Automobile charging pile electric leakage monitoring system based on data acquisition

Abstract

The invention belongs to the technical field of charging pile management, and particularly relates to an automobile charging pile electric leakage monitoring system based on data acquisition, which comprises an intelligent sensor module, a data processing output module, an electric leakage identification module, an electric leakage protection module and a charging pile supervision end, real-time monitoring and data processing are performed on the charging pile through the intelligent sensor module and the data processing output module, and the electric leakage identification module performs electric leakage identification and early warning based on the monitoring information of the charging pile, so that the safety and efficiency of the charging process of the automobile charging pile are ensured; the electric leakage management risk of the charging piles in each region in the detection period is analyzed through the planning decision output module, so that management personnel can reasonably formulate or adjust a subsequent supervision scheme for each region, safe and stable operation of the charging piles in each region is ensured, the intelligent degree is high, and the efficiency is high. And the supervision difficulty of the charging piles in each area is obviously reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of charging pile management, and in particular to a vehicle charging pile leakage monitoring system based on data collection. Background Art

[0002] Car charging piles are key facilities for providing electric energy for electric vehicles or plug-in hybrid vehicles, playing a role similar to that of traditional gas stations. With the rapid development of the electric vehicle industry, the construction and management of charging piles are becoming increasingly important. However, the leakage problem of charging piles during use not only affects the charging efficiency, but also easily causes safety accidents. At present, it is difficult to fully and real-time monitor the working status of charging piles and realize leakage identification and early warning. It is also impossible to accurately assess the leakage management risk of charging piles in various regions, which is not conducive to the reasonable formulation of subsequent supervision plans for various regions. The degree of intelligence is low and the supervision is difficult. In view of the above technical defects, a solution is now proposed. Summary of the invention

[0003] The purpose of the present invention is to provide a leakage monitoring system for automobile charging piles based on data acquisition, which solves the problems that the prior art is difficult to comprehensively and real-time monitor the working status of the charging piles and realize leakage identification and early warning, and is unable to accurately assess the leakage management risk of charging piles in various areas, has a low degree of intelligence and is difficult to supervise.

[0004] To achieve the above object, the present invention provides the following technical solutions: A vehicle charging pile leakage monitoring system based on data acquisition includes an intelligent sensor module, a data processing output module, a leakage identification module, a leakage protection module and a charging pile supervision terminal; the intelligent sensor module uses a high-precision current sensor and a voltage sensor to monitor the current and voltage of the charging pile in real time, and uses a temperature sensor to monitor the temperature change of the charging pile, and sends the charging pile monitoring data to the data processing output module; The data processing output module receives the charging pile monitoring data transmitted by the intelligent sensor module, and performs preprocessing and feature extraction on the charging pile monitoring data, wherein the preprocessing includes data cleaning and calibration, and the feature extraction extracts feature information including current fluctuation, voltage anomaly and temperature change, and sends the feature extraction information to the leakage identification module; The leakage identification module is based on machine learning technology. By training and learning a large amount of historical data, a leakage identification model for the charging pile is established. The leakage identification model automatically identifies whether there is a leakage phenomenon in the charging pile based on feature extraction information. When the leakage phenomenon is identified, a leakage alarm information is generated and the leakage alarm information is sent to the leakage protection module and the charging pile supervision end; the charging pile supervision end displays the leakage alarm information and issues a corresponding early warning. When the leakage protection module receives the leakage alarm information, it cuts off the power supply of the corresponding charging pile.

[0005] Furthermore, the charging pile supervision end is communicated with the charging pile zoning management module, and the charging pile zoning management module is communicated with the planning decision output module. The charging pile zoning management module obtains the area where charging pile supervision is required, marks the corresponding area as management area i, and i is a natural number greater than 1; all charging piles distributed in management area i are obtained, and all charging piles in management area i are sent to the planning decision output module.

[0006] Furthermore, the planning decision output module is used to set the detection period, analyze the leakage management risk of the charging piles in the management area i during the detection period, generate a high-risk management signal or a low-risk management signal for the management area i through the analysis, and send the high-risk management signal or the low-risk management signal for the management area i to the charging pile supervision end.

[0007] Furthermore, the specific analysis process of the planning decision output module includes: The leakage analysis value of the corresponding charging pile in the management area i is obtained by analysis, the leakage analysis values ​​of all the charging piles in the management area i are averaged to obtain the leakage risk value, and the number of charging piles in the management area i whose leakage analysis value exceeds the preset leakage analysis threshold is marked as the leakage risk table value; The time when the corresponding charging pile in the management area i generates leakage alarm information is obtained and marked as the leakage identification time, and the time when the maintenance personnel complete the inspection and maintenance of the corresponding charging pile is collected and marked as the response end time, and the interval between the response end time and the leakage identification time is marked as the response efficiency value, and the average value of the response efficiency values ​​for all charging piles in the management area i during the detection period is obtained and marked as the response analysis value; The district management decision value is obtained by numerically calculating the response analysis value, the leakage risk value and the leakage risk table value, and a preset district management decision threshold corresponding to it is assigned to the management area i. The district management decision value is numerically compared with the corresponding preset district management decision threshold. If the district management decision value exceeds the preset district management decision threshold, a high-risk management signal for the management area i is generated; if the district management decision value does not exceed the preset district management decision threshold, a low-risk management signal for the management area i is generated.

[0008] Furthermore, the method for obtaining the leakage analysis value is as follows: The total number of leakage alarm information generated by the corresponding charging pile during the detection period is obtained and marked as the leakage alarm value, the time when the leakage protection module cuts off the power supply of the corresponding charging pile is collected and marked as the protection start time, and the time difference between the protection start time and the corresponding leakage identification time is calculated to obtain the leakage protection interval value; All leakage protection interval values ​​corresponding to the corresponding charging piles during the detection period are obtained and their average is calculated to the leakage protection performance value, and the number of leakage protection interval values ​​corresponding to the corresponding charging piles during the detection period that exceed the preset leakage protection interval threshold is marked as leakage protection abnormal value; the leakage analysis value of the corresponding charging pile is obtained by numerically calculating the leakage alarm value, the leakage protection performance value and the leakage protection abnormal value.

[0009] Furthermore, the specific allocation process of allocating the preset area management decision threshold adapted to the management area i is as follows: The monitoring coefficient of management area i is obtained, and several groups of preset monitoring coefficient ranges are set in advance, and each group of preset monitoring coefficient ranges corresponds to a group of preset area management decision thresholds. The monitoring coefficient of management area i is compared with all preset monitoring coefficient ranges one by one, and the preset monitoring coefficient range containing the corresponding monitoring coefficient is marked as a matching range, and the preset area management decision threshold corresponding to the matching range is marked as the preset area management decision threshold adapted for management area i.

[0010] The planning decision output module is communicatively connected to the regional monitoring module. The regional monitoring module monitors the management area i through the monitoring camera, analyzes the monitoring video to obtain the monitoring coefficient of the management area i during the detection period, and sends the monitoring coefficient of the management area i to the planning decision output module.

[0011] Furthermore, the specific analysis process of the regional monitoring module is as follows: The number of personnel distributed in the management area i is obtained and the ratio thereof is calculated to the area of ​​the management area i to obtain the regional personnel distribution value, and the number of charging piles in operation in the management area i is obtained and marked as the charging pile operation occupancy value, and the regional personnel distribution value and the charging pile operation occupancy value are numerically compared with the preset regional personnel distribution threshold and the preset charging pile operation occupancy threshold, respectively. If the regional personnel distribution value or the charging pile operation occupancy value exceeds the corresponding preset threshold, it is judged that the management area i is in a high impact state; The total duration of the high-impact state in the management area i during the detection period is obtained and marked as the high-impact detection value, and the regional personnel coefficient is obtained by averaging all the regional personnel distribution values ​​of the management area i during the detection period, and the regional operation coefficient is obtained by averaging all the charging pile operation occupancy values ​​of the management area i during the detection period; the monitoring coefficient of the management area i is obtained by numerically calculating the high-impact detection value, the regional personnel coefficient and the regional operation coefficient.

[0012] Furthermore, the planning decision output module is communicatively connected to the charging pile evaluation module. The planning decision output module marks the charging piles in the management area i whose leakage analysis values ​​exceed the preset leakage analysis threshold as target charging piles, and sends the target charging piles to the charging pile evaluation module. The charging pile evaluation module performs a usage warning analysis on the corresponding target charging piles, determines whether to generate a usage termination signal for the corresponding target charging pile through the usage warning analysis, and sends the usage termination signal of the corresponding target charging pile to the charging pile supervision end.

[0013] Furthermore, the specific analysis process using early warning analysis is as follows: The installation time of the corresponding target charging pile is collected, and the interval between the installation time and the current time is marked as the installation time. The real-time detection data of various environmental parameters of the environment in which the target charging pile is located is collected. If there is an environmental parameter in which the real-time detection data does not meet the corresponding preset requirements, it is judged that the corresponding target charging pile is in an external factor damage state, and the total time of the corresponding target charging pile in the external factor damage state in the historical stage is marked as the external factor damage value; and collecting the real-time operation load data of the corresponding target charging pile, comparing the real-time operation load data with the preset real-time operation load data threshold, if the real-time operation load data exceeds the preset real-time operation load data threshold, then judging that the corresponding target charging pile is in a high-load operation state, obtaining the total duration of the corresponding target charging pile in the high-load operation state in the historical stage and marking it as the high-load operation value, and marking the charging frequency of the corresponding target charging pile in the historical stage as the charging frequency detection value; The usage warning coefficient is obtained by numerically calculating the installation time, external factor damage value, high-load operation value and charging frequency detection value, and the usage warning coefficient is numerically compared with the preset usage warning coefficient threshold. If the usage warning coefficient exceeds the preset usage warning coefficient threshold, a usage termination signal of the corresponding target charging pile is generated.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. In the present invention, by real-time monitoring of charging piles and leakage identification and early warning, the safety and efficiency of the charging process of automobile charging piles are ensured, and the leakage management risk of charging piles in various regions during the detection period is analyzed through the planning decision output module, which is conducive to the management personnel to reasonably formulate or adjust the subsequent supervision plan for each region, ensure the safe and stable operation of charging piles in each region, and significantly reduce the difficulty of supervision of charging piles in each region; 2. In the present invention, the charging piles whose leakage analysis values ​​in the corresponding area exceed the preset leakage analysis threshold are marked as target charging piles through the planning decision output module, and the charging pile evaluation module performs a usage warning analysis on the corresponding target charging piles to determine whether to generate a usage termination signal for the corresponding target charging pile. When the usage termination signal is generated, the management personnel are reminded to replace the corresponding charging piles in time as needed to ensure the subsequent charging stability and charging safety, further reduce the difficulty of supervision on the charging piles, and have a high degree of intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings; Figure 1 This is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a system block diagram of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Embodiment 1: Figure 1 As shown, the present invention proposes a leakage monitoring system for automobile charging piles based on data acquisition, including an intelligent sensor module, a data processing output module, a leakage identification module, a leakage protection module and a charging pile supervision terminal; the intelligent sensor module adopts a high-precision current sensor and a voltage sensor to monitor the current and voltage of the charging pile in real time, and adopts a temperature sensor to monitor the temperature change of the charging pile, etc., and sends the charging pile monitoring data to the data processing output module; The data processing output module receives the charging pile monitoring data transmitted by the intelligent sensor module, and performs preprocessing and feature extraction on the charging pile monitoring data. The preprocessing includes data cleaning and calibration to eliminate noise and errors, and the feature extraction extracts characteristic information such as current fluctuation, voltage anomaly and temperature change, and sends the feature extraction information to the leakage identification module. The leakage identification module is based on machine learning technology. By training and learning a large amount of historical data, a leakage identification model for the charging pile is established. The leakage identification model automatically identifies whether there is a leakage phenomenon in the charging pile based on feature extraction information. When the leakage phenomenon is identified, it generates leakage alarm information and sends the leakage alarm information to the leakage protection module and the charging pile supervision end; when the leakage protection module receives the leakage alarm information, it cuts off the power supply of the corresponding charging pile.

[0018] The charging pile monitoring end displays the leakage alarm information and issues corresponding warnings, and the charging pile monitoring end provides an intuitive user interface, allowing managers to view the electrical parameters, leakage identification results and alarm information of the charging pile in real time. Managers can also perform parameter settings, alarm threshold adjustment and other operations through the interface. The present invention uses high-precision sensors and big data analysis technology to monitor key parameters such as current, voltage, and temperature of the charging pile in real time, and promptly discovers and warns of abnormal conditions such as leakage to ensure the safety and efficiency of the charging process. It has the advantages of high intelligence, high monitoring accuracy, and fast response speed, and is suitable for the safety monitoring of various types of electric vehicle charging piles.

[0019] In addition, the charging pile supervision end is communicatively connected to the charging pile zoning management module, and the charging pile zoning management module is communicatively connected to the planning decision output module. The charging pile zoning management module obtains the area where charging pile supervision is required, marks the corresponding area as management area i, and i is a natural number greater than 1; obtains all charging piles distributed in management area i, and sends all charging piles in management area i to the planning decision output module and the charging pile supervision end.

[0020] The planning decision output module is used to set the detection period, preferably, the detection period is twenty-five days; analyze the leakage management risk of the charging piles in the management area i during the detection period, and generate a high risk signal or a low risk signal for the management area i through analysis; And sending the high-risk management signal or low-risk management signal of management area i to the charging pile supervision end is conducive to the management personnel to reasonably formulate or adjust the subsequent supervision plan for management area i, strengthen the subsequent supervision of management area i when receiving the high-risk management signal, and ensure the safe and stable operation of charging piles in management area i; the specific analysis process of the planning decision output module is as follows: The total number of leakage alarm information generated by the corresponding charging pile during the detection period is obtained and marked as the leakage alarm value, the time when the leakage protection module cuts off the power supply of the corresponding charging pile is collected and marked as the protection start time, and the time difference between the protection start time and the corresponding leakage identification time is calculated to obtain the leakage protection interval value; Obtain all leakage protection interval values ​​corresponding to the corresponding charging piles during the detection period and calculate their average to the leakage protection performance value, and mark the number of leakage protection interval values ​​corresponding to the corresponding charging piles during the detection period that exceed the preset leakage protection interval threshold as leakage protection abnormal values; The leakage alarm value BKi, the leakage protection performance value ZWi and the leakage protection abnormal value SYi are numerically calculated by the formula YUi=wq×BKi+uy×ZWi+np×SYi to obtain the leakage analysis value YUi of the corresponding charging pile; wherein wq, uy and np are preset weight coefficients with values ​​greater than zero, and the larger the value of the leakage analysis value YUi, the more serious the leakage safety hazard of the corresponding charging pile in the management area i during the detection period; The leakage analysis values ​​of all charging piles in the management area i are averaged to obtain the leakage risk value, and the leakage analysis value YUi is numerically compared with the preset leakage analysis threshold, and the number of charging piles in the management area i whose leakage analysis values ​​exceed the preset leakage analysis threshold is marked as the leakage risk table value; The time when the corresponding charging pile in the management area i generates leakage alarm information is obtained and marked as the leakage identification time, and the time when the maintenance personnel complete the inspection and maintenance of the corresponding charging pile is collected and marked as the response end time, and the interval between the response end time and the leakage identification time is marked as the response efficiency value, and the average value of the response efficiency values ​​for all charging piles in the management area i during the detection period is obtained and marked as the response analysis value; The zone management decision value LXi is obtained by numerically calculating the response analysis value WYi, the leakage risk value FKi and the leakage risk table value XFi through the formula LXi=ew×WYi+fw×FKi+hy×XFi; wherein ew, fw, and hy are preset weight coefficients with values ​​greater than zero, and the larger the value of the zone management decision value LXi, the higher the overall risk of leakage management of charging piles in the management area i during the detection period; Allocating a preset zone management decision threshold value adapted to the management area i, specifically: obtaining the monitoring coefficient TXi of the management area i, setting several groups of preset monitoring coefficient ranges in advance, and each group of preset monitoring coefficient ranges corresponds to a group of preset zone management decision threshold values; wherein the values ​​of all preset zone management decision threshold values ​​are positive numbers, and the larger the value of the corresponding preset monitoring coefficient range is, the smaller the value of the preset zone management decision threshold value matched therewith is; Compare the monitoring coefficient TXi of the management area i with all preset monitoring coefficient ranges one by one, mark the preset monitoring coefficient range containing the corresponding monitoring coefficient TXi as the matching range, and mark the preset area management decision threshold corresponding to the matching range as the preset area management decision threshold adapted to the management area i; The zone management decision value LXi is numerically compared with the corresponding preset zone management decision threshold. If the zone management decision value LXi exceeds the preset zone management decision threshold, it indicates that the overall risk of charging pile leakage management for management area i during the detection period is high, and a high-risk management signal for management area i is generated; if the zone management decision value LXi does not exceed the preset zone management decision threshold, it indicates that the overall risk of charging pile leakage management for management area i during the detection period is low, and a low-risk management signal for management area i is generated.

[0021] Furthermore, the planning decision output module is connected to the regional monitoring module in communication. The regional monitoring module monitors the management area i through the monitoring camera, analyzes the monitoring video to obtain the monitoring coefficient of the management area i during the detection period, and sends the monitoring coefficient of the management area i to the planning decision output module, which can not only effectively monitor the management area i and accurately evaluate its risk control importance, but also provide data support for the analysis process of the planning decision output module to ensure the accuracy of its analysis results; the specific analysis process of the regional monitoring module is as follows: The number of personnel distributed in the management area i is obtained and the ratio thereof is calculated to the area of ​​the management area i to obtain the regional personnel distribution value, and the number of charging piles in operation in the management area i is obtained and marked as the charging pile operation occupancy value, and the regional personnel distribution value and the charging pile operation occupancy value are numerically compared with the preset regional personnel distribution threshold and the preset charging pile operation occupancy threshold, respectively. If the regional personnel distribution value or the charging pile operation occupancy value exceeds the corresponding preset threshold, it is judged that the management area i is in a high impact state; The total duration of the high-impact state in the management area i during the detection period is obtained and marked as the high-impact detection value, and the average of all regional personnel distribution values ​​of the management area i during the detection period is calculated to obtain the regional personnel coefficient, and the average of all charging pile operation occupancy values ​​of the management area i during the detection period is calculated to obtain the regional operation occupancy coefficient; The monitoring coefficient TXi of management area i is obtained by numerically calculating the high-impact detection value YNi, the regional personnel coefficient SPi and the regional occupancy coefficient ZMi through the formula TXi=hu×YNi+sq×SPi+kp×ZMi; among them, hu, sq, kp are preset weight coefficients with values ​​greater than zero, and the larger the value of the monitoring coefficient TXi, the higher the flow of people and the utilization rate of charging piles in management area i during the detection period, and the management area i relatively needs stricter leakage risk control measures.

[0022] Embodiment 2: Figure 2As shown, the difference between this embodiment and the first embodiment is that the planning decision output module is communicatively connected to the charging pile evaluation module, the planning decision output module marks the charging piles whose leakage analysis values ​​in the management area i exceed the preset leakage analysis threshold as target charging piles, and sends the target charging piles to the charging pile evaluation module, the charging pile evaluation module performs a usage warning analysis on the corresponding target charging piles, and determines whether to generate a usage termination signal for the corresponding target charging piles through the usage warning analysis; The use termination signal of the corresponding target charging pile is sent to the charging pile supervision end. When the charging pile supervision end receives the use termination signal, it issues a corresponding warning to remind the management personnel to replace the corresponding charging pile in time as needed to ensure the subsequent charging stability and charging safety, significantly reduce the difficulty of supervision on the charging pile, and have a high degree of intelligence; the specific analysis process of using early warning analysis is as follows: The installation time of the corresponding target charging pile is collected, and the interval between the installation time and the current time is marked as the installation time. In addition, the real-time detection data of various environmental parameters (including environmental parameters such as ambient temperature and ambient humidity) of the environment in which the target charging pile is located is collected. If there are environmental parameters whose real-time detection data do not meet the corresponding preset requirements, which may have an adverse effect on the service life of the charging pile, the corresponding target charging pile is judged to be in an external factor damage state, and the total duration of the corresponding target charging pile in the external factor damage state in the historical stage is marked as the external factor damage value; and collecting the real-time operation load data of the corresponding target charging pile (i.e., the data value of the power load size that the charging pile bears during operation), comparing the real-time operation load data with the preset real-time operation load data threshold; if the real-time operation load data exceeds the preset real-time operation load data threshold, which is likely to have an adverse effect on the service life of the charging pile, then the corresponding target charging pile is judged to be in a high-load operation state, and the total duration of the corresponding target charging pile in the historical stage in the high-load operation state is obtained and marked as the high-load operation value, and the charging frequency of the corresponding target charging pile in the historical stage is marked as the charging frequency detection value; The installation time ZKi, external factor damage value SXi, high-load operation value YPi and charging frequency detection value GSi are numerically calculated by the formula HPi=(ns×ZKi+eg×SXi+my×YPi) / 3+aq×GSi to obtain the use warning coefficient HPi, where ns, eg, my, aq are preset weight coefficients with values ​​greater than zero, and the larger the value of the use warning coefficient HPi, the worse the current life of the corresponding target charging pile is, and the more timely it needs to be replaced; The usage warning coefficient HPi is numerically compared with the preset usage warning coefficient threshold. If the usage warning coefficient HPi exceeds the preset usage warning coefficient threshold, it indicates that the current life condition of the corresponding target charging pile is poor and needs to be replaced in time, then a usage termination signal for the corresponding target charging pile is generated.

[0023] The working principle of the present invention is as follows: when in use, the charging pile is monitored in real time through the intelligent sensor module, the data processing output module pre-processes and extracts features from the monitoring data of the charging pile, the leakage identification model in the leakage identification module identifies leakage based on the feature extraction information, and generates leakage alarm information when the leakage phenomenon is identified, and the leakage protection module cuts off the power supply of the corresponding charging pile when receiving the leakage alarm information, thereby ensuring the safety and efficiency of the charging process, and the leakage management risk of the charging piles in each area during the detection period is analyzed through the planning decision output module, and the subsequent supervision of the corresponding area is strengthened when a high-risk management signal is received, which is conducive to the management personnel to reasonably formulate or adjust the subsequent supervision plan for each area, thereby ensuring the safe and stable operation of the charging piles in each area, with a high degree of intelligence, and significantly reducing the difficulty of supervising the charging piles in each area.

[0024] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A vehicle charging pile leakage monitoring system based on data acquisition, characterized in that: It includes an intelligent sensor module, a data processing output module, a leakage identification module, a leakage protection module and a charging pile monitoring terminal; the intelligent sensor module uses a high-precision current sensor and a voltage sensor to monitor the current and voltage of the charging pile in real time, and uses a temperature sensor to monitor the temperature change of the charging pile, and sends the charging pile monitoring data to the data processing output module; The data processing output module receives the charging pile monitoring data transmitted by the intelligent sensor module, pre-processes and extracts features of the charging pile monitoring data, and sends the feature extraction information to the leakage identification module; The leakage identification module is used to establish a leakage identification model for the charging pile. The leakage identification model automatically identifies whether there is a leakage phenomenon in the charging pile based on feature extraction information. When the leakage phenomenon is identified, a leakage alarm information is generated, and the leakage alarm information is sent to the leakage protection module and the charging pile supervision end; the charging pile supervision end displays the leakage alarm information and issues a corresponding early warning. When the leakage protection module receives the leakage alarm information, it cuts off the power supply of the corresponding charging pile.

2. According to the data acquisition-based vehicle charging pile leakage monitoring system of claim 1, it is characterized in that: The charging pile supervision terminal is communicated with the charging pile partition management module, and the charging pile partition management module is communicated with the planning decision output module. The charging pile partition management module obtains the area where the charging pile supervision is required, and marks the corresponding area as the management area i, where i is a natural number greater than 1; All charging piles distributed in the management area i are obtained, and all charging piles in the management area i are sent to the planning decision output module.

3. According to the data acquisition-based vehicle charging pile leakage monitoring system of claim 2, it is characterized in that: The planning decision output module is used to set the detection period, analyze the leakage management risk of the charging piles in the management area i during the detection period, generate a high-risk management signal or a low-risk management signal for the management area i through analysis, and send the high-risk management signal or the low-risk management signal for the management area i to the charging pile supervision end.

4. The vehicle charging pile leakage monitoring system based on data acquisition according to claim 3 is characterized in that: The specific analysis process of the planning decision output module includes: The leakage analysis value of the corresponding charging pile in the management area i is obtained by analysis, the leakage analysis values ​​of all the charging piles in the management area i are averaged to obtain the leakage risk value, and the number of charging piles in the management area i whose leakage analysis value exceeds the preset leakage analysis threshold is marked as the leakage risk table value; The time when the corresponding charging pile in the management area i generates leakage alarm information is obtained and marked as the leakage identification time, and the time when the maintenance personnel complete the inspection and maintenance of the corresponding charging pile is collected and marked as the response end time, and the interval between the response end time and the leakage identification time is marked as the response efficiency value, and the average value of the response efficiency values ​​for all charging piles in the management area i during the detection period is obtained and marked as the response analysis value; The district management decision value is obtained by numerically calculating the response analysis value, leakage risk value and leakage risk table value, and a preset district management decision threshold corresponding to the management area i is assigned. If the district management decision value exceeds the preset district management decision threshold, a high-risk management signal for the management area i is generated; if the district management decision value does not exceed the preset district management decision threshold, a low-risk management signal for the management area i is generated.

5. The vehicle charging pile leakage monitoring system based on data acquisition according to claim 4 is characterized in that: The specific method for obtaining the leakage analysis value is as follows: The total number of leakage alarm information generated by the corresponding charging pile during the detection period is obtained and marked as the leakage alarm value, the time when the leakage protection module cuts off the power supply of the corresponding charging pile is collected and marked as the protection start time, and the time difference between the protection start time and the corresponding leakage identification time is calculated to obtain the leakage protection interval value; All leakage protection interval values ​​corresponding to the corresponding charging piles during the detection period are obtained and their average is calculated to the leakage protection performance value, and the number of leakage protection interval values ​​corresponding to the corresponding charging piles during the detection period that exceed the preset leakage protection interval threshold is marked as leakage protection abnormal value; the leakage analysis value of the corresponding charging pile is obtained by numerically calculating the leakage alarm value, the leakage protection performance value and the leakage protection abnormal value.

6. The vehicle charging pile leakage monitoring system based on data acquisition according to claim 4 is characterized in that: The specific allocation process of allocating the preset zone management decision threshold value adapted to the management area i is as follows: The monitoring coefficient of management area i is obtained, and several groups of preset monitoring coefficient ranges are set in advance, and each group of preset monitoring coefficient ranges corresponds to a group of preset area management decision thresholds. The preset monitoring coefficient ranges containing the corresponding monitoring coefficients are marked as matching ranges, and the preset area management decision thresholds corresponding to the matching ranges are marked as preset area management decision thresholds adapted to management area i.

7. The vehicle charging pile leakage monitoring system based on data acquisition according to claim 4 is characterized in that: The planning decision output module is communicatively connected to the regional monitoring module. The regional monitoring module monitors the management area i through the monitoring camera, analyzes the monitoring video to obtain the monitoring coefficient of the management area i during the detection period, and sends the monitoring coefficient of the management area i to the planning decision output module.

8. The vehicle charging pile leakage monitoring system based on data acquisition according to claim 7 is characterized in that: The specific analysis process of the regional monitoring module is as follows: The number of personnel distributed in the management area i is obtained and the ratio thereof is calculated to the area of ​​the management area i to obtain the regional personnel distribution value, and the number of charging piles in operation in the management area i is obtained and marked as the charging pile operation occupancy value, and the regional personnel distribution value and the charging pile operation occupancy value are numerically compared with the preset regional personnel distribution threshold and the preset charging pile operation occupancy threshold, respectively. If the regional personnel distribution value or the charging pile operation occupancy value exceeds the corresponding preset threshold, it is judged that the management area i is in a high impact state; The total duration of the high-impact state in the management area i during the detection period is obtained and marked as the high-impact detection value, and the regional personnel coefficient is obtained by averaging all the regional personnel distribution values ​​of the management area i during the detection period, and the regional operation coefficient is obtained by averaging all the charging pile operation occupancy values ​​of the management area i during the detection period; the monitoring coefficient of the management area i is obtained by numerically calculating the high-impact detection value, the regional personnel coefficient and the regional operation coefficient.

9. The vehicle charging pile leakage monitoring system based on data acquisition according to claim 7 is characterized in that: The planning decision output module is communicatively connected to the charging pile evaluation module. The planning decision output module marks the charging piles in the management area i whose leakage analysis values ​​exceed the preset leakage analysis threshold as target charging piles, and sends the target charging piles to the charging pile evaluation module. The charging pile evaluation module performs a usage warning analysis on the corresponding target charging piles, determines whether to generate a usage termination signal for the corresponding target charging pile through the usage warning analysis, and sends the usage termination signal of the corresponding target charging pile to the charging pile supervision end.

10. The vehicle charging pile leakage monitoring system based on data acquisition according to claim 9 is characterized in that: The specific analysis process using early warning analysis is as follows: The usage warning coefficient is obtained by numerically calculating the installation time, external factor damage value, high-load operation value and charging frequency detection value. If the usage warning coefficient exceeds the preset usage warning coefficient threshold, a usage termination signal of the corresponding target charging pile is generated.

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