle in the combination of electric test vehicles is located during maintenance;

[0062] S204: Determine whether the electromagnetic characteristic data of the location where each electric test vehicle in the combination of electric test vehicles is located during maintenance is less than the electromagnetic anti-interference capability data of the electric test vehicle;

[0063] S206: When the electromagnetic characteristic data of the location where each electric test vehicle in the combination of electric test vehicles is located during maintenance is less than the electromagnetic anti-interference capability data of the electric test vehicle, the combination of electric test vehicles is output, and work is allocated according to the combination of electric test vehicles to generate a work allocation result for the electric test vehicles;

[0064] S208: When the electromagnetic characteristic data of the location where each electric test vehicle in the combination of electric test vehicles is located during maintenance is not all smaller than the electromagnetic anti-interference capability data of the electric test vehicle, the combination of electric test vehicles is reallocated.

[0065] It should be noted that when the electromagnetic signature data of each electric test vehicle in the combination of electric test vehicles at the location where it is being maintained is less than the electromagnetic anti-interference capability data of the electric test vehicle, optimization through a genetic algorithm can improve the rationality of the work allocation of the electric test vehicles. The electromagnetic anti-interference capability data includes the wavelength of the anti-interference electromagnetic wave and the type of electromagnetic wave.

[0066] Furthermore, in this method, historical service data information of the electric test vehicle is obtained, and a fault prediction model is constructed based on the historical service data information of the electric test vehicle, specifically including:

[0067] Acquiring historical service data information of the electric test vehicle, constructing a training set based on the historical service data information of the electric test vehicle, constructing a fault prediction model based on a deep neural network, and inputting the training set into the fault prediction model for training;

[0068] After the loss function of the fault prediction model converges to a preset value, the model parameters of the fault prediction model are saved, the training of the fault prediction model is completed, and the fault prediction model is output.

[0069] Furthermore, in this method, the fault information of each electric test vehicle is predicted by the fault prediction model, specifically:

[0070] Acquiring service data information of the electric test vehicle within a preset time, and inputting the service data information of the electric test vehicle within the preset time into the fault prediction model to perform fault prediction;

[0071] The fault time and fault type of each electric test vehicle are obtained through prediction, and the fault information of each electric test vehicle is generated according to the fault time and fault type of each electric test vehicle.

[0072] It should be noted that deep neural networks include recursive neural networks, BP neural networks, convolutional neural networks, etc.

[0073] like Figure 3 As shown, further, in this method, the work allocation results of the electric test vehicles are redistributed according to the fault information of each electric test vehicle to obtain the operation and maintenance results of the electric test vehicle, which specifically includes:

[0074] S302: Obtain the maintenance type of each maintenance area, construct a search tag based on the maintenance type of the maintenance area, and perform a search through big data based on the search tag to obtain the average maintenance time of each maintenance area;

[0075] S304: Determine whether there is an electric test vehicle whose fault time in the fault information is the average maintenance time in the maintenance area;

[0076] S306: When there is an electric test vehicle whose fault time in the fault information is within the average maintenance time of the maintenance area, the work allocation result of the electric test vehicle is reallocated, and the operation and maintenance result of the electric test vehicle is calculated based on the reallocated work allocation result;

[0077] S308: When there is no electric test vehicle whose fault time in the fault information is within the average maintenance time of the maintenance area, generating an operation and maintenance result of the electric test vehicle based on the work allocation result of the electric test vehicle.

[0078] It should be noted that this method can improve the rationality of the work distribution of the electric test vehicle.

[0079] like Figure 4As shown, the second aspect of the present invention provides an operation and maintenance system 4 of an integrated electric test vehicle management system. The system 4 includes a memory 41 and a processor 42. The memory 41 includes an operation and maintenance method program of the integrated electric test vehicle management system. When the operation and maintenance method program of the integrated electric test vehicle management system is executed by the processor 42, the following steps are implemented:

[0080] Acquiring environmental data of the area to be repaired in the target area, and acquiring electromagnetic characteristic data of a position of the electric power test vehicle in the area to be repaired in the target area based on the environmental data of the area to be repaired in the target area;

[0081] Acquire electromagnetic anti-interference capability data of the electric test vehicle, and initialize a work assignment result of the electric test vehicle based on the electromagnetic characteristic data of the location of the electric test vehicle in the area to be repaired in the target area and the electromagnetic anti-interference capability data of the electric test vehicle;

[0082] Acquiring historical service data information of the electric test vehicle, and building a fault prediction model based on the historical service data information of the electric test vehicle, and predicting fault information of each electric test vehicle using the fault prediction model;

[0083] The work distribution results of the electric test vehicle are redistributed according to the fault information of each electric test vehicle, and the operation and maintenance results of the electric test vehicle are obtained. The operation and maintenance results of the electric test vehicle are transmitted to the electric test vehicle control terminal through the integrated electric test vehicle management system.

[0084] Furthermore, in this system, environmental data of the area to be repaired in the target area is obtained, and electromagnetic characteristic data of the area to be repaired in the target area is obtained based on the environmental data of the area to be repaired in the target area, specifically:

[0085] Obtain environmental data that affects electromagnetic signature data, and use big data to retrieve the attenuation ratio of electromagnetic data under different environmental data. Graph neural networks are introduced, with environmental data as the first graph node and the attenuation ratio as the second graph node.

[0086] Connecting the first graph node and the second graph node to construct a topology graph, performing matrix representation on the topology graph to obtain an adjacency matrix, constructing a database, inputting the adjacency matrix one by one into a storage space of the database, and configuring a query address;

[0087] Obtaining environmental data of the area to be repaired in the target area, inputting the environmental data of the area to be repaired in the target area into the database for data query, and obtaining an attenuation ratio of electromagnetic data under the environmental data of the area to be repaired in the target area;

[0088] Acquire electromagnetic data of the area to be repaired, the location of the electric test vehicle during maintenance, and the location of the area to be repaired through an electromagnetic sensor, and calculate a Euclidean distance value based on the location of the electric test vehicle during maintenance and the location of the area to be repaired;

[0089] The electromagnetic characteristic data of the position of the electric test vehicle in the target area to be repaired is calculated based on the Euclidean distance value, the attenuation ratio of the electromagnetic data under the environmental data of the area to be repaired in the target area, and the electromagnetic data of the area to be repaired.

[0090] Furthermore, in the present system, the electromagnetic anti-interference capability data of the electric test vehicle is obtained, and the work allocation result of the electric test vehicle is initialized according to the electromagnetic characteristic data of the location of the electric test vehicle in the area to be repaired in the target area and the electromagnetic anti-interference capability data of the electric test vehicle, specifically including:

[0091] Introducing a genetic algorithm and setting a genetic generation based on the genetic algorithm to obtain electromagnetic anti-interference capability data of the electric test vehicles, randomly selecting a combination of electric test vehicles and randomly assigning them to each area to be repaired, and obtaining electromagnetic characteristic data of the location where each electric test vehicle in the combination of electric test vehicles is located during maintenance;

[0092] Determining whether electromagnetic characteristic data of the location where each electric test vehicle in the combination of electric test vehicles is located during maintenance is less than electromagnetic anti-interference capability data of the electric test vehicle;

[0093] When the electromagnetic characteristic data of the location where each electric test vehicle in the combination of the electric test vehicles is located during maintenance is less than the electromagnetic anti-interference capability data of the electric test vehicle, the combination of the electric test vehicles is output, and work allocation is performed according to the combination of the electric test vehicles to generate a work allocation result for the electric test vehicles;

[0094] When the electromagnetic characteristic data of the location where each electric test vehicle in the combination of the electric test vehicles is located during maintenance is not all smaller than the electromagnetic anti-interference capability data of the electric test vehicle, the combination of the electric test vehicles is reallocated.

[0095] Furthermore, in this system, historical service data information of the electric test vehicle is obtained, and a fault prediction model is constructed based on the historical service data information of the electric test vehicle, specifically including:

[0096] Acquiring historical service data information of the electric test vehicle, constructing a training set based on the historical service data information of the electric test vehicle, constructing a fault prediction model based on a deep neural network, and inputting the training set into the fault prediction model for training;

[0097] After the loss function of the fault prediction model converges to a preset value, the model parameters of the fault prediction model are saved, the training of the fault prediction model is completed, and the fault prediction model is output.

[0098] Furthermore, in this system, the fault prediction model is used to predict the fault information of each electric test vehicle, specifically:

[0099] Acquiring service data information of the electric test vehicle within a preset time, and inputting the service data information of the electric test vehicle within the preset time into the fault prediction model to perform fault prediction;

[0100] The fault time and fault type of each electric test vehicle are obtained through prediction, and the fault information of each electric test vehicle is generated according to the fault time and fault type of each electric test vehicle.

[0101] Furthermore, in the present system, the work allocation results of the electric test vehicles are redistributed according to the fault information of each electric test vehicle to obtain the operation and maintenance results of the electric test vehicle, specifically including:

[0102] Obtain the maintenance type of each maintenance area, and construct a search tag based on the maintenance type of the maintenance area. Search through big data based on the search tag to obtain the average maintenance time of each maintenance area;

[0103] Determine whether there is an electric test vehicle whose fault time in the fault information is equal to the average maintenance time in the maintenance area;

[0104] When there is an electric test vehicle whose fault time in the fault information is within the average maintenance time of the maintenance area, the work allocation result of the electric test vehicle is reallocated, and the operation and maintenance result of the electric test vehicle is calculated based on the reallocated work allocation result;

[0105] When there is no electric test vehicle whose fault time in the fault information is within the average maintenance time of the maintenance area, an operation and maintenance result of the electric test vehicle is generated based on the work allocation result of the electric test vehicle.

[0106] The third aspect of the present invention provides a computer-readable storage medium, which includes an operation and maintenance method program of an integrated electric test vehicle management system. When the operation and maintenance method program of the integrated electric test vehicle management system is executed by a processor, the steps of any one of the operation and maintenance methods of the integrated electric test vehicle management system are implemented.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0108] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0109] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0110] Those skilled in the art will appreciate that all or part of the steps of the above-mentioned method embodiments may be implemented by hardware associated with program instructions, and the aforementioned program may be stored in a computer-readable storage medium. When the program is executed, the program executes the steps of the above-mentioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0111] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0112] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A comprehensive vehicle management and operation and maintenance method, characterized in that: The following steps are involved: Acquire environmental data of the area to be repaired in the target area, and acquire electromagnetic characteristic data of the position of the integrated vehicle in the area to be repaired in the target area based on the environmental data of the area to be repaired in the target area; Acquire electromagnetic anti-interference capability data of the integrated vehicle, and initialize the work allocation result of the integrated vehicle according to the electromagnetic characteristic data of the location of the integrated vehicle in the area to be repaired in the target area and the electromagnetic anti-interference capability data of the integrated vehicle; Acquiring historical service data information of the integrated vehicle, building a fault prediction model based on the historical service data information of the integrated vehicle, and predicting fault information of each integrated vehicle using the fault prediction model; Re-allocating the work allocation results of the integrated vehicle according to the fault information of each integrated vehicle, obtaining the operation and maintenance results of the integrated vehicle, and transmitting the operation and maintenance results of the integrated vehicle to the integrated vehicle control terminal through the integrated vehicle management system; Acquire environmental data of the area to be repaired in the target area, and acquire electromagnetic characteristic data of the area to be repaired in the target area according to the environmental data of the area to be repaired in the target area, specifically: Obtain environmental data that affects electromagnetic signature data, and use big data to retrieve the attenuation ratio of electromagnetic data under different environmental data. Graph neural networks are introduced, with environmental data as the first graph node and the attenuation ratio as the second graph node. Connecting the first graph node and the second graph node to construct a topology graph, performing matrix representation on the topology graph to obtain an adjacency matrix, constructing a database, inputting the adjacency matrix one by one into a storage space of the database, and configuring a query address; Obtaining environmental data of the area to be repaired in the target area, inputting the environmental data of the area to be repaired in the target area into the database for data query, and obtaining an attenuation ratio of electromagnetic data under the environmental data of the area to be repaired in the target area; Acquire electromagnetic data of the area to be repaired, the location of the integrated vehicle during maintenance, and the location of the area to be repaired through an electromagnetic sensor, and calculate a Euclidean distance value based on the location of the integrated vehicle during maintenance and the location of the area to be repaired; Calculate electromagnetic characteristic data of the location of the integrated vehicle in the target area to be repaired based on the Euclidean distance value, the attenuation ratio of the electromagnetic data under the environmental data of the area to be repaired in the target area, and the electromagnetic data of the area to be repaired; Acquire the electromagnetic anti-interference capability data of the integrated vehicle, and initialize the work allocation result of the integrated vehicle according to the electromagnetic characteristic data of the location of the integrated vehicle in the area to be repaired in the target area and the electromagnetic anti-interference capability data of the integrated vehicle, specifically including: Obtain electromagnetic anti-interference capability data of the integrated vehicles, randomly select a combination of integrated vehicles, and randomly assign them to each area to be repaired, and obtain electromagnetic characteristic data of the location where each integrated vehicle in the combination is located during maintenance; Determining whether the electromagnetic characteristic data of the location where each integrated vehicle in the combination of integrated vehicles is located during maintenance is less than the electromagnetic anti-interference capability data of the integrated vehicle; When the electromagnetic characteristic data of the position where each integrated vehicle in the combination of integrated vehicles is located during maintenance is less than the electromagnetic anti-interference capability data of the integrated vehicle, the combination of integrated vehicles is output, and work allocation is performed according to the combination of integrated vehicles to generate a work allocation result for the integrated vehicles; When the electromagnetic characteristic data of the position where each integrated vehicle in the combination of integrated vehicles is located during maintenance is not all smaller than the electromagnetic anti-interference capability data of the integrated vehicle, the combination of integrated vehicles is reallocated.

2. A comprehensive vehicle management and operation and maintenance method according to claim 1, characterized in that: Obtaining historical service data information of the integrated vehicle and building a fault prediction model based on the historical service data information of the integrated vehicle, specifically including: Acquiring historical service data information of the integrated vehicle, constructing a training set based on the historical service data information of the integrated vehicle, constructing a fault prediction model based on a deep neural network, and inputting the training set into the fault prediction model for training; After the loss function of the fault prediction model converges to a preset value, the model parameters of the fault prediction model are saved, the training of the fault prediction model is completed, and the fault prediction model is output.

3. A comprehensive vehicle management and operation and maintenance method according to claim 1, characterized in that: The fault prediction model is used to predict the fault information of each integrated vehicle, specifically: Acquiring service data information of the integrated vehicle within a preset time, and inputting the service data information of the integrated vehicle within the preset time into the fault prediction model to perform fault prediction; Through prediction, the failure time and failure type of each integrated vehicle are obtained, and the failure information of each integrated vehicle is generated according to the failure time and failure type of each integrated vehicle.

4. A comprehensive vehicle management and operation and maintenance method according to claim 1, characterized in that: Re-allocating the work allocation results of the integrated vehicles according to the fault information of each integrated vehicle to obtain the operation and maintenance results of the integrated vehicles, specifically including: Obtain the maintenance type of each maintenance area, and construct a search tag based on the maintenance type of the maintenance area. Search through big data based on the search tag to obtain the average maintenance time of each maintenance area; Determine whether there is a comprehensive vehicle whose fault time in the fault information is equal to the average maintenance time in the maintenance area; When there is a comprehensive vehicle whose fault time in the fault information is within the average repair time of the maintenance area, the work allocation result of the comprehensive vehicle is reallocated, and the operation and maintenance result of the comprehensive vehicle is calculated based on the reallocated work allocation result; When there is no integrated vehicle whose fault time in the fault information is within the average maintenance time of the maintenance area, an operation and maintenance result of the integrated vehicle is generated based on the work allocation result of the integrated vehicle.

5. A computer-readable storage medium, characterized in that The computer-readable storage medium includes an operation and maintenance method program of an integrated vehicle management system. When the operation and maintenance method program of the integrated vehicle management system is executed by a processor, the steps of the operation and maintenance method of the integrated vehicle management system as described in any one of claims 1-4 are implemented.

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