A charging pile safety monitoring system

Abstract

The present application relates to the field of charging pile safety technology, and discloses a charging pile safety monitoring system, which includes a charging pile aging test module and a charging pile aging feedback module connected in communication. The present application utilizes a charging pile aging test module and a charging pile aging feedback module connected in communication to achieve comprehensive and systematic safety monitoring of charging piles. The control unit coordinates the test power supply unit, the test charging pile unit, and the test load unit to simulate the charging process, collect multi-dimensional test charging data, and transmit it to the analysis unit. The analysis unit generates a charging pile aging monitoring model in combination with the current charging data, which achieves accurate analysis of charging pile failures and effective prediction of life.

Description

Technical Field

[0001] The present application relates to the field of charging pile safety technology, and specifically to a charging pile safety monitoring system. Background Art

[0002] With the widespread popularity of electric vehicles, charging piles, as important supporting facilities, have attracted much attention for their safety and reliability. However, the existing safety monitoring technology for charging piles has many shortcomings.

[0003] In traditional charging pile testing, only simple functional tests are often performed on the charging piles, lacking effective monitoring of performance changes and safety hazards during long-term use. On the one hand, the performance data collection of charging piles under different working conditions (such as different voltages, currents, power loads and temperature environments) is not comprehensive enough, and it is impossible to accurately grasp its actual operating conditions under complex working conditions. On the other hand, existing technologies make it difficult to effectively predict the life of charging piles, and it is impossible to assess in advance the time when charging piles may fail, making it difficult to formulate a reasonable maintenance plan.

[0004] At the same time, in terms of fault analysis, there is a lack of systematic methods and knowledge base support, making it difficult to quickly and accurately identify and locate the causes of new fault types. In addition, the data utilization efficiency is low, and the potential information in the test data is not fully mined to optimize the monitoring and prediction models.

[0005] In addition, the detection process is not closely integrated with the actual operation scenario, resulting in the test results may not truly reflect the safety performance of the charging pile in actual use. Chinese patent number CN202411437105.3 discloses a charging pile health detection system based on Internet of Things technology, but the invention fails to monitor the aging of charging piles.

[0006] Therefore, there is an urgent need for a new charging pile safety monitoring system to ensure the safe and stable operation of charging piles and improve the overall quality and reliability of electric vehicle charging facilities. Summary of the invention

[0007] The purpose of this application is to provide a charging pile safety monitoring system to solve the technical problems raised in the above background technology.

[0008] To achieve the above-mentioned purpose, the present application discloses the following technical solutions: a charging pile safety monitoring system, comprising a charging pile aging test module and a charging pile aging feedback module connected in communication;

[0009] The charging pile aging test module includes a control unit, a test power supply unit, a test charging pile unit and a test load unit; when the charging pile aging test module is running, the control unit controls the test power supply unit to charge the test load unit through the test charging pile unit based on a preset charging process, and the control unit collects the test charging data generated by the charging process and transmits it to the charging pile aging feedback module; wherein: the test power supply unit is connected to the test charging pile unit, the test charging pile unit is connected to the test load unit, the test power supply unit, the test charging pile unit and the test load unit are all connected to the control unit, and the control unit is connected to the charging pile aging feedback module; the test charging data at least includes the first performance parameter data of the test power supply unit, the second performance parameter data of the test charging pile unit and the third performance parameter data of the test load unit, and the performance parameter data at least includes voltage, current, power and temperature;

[0010] The charging pile aging feedback module includes an analysis unit, an active power supply unit, an active charging pile unit, an active load unit and a visualization unit; when the charging pile aging feedback module is running, the analysis unit receives and analyzes the test charging data to generate a charging pile aging monitoring model, and monitors the active charging data based on the charging pile aging monitoring model, and generates an aging report based on the monitoring result, and the visualization unit receives the aging report and displays it; wherein: the active power supply unit is connected to the active charging pile unit, the active charging pile unit is connected to the active load unit, the active power supply unit, the active charging pile unit and the active load unit are all connected to the analysis unit, the analysis unit is connected to the charging pile aging test module, and the analysis unit is connected to the visualization unit; the active charging data at least includes the fourth performance parameter data of the active power supply unit, the fifth performance parameter data of the active charging pile unit and the sixth performance parameter data of the active load unit; the charging pile aging monitoring model is used to perform safety monitoring on the charging pile based on the test charging data and in combination with the active charging data, and the safety monitoring at least includes fault analysis and life prediction.

[0011] Preferably, the control unit controls the charging process of the test power supply unit charging the test load unit via the test charging pile unit based on a preset charging process, specifically:

[0012] Extracting features from the current charging data to obtain a charging feature set, wherein the charging feature set is used to characterize the performance parameter requirements that the test power supply unit, the test charging pile unit, and the test load unit need to meet when performing a charging pile aging test;

[0013] The charging feature set is saved to the control unit. When the charging pile aging test module is running, the control unit selects the charging feature set and controls the test power supply unit, the test charging pile unit and the test load unit to execute, thereby completing the corresponding charging process.

[0014] Preferably, the process of collecting the test charging data includes:

[0015] When the test power supply unit, the test charging pile unit and the test load unit perform a charging process, first performance parameter data of the test power supply unit is collected based on a time series, second performance parameter data of the test charging pile unit is collected based on a time series, and third performance parameter data of the test load unit is collected based on a time series;

[0016] The first performance parameter data, the second performance parameter data and the third performance parameter data are packaged to obtain test charging data.

[0017] Preferably, the generation process of the charging pile aging monitoring model includes:

[0018] A charging pile aging monitoring learning model is constructed using deep learning technology. The model stores a fault knowledge base for fault analysis and a life assessment algorithm for life prediction.

[0019] Inputting the charging test data into the charging pile aging monitoring learning model and training it, the training at least comprising updating the fault knowledge base based on the faults existing in the charging test data and updating the life assessment algorithm based on the charging test data;

[0020] The charging pile aging monitoring learning model that meets the preset model accuracy threshold is output and defined as the charging pile aging monitoring model.

[0021] Preferably, the updating of the fault knowledge base based on the faults existing in the charging test data is specifically:

[0022] Acquiring expert knowledge for fault analysis, verifying the expert knowledge based on the expert knowledge and in combination with the test charging data, and storing the verified expert knowledge in the fault knowledge base;

[0023] Based on the test charging data, feature extraction is performed on faults that do not belong to the expert knowledge to obtain data-driven knowledge, and the data-driven knowledge is verified, and the verified data-driven knowledge is stored in the fault knowledge base.

[0024] Preferably, the updating of the life evaluation algorithm based on the charging test data is specifically as follows:

[0025] The life assessment algorithm stores a comprehensive life calculation formula for life prediction, and the comprehensive life calculation formula is specifically:

[0026] ;

[0027] in, For charging piles in time The total failure probability, is the calculated predicted lifespan;

[0028] Update the test charging data using , and update Specifically:

[0029] ;

[0030] in, is a voltage failure probability function updated based on the test charging data and obtained based on the probability of charging piles failing due to voltage factors in historical test charging data, is a current failure probability function updated based on the test charging data and obtained based on the probability of charging piles failing due to current factors in historical test charging data, is a power failure probability function updated based on the test charging data and obtained based on the probability of charging piles failing due to power factors in historical test charging data, It is a temperature failure probability function updated based on the test charging data and the function is obtained based on the probability of charging piles failing due to temperature factors in historical test charging data.

[0031] Preferably, the process of collecting the active charging data includes:

[0032] When the active power supply unit, the active charging pile unit and the active load unit perform an actual charging process, the fourth performance parameter data of the active power supply unit is collected based on a time series, the fifth performance parameter data of the active charging pile unit is collected based on a time series, and the sixth performance parameter data of the active load unit is collected based on a time series;

[0033] The fourth performance parameter data, the fifth performance parameter data and the sixth performance parameter data are packaged to obtain the active charging data.

[0034] Preferably, the monitoring of the current charging data based on the charging pile aging monitoring model is specifically as follows:

[0035] Inputting the current charging data into the charging pile aging monitoring model;

[0036] Run the charging pile aging monitoring model to perform fault analysis and life prediction; wherein the fault analysis specifically involves calling the fault knowledge base to perform fault analysis on the active charging data to obtain the active charging pile faults, and the life prediction specifically involves calling the life assessment algorithm to predict the active charging data to obtain the predicted life of the active charging piles.

[0037] Preferably, the generation process of the aging report includes:

[0038] Obtain the fault of the active charging pile and the predicted life of the active charging pile;

[0039] An aging report is generated by utilizing natural language technology and a preset aging report template, combining the faults of the active charging piles and the predicted life of the active charging piles.

[0040] Preferably, the receiving and displaying of the aging report is specifically:

[0041] The aging report is displayed in a preset display mode by using visualization technology and a preset display template in combination with the aging report.

[0042] Beneficial effects: The charging pile safety monitoring system of the present application utilizes a charging pile aging test module and a charging pile aging feedback module connected by communication to achieve comprehensive and systematic safety monitoring of charging piles. The control unit coordinates the test power supply unit, the test charging pile unit, and the test load unit to simulate the charging process, collect multi-dimensional test charging data and transmit it to the analysis unit. The analysis unit generates a charging pile aging monitoring model based on the current charging data, achieving accurate analysis of charging pile failures and effective prediction of life. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 This is a structural block diagram of the charging pile safety monitoring system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] The technical solutions in the embodiments of the present application are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0046] In this article, the term "comprising" is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprising..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0047] This embodiment discloses Figure 1 A charging pile safety monitoring system shown includes a charging pile aging test module and a charging pile aging feedback module connected in communication;

[0048] The charging pile aging test module includes a control unit, a test power supply unit, a test charging pile unit and a test load unit; when the charging pile aging test module is running, the control unit controls the test power supply unit to charge the test load unit via the test charging pile unit based on a preset charging process, and the control unit collects the test charging data generated by the charging process and transmits it to the charging pile aging feedback module; wherein: the test power supply unit is connected to the test charging pile unit, the test charging pile unit is connected to the test load unit, the test power supply unit, the test charging pile unit and the test load unit are all connected to the control unit, and the control unit is connected to the charging pile aging feedback module; the test charging data at least includes the first performance parameter data of the test power supply unit, the second performance parameter data of the test charging pile unit and the third performance parameter data of the test load unit, and the performance parameter data at least includes voltage, current, power and temperature;

[0049] The charging pile aging feedback module includes an analysis unit, an active power supply unit, an active charging pile unit, an active load unit and a visualization unit; when the charging pile aging feedback module is running, the analysis unit receives and analyzes the test charging data to generate a charging pile aging monitoring model, and monitors the active charging data based on the charging pile aging monitoring model, and generates an aging report based on the monitoring results, and the visualization unit receives the aging report and displays it; wherein: the active power supply unit is connected to the active charging pile unit, the active charging pile unit is connected to the active load unit, the active power supply unit, the active charging pile unit and the active load unit are all connected to the analysis unit, the analysis unit is connected to the charging pile aging test module, and the analysis unit is connected to the visualization unit; the active charging data at least includes the fourth performance parameter data of the active power supply unit, the fifth performance parameter data of the active charging pile unit and the sixth performance parameter data of the active load unit; the charging pile aging monitoring model is used to perform safety monitoring on the charging pile based on the test charging data and in combination with the active charging data, and the safety monitoring at least includes fault analysis and life prediction.

[0050] It should be noted that the charging pile aging test module of the present embodiment can be directly applied to the factory inspection of charging piles by charging pile manufacturers and even destructive charging pile experiments, so as to improve the quality of charging piles. Furthermore, the charging pile aging feedback module of the present embodiment can be directly applied to the use of charging pile managers, and based on the communication connection between the charging pile aging test module and the charging pile aging feedback module, the charging pile manufacturer can realize the service upgrade of the charging pile manager.

[0051] Through the above, this embodiment utilizes the communication-connected charging pile aging test module and the charging pile aging feedback module to achieve comprehensive and systematic safety monitoring of the charging pile. The control unit coordinates the test power supply unit, the test charging pile unit, and the test load unit to simulate the charging process, collect multi-dimensional test charging data and transmit it to the analysis unit. The analysis unit generates a charging pile aging monitoring model based on the current charging data, which achieves accurate analysis of charging pile failures and effective prediction of life. In actual operation, hidden faults such as unstable power output caused by long-term use can be discovered in time, and the remaining service life of the charging pile can be estimated, providing a scientific basis for maintenance and replacement, ensuring the safe and stable operation of the charging pile, and improving the reliability of the entire charging facility.

[0052] Specifically, the control unit controls the charging process of the test power supply unit charging the test load unit via the test charging pile unit based on a preset charging process, specifically:

[0053] Feature extraction is performed on the current charging data to obtain a charging feature set, which is used to characterize the performance parameter requirements that need to be met by the test power supply unit, the test charging pile unit, and the test load unit when performing the charging pile aging test;

[0054] The charging feature set is saved to the control unit. When the charging pile aging test module is running, the control unit selects the charging feature set and controls the test power supply unit, the test charging pile unit and the test load unit to execute and complete the corresponding charging process.

[0055] Based on the above, this embodiment uses the feature extraction of the current charging data to obtain the charging feature set, thereby achieving precise control of the charging process. The control unit controls each unit to perform corresponding charging operations based on the feature set to ensure that the test environment is consistent with actual needs. In a simple example, if the current charging pile is often overloaded during peak hours, the appropriate power, current and other parameter requirements are determined through feature extraction, and the working conditions are simulated in the test to make the test results more targeted. This improves the effectiveness of the test, helps to discover potential problems, optimizes the performance of the charging pile, and ensures its safety in actual use.

[0056] Specifically, the collection process of test charging data includes:

[0057] When the test power supply unit, the test charging pile unit and the test load unit perform a charging process, first performance parameter data of the test power supply unit is collected based on a time series, second performance parameter data of the test charging pile unit is collected based on a time series, and third performance parameter data of the test load unit is collected based on a time series;

[0058] The first performance parameter data, the second performance parameter data and the third performance parameter data are packaged to obtain test charging data.

[0059] Based on the above, this embodiment uses a method of collecting and packaging performance parameter data of each unit based on time series to achieve comprehensive and orderly test charging data collection. During the test, data such as voltage, current, power, and temperature at different time points can be obtained in real time to fully record performance changes during the charging process. For example, when the temperature of the test charging pile unit rises abnormally in the middle of charging, the data collected through the time series can clearly trace the temperature change trend and help analyze the cause of the fault. It provides rich and accurate data support for the subsequent accurate analysis of the aging of the charging pile, judgment of the fault type, and prediction of the life span, and improves the reliability of safety monitoring.

[0060] Specifically, the generation process of the charging pile aging monitoring model includes:

[0061] A charging pile aging monitoring learning model is constructed using deep learning technology. The model stores a fault knowledge base for fault analysis and a life assessment algorithm for life prediction.

[0062] Inputting the charging test data into the charging pile aging monitoring learning model and training it, the training at least including updating the fault knowledge base based on the faults existing in the charging test data and updating the life assessment algorithm based on the charging test data;

[0063] The charging pile aging monitoring learning model that meets the preset model accuracy threshold is output and defined as the charging pile aging monitoring model.

[0064] Based on the above, this embodiment uses existing deep learning technology to construct and train a charging pile aging monitoring learning model, thereby achieving efficient and accurate aging monitoring model generation. By inputting charging test data into the model, the fault knowledge base and life assessment algorithm are continuously updated to adapt to various actual situations. In a simple example, when encountering a new type of fault, the fault knowledge base can be updated based on data-driven knowledge to improve the fault analysis capability. Finally, a model that meets the accuracy threshold is obtained, which can more accurately monitor the safety of the charging pile, effectively reduce the risk of failure, and extend the service life of the charging pile.

[0065] Specifically, the fault knowledge base is updated based on the faults existing in the charging test data, specifically:

[0066] Acquire expert knowledge for fault analysis, verify the expert knowledge based on the expert knowledge and in combination with test charging data, and save the verified expert knowledge in a fault knowledge base;

[0067] Based on the test charging data, the features of the faults that do not belong to the expert knowledge are extracted to obtain the data-driven knowledge, and the data-driven knowledge is verified, and the verified data-driven knowledge is saved in the fault knowledge base.

[0068] Based on the above, this embodiment uses the acquisition of expert knowledge combined with test charging data verification, as well as the extraction and verification of new fault data-driven knowledge, to achieve a comprehensive update of the fault knowledge base. Expert knowledge provides a theoretical basis for fault analysis, such as relying on empirical knowledge when judging circuit faults. Data-driven knowledge supplements newly emerging complex fault conditions. In a simple example, the fault is caused by the charging compatibility problem between the charging pile and the new electric vehicle. The combination of the two makes the fault knowledge base more complete, improves the ability to identify and analyze various fault types, and ensures the safe operation of the charging pile.

[0069] Specifically, the life evaluation algorithm is updated based on the charging test data, specifically:

[0070] The life assessment algorithm stores a comprehensive life calculation formula for life prediction, which is specifically:

[0071] ;

[0072] in, For charging piles in time The total failure probability, is the calculated predicted lifespan;

[0073] Update with test charging data , and update Specifically:

[0074] ;

[0075] in, is a voltage failure probability function updated based on the test charging data and obtained based on the probability of charging piles failing due to voltage factors in the historical test charging data, is a current failure probability function updated based on the test charging data and obtained based on the probability of charging piles failing due to current factors in the historical test charging data, is a power failure probability function updated based on the test charging data and the function is obtained based on the probability of charging piles failing due to power factors in the historical test charging data, It is a temperature failure probability function updated based on the test charging data and is obtained based on the probability of charging piles failing due to temperature factors in historical test charging data.

[0076] As a preferred implementation of this embodiment, , , and The failure probability formula can be constructed based on the same principle. For example:

[0077] ;

[0078] in, is a voltage failure threshold value established based on experience known to those skilled in the art, and the voltage attenuation ( For the Secondary measurement voltage), Its probability density function is, The probability of failure of the charging pile caused by the calculated voltage can be calculated based on this formula. The probability of failure caused by voltage at different time points can be calculated to obtain the voltage-related life distribution function. , indicating that at time The cumulative probability of charging pile failure caused by internal voltage is calculated. Based on this, the , , and 's construction.

[0079] Based on the above, this embodiment uses the failure probability function of each factor in the test charging data to update the comprehensive life calculation formula, thereby achieving a more accurate life prediction. By analyzing the failure conditions caused by voltage, current, power and temperature factors in the historical test data, the failure probability function of each factor is determined, such as the adjustment of the temperature failure probability function under the high temperature environment in summer in a certain area. This enables the life assessment algorithm to better adapt to actual working conditions, more accurately estimate the life of the charging pile, provide a basis for the reasonable arrangement of maintenance and replacement plans, and reduce operating costs.

[0080] Specifically, the process of collecting active charging data includes:

[0081] When the active power supply unit, the active charging pile unit and the active load unit perform an actual charging process, the fourth performance parameter data of the active power supply unit is collected based on the time series, the fifth performance parameter data of the active charging pile unit is collected based on the time series, and the sixth performance parameter data of the active load unit is collected based on the time series;

[0082] The fourth performance parameter data, the fifth performance parameter data and the sixth performance parameter data are packaged to obtain the active charging data.

[0083] Based on the above, this embodiment uses the time series-based collection and packaging of performance parameter data of each unit in service to accurately grasp the actual operating conditions of the current charging piles. During the actual charging process, real-time data of the current power supply unit, charging pile unit and load unit can be obtained in a timely manner, such as high current and high power data collected during peak hours at commercial charging stations. These data provide actual operation references for the charging pile aging monitoring model, making the monitoring and prediction results more realistic, helping to timely discover potential safety hazards and ensure the reliable operation of the charging piles.

[0084] Specifically, the current charging data is monitored based on the charging pile aging monitoring model, specifically:

[0085] Input the current charging data into the charging pile aging monitoring model;

[0086] Run the charging pile aging monitoring model to perform fault analysis and life prediction; the fault analysis specifically involves calling the fault knowledge base to perform fault analysis on the active charging data to obtain the active charging pile faults, and the life prediction specifically involves calling the life assessment algorithm to predict the active charging data to obtain the predicted life of the active charging piles.

[0087] Based on the above, this embodiment uses the input of current charging data into the aging monitoring model for analysis, thereby realizing real-time fault analysis and life prediction of current charging piles. When the current charging pile has abnormal charging speed and other conditions, the model calls the fault knowledge base to analyze possible causes of the fault, such as poor contact of the charging line. At the same time, the remaining life is predicted through the life assessment algorithm so that maintenance measures can be taken in advance. The timeliness and effectiveness of the operation and maintenance of the charging piles are improved, and the continuity and safety of the charging service are guaranteed.

[0088] Specifically, the generation process of the aging report includes:

[0089] Obtain the fault information and predicted lifespan of the charging piles in service;

[0090] Using natural language technology and preset aging report templates, an aging report is generated by combining the faults of existing charging piles and the predicted life of existing charging piles.

[0091] Based on the above, this embodiment uses existing natural language technology to combine the faults of current charging piles and predicted life to generate an aging report, thereby achieving a clear presentation of monitoring results. The fault conditions and life prediction results are described in plain language, for example, "Charging pile a has unstable power output due to heat dissipation problems, and the estimated remaining life is 3 years." This makes it convenient for operation and maintenance personnel to quickly understand the status of the charging piles, provides clear guidance for formulating maintenance strategies, improves the efficiency of operation and maintenance work, and ensures the stable operation of the charging pile system.

[0092] Specifically, receive and display the aging report, specifically:

[0093] By using visualization technology and preset display templates, combined with the aging report, the aging report is displayed in a preset display method.

[0094] Based on the above, this embodiment uses existing visualization technology combined with aging reports for display, realizing intuitive presentation of monitoring information. Through preset display templates, such as displaying the life trend of charging piles in the form of charts and presenting fault details in the form of lists, the aging report is displayed in an intuitive way on the monitoring screen or mobile terminal. It enables operation and maintenance personnel to obtain key information more conveniently and detect anomalies in a timely manner, such as quickly locating faulty charging piles among a large number of charging pile data. It improves the efficiency of information transmission and helps to quickly respond to and handle charging pile safety issues.

[0095] In summary, the charging pile safety monitoring system of this embodiment uses the charging pile aging test module and the charging pile aging feedback module connected by communication to achieve comprehensive and systematic safety monitoring of the charging pile. The control unit coordinates the test power supply unit, the test charging pile unit and the test load unit to simulate the charging process, collect multi-dimensional test charging data and transmit it to the analysis unit. The analysis unit generates a charging pile aging monitoring model based on the current charging data, which realizes the accurate analysis of charging pile failures and the effective prediction of life.

[0096] In the embodiments provided in the present application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to implement the functions described herein, or a combination thereof. For software implementation, part or all of the processes of the embodiment can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable storage medium or transmitted as one or more instructions or codes on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein the communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The storage medium can be any available medium that can be accessed by a computer. Computer-readable storage media can include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer.

[0097] Finally, it should be noted that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A charging pile safety monitoring system, characterized in that: Including a charging pile aging test module and a charging pile aging feedback module connected by communication; The charging pile aging test module includes a control unit, a test power supply unit, a test charging pile unit and a test load unit; when the charging pile aging test module is running, the control unit controls the test power supply unit to charge the test load unit through the test charging pile unit based on a preset charging process, and the control unit collects the test charging data generated by the charging process and transmits it to the charging pile aging feedback module; wherein: the test power supply unit is connected to the test charging pile unit, the test charging pile unit is connected to the test load unit, the test power supply unit, the test charging pile unit and the test load unit are all connected to the control unit, and the control unit is connected to the charging pile aging feedback module; the test charging data at least includes the first performance parameter data of the test power supply unit, the second performance parameter data of the test charging pile unit and the third performance parameter data of the test load unit, and the performance parameter data at least includes voltage, current, power and temperature; The charging pile aging feedback module includes an analysis unit, an active power supply unit, an active charging pile unit, an active load unit and a visualization unit; when the charging pile aging feedback module is running, the analysis unit receives and analyzes the test charging data to generate a charging pile aging monitoring model, and monitors the active charging data based on the charging pile aging monitoring model, and generates an aging report based on the monitoring result, and the visualization unit receives the aging report and displays it; wherein: the active power supply unit is connected to the active charging pile unit, the active charging pile unit is connected to the active load unit, the active power supply unit, the active charging pile unit and the active load unit are all connected to the analysis unit, the analysis unit is connected to the charging pile aging test module, and the analysis unit is connected to the visualization unit; the active charging data at least includes the fourth performance parameter data of the active power supply unit, the fifth performance parameter data of the active charging pile unit and the sixth performance parameter data of the active load unit; the charging pile aging monitoring model is used to perform safety monitoring on the charging pile based on the test charging data and in combination with the active charging data, and the safety monitoring at least includes fault analysis and life prediction; Wherein, the control unit controls the charging process of the test power supply unit charging the test load unit via the test charging pile unit based on a preset charging process, specifically: Extracting features from the current charging data to obtain a charging feature set, wherein the charging feature set is used to characterize the performance parameter requirements that the test power supply unit, the test charging pile unit, and the test load unit need to meet when performing a charging pile aging test; The charging feature set is saved to the control unit. When the charging pile aging test module is running, the control unit selects the charging feature set and controls the test power supply unit, the test charging pile unit and the test load unit to execute, thereby completing the corresponding charging process.

2. The charging pile safety monitoring system according to claim 1, characterized in that: The test charging data collection process includes: When the test power supply unit, the test charging pile unit and the test load unit perform a charging process, first performance parameter data of the test power supply unit is collected based on a time series, second performance parameter data of the test charging pile unit is collected based on a time series, and third performance parameter data of the test load unit is collected based on a time series; The first performance parameter data, the second performance parameter data and the third performance parameter data are packaged to obtain test charging data.

3. The charging pile safety monitoring system according to claim 1, characterized in that: The generation process of the charging pile aging monitoring model includes: A charging pile aging monitoring learning model is constructed using deep learning technology. The model stores a fault knowledge base for fault analysis and a life assessment algorithm for life prediction. Inputting charging test data into the charging pile aging monitoring learning model and training it, the training at least comprising updating the fault knowledge base based on the faults existing in the charging test data and updating the life assessment algorithm based on the charging test data; The charging pile aging monitoring learning model that meets the preset model accuracy threshold is output and defined as the charging pile aging monitoring model.

4. The charging pile safety monitoring system according to claim 3, characterized in that: The updating of the fault knowledge base based on the faults existing in the charging test data is specifically as follows: Acquiring expert knowledge for fault analysis, verifying the expert knowledge based on the expert knowledge and in combination with the test charging data, and storing the verified expert knowledge in the fault knowledge base; Based on the test charging data, feature extraction is performed on faults that do not belong to the expert knowledge to obtain data-driven knowledge, and the data-driven knowledge is verified, and the verified data-driven knowledge is stored in the fault knowledge base.

5. The charging pile safety monitoring system according to claim 3, characterized in that: The updating of the life evaluation algorithm based on the charging test data is specifically as follows: The life assessment algorithm stores a comprehensive life calculation formula for life prediction, and the comprehensive life calculation formula is specifically: ； in, For charging piles in time The total failure probability, is the calculated predicted lifespan; Update the test charging data using , and update Specifically: ； in, is a voltage failure probability function updated based on the test charging data and obtained based on the probability of charging piles failing due to voltage factors in historical test charging data, is a current failure probability function updated based on the test charging data and obtained based on the probability of charging piles failing due to current factors in historical test charging data, is a power failure probability function updated based on the test charging data and obtained based on the probability of charging piles failing due to power factors in historical test charging data, It is a temperature failure probability function updated based on the test charging data and the function is obtained based on the probability of charging piles failing due to temperature factors in historical test charging data.

6. The charging pile safety monitoring system according to claim 1, characterized in that: The process of collecting the active charging data includes: When the active power supply unit, the active charging pile unit and the active load unit perform an actual charging process, the fourth performance parameter data of the active power supply unit is collected based on a time series, the fifth performance parameter data of the active charging pile unit is collected based on a time series, and the sixth performance parameter data of the active load unit is collected based on a time series; The fourth performance parameter data, the fifth performance parameter data and the sixth performance parameter data are packaged to obtain the active charging data.

7. The charging pile safety monitoring system according to claim 3, characterized in that: The monitoring of the current charging data based on the charging pile aging monitoring model is specifically as follows: Inputting the current charging data into the charging pile aging monitoring model; Run the charging pile aging monitoring model to perform fault analysis and life prediction; wherein the fault analysis specifically involves calling the fault knowledge base to perform fault analysis on the active charging data to obtain the active charging pile faults, and the life prediction specifically involves calling the life assessment algorithm to predict the active charging data to obtain the predicted life of the active charging piles.

8. The charging pile safety monitoring system according to claim 7, characterized in that: The generation process of the aging report includes: Obtain the fault of the active charging pile and the predicted life of the active charging pile; An aging report is generated by utilizing natural language technology and a preset aging report template, combining the faults of the active charging piles and the predicted life of the active charging piles.

9. The charging pile safety monitoring system according to claim 8, characterized in that: The receiving and displaying of the aging report specifically includes: The aging report is displayed in a preset display mode by using visualization technology and a preset display template in combination with the aging report.

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