Power distribution cabinet power performance test system and method

Abstract

The invention belongs to the technical field of power distribution cabinet inspection, and particularly relates to a power distribution cabinet power performance inspection system and method. According to the invention, by monitoring the power, current, temperature and other data of the power distribution cabinet in real time, abnormal electrical units can be found in time, faults can be prevented, stable operation of the power distribution cabinet can be ensured, the current and temperature weight values are comprehensively considered and combined with the power data, and the operation risk of the power distribution cabinet can be evaluated more comprehensively and accurately. Misjudgment caused by single data abnormity is avoided, potential electrical unit faults are found and positioned in advance, the overall fault occurrence probability is reduced, the maintenance cost and downtime are further reduced, an inspection report can be automatically generated, an alarm signal can be sent out, the workload of manual inspection is reduced, and the operation and maintenance efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power distribution cabinet inspection, and in particular relates to a power distribution cabinet power performance inspection system and method. Background Art

[0002] As an important part of the power system, the distribution cabinet is responsible for distributing electrical energy to various electrical equipment to ensure the normal operation of the power system. With the increase in power demand and the complexity of equipment, the operation of the distribution cabinet directly affects the safety and stability of the entire power system. Therefore, it is particularly important to effectively monitor and inspect the power performance of the distribution cabinet.

[0003] With the development of Internet of Things and big data technologies, power performance inspection methods based on real-time monitoring and intelligent analysis have gradually become a research hotspot. However, the current power performance inspection technology still has some shortcomings in application. For example, the lack of accurate identification of the period of fluctuation in the operation of the distribution cabinet leads to unclear inspection focus and inability to effectively focus on the period with greater potential risks. In addition, the existing methods are not perfect in identifying electrical unit anomalies and locating faults. They fail to combine the multi-dimensional data of the electrical unit for comprehensive evaluation, making it difficult to accurately judge the overall operating health of the distribution cabinet. Summary of the invention

[0004] The purpose of the present invention is to provide a method for testing the power performance of a distribution cabinet, which can monitor the operating status of the distribution cabinet in real time, comprehensively analyze multi-dimensional data such as power, current, temperature, etc., and automatically generate an intelligent testing method for testing reports and alarm signals, so as to improve the efficiency, accuracy and automation level of the power performance testing of the distribution cabinet.

[0005] The technical solution adopted by the present invention is as follows: A method for testing power performance of a power distribution cabinet, comprising: Obtain daily operation data of the power distribution cabinet, and obtain daily operation fluctuation period based on the daily operation data; Obtaining power data of each electrical unit during the daily operation fluctuation period, determining whether the power data of each electrical unit meets the first preset condition, and if not, marking it as an abnormal electrical unit; Acquire current data and corresponding temperature data of each abnormal electrical unit, and acquire current weight value and temperature weight value of the corresponding abnormal electrical unit according to the current data and the corresponding temperature data; Obtain the operation risk value of the power distribution cabinet based on the current weight value, temperature weight value, and electrical unit power data; Determine whether the operation risk value meets the preset value. If not, the distribution cabinet is judged to be abnormal, an inspection report is generated and an alarm signal is issued.

[0006] In a preferred solution, the step of obtaining daily operation data of the power distribution cabinet and obtaining the daily operation fluctuation period according to the daily operation data includes: Build assessment periods; Obtain daily operation data of the power distribution cabinet within the construction evaluation period, and obtain corresponding multiple electrical daily operation values ​​from the daily operation data; Obtain the electrical daily operation assessment interval value; Determine whether each electrical daily operation value is within the electrical daily operation evaluation interval value; If the electrical daily operation value is within the electrical daily operation evaluation interval, the daily operation of the power distribution cabinet is determined to be stable; If the daily electrical operation value is not within the daily electrical operation evaluation interval and is greater than the upper limit of the daily electrical operation evaluation interval, the daily operation of the power distribution cabinet is determined to be highly abnormal; If the electrical daily operation value is not within the electrical daily operation evaluation interval value and is less than the lower limit of the electrical daily operation evaluation interval value, the daily operation of the distribution cabinet is judged to be low abnormal; Obtain multiple abnormal time periods corresponding to high abnormality and low abnormality of daily operation of the power distribution cabinet; Obtain the total number of abnormal times during each abnormal period when the daily operation of the distribution cabinet is highly abnormal or less abnormal; Get the number of abnormal thresholds for a period; Determine whether the total number of abnormalities in a time period exceeds the abnormality threshold number in the time period; If the total number of abnormalities in a time period exceeds the threshold number of abnormalities in a time period, it is determined to be a daily operation fluctuation period of the distribution cabinet; If the total number of abnormalities in a time period does not exceed the abnormality threshold number in the time period, it is determined that the distribution cabinet is operating normally on a daily basis.

[0007] In a preferred embodiment, the step of constructing an evaluation period includes: Obtain daily operation data of the power distribution cabinet; Obtain daily standard operating range data of the power distribution cabinet; Determine whether the daily operation data of the power distribution cabinet exceeds the daily standard operation range data of the power distribution cabinet; If the daily operation data of the distribution cabinet exceeds the daily standard operation interval data of the distribution cabinet, the time when the daily operation data of the distribution cabinet exceeds the daily standard operation interval data of the distribution cabinet is marked as the first start time; Obtain the daily operation data of the distribution cabinet that exceeds the daily standard operation range data of the distribution cabinet, and mark it as exceeded data; Obtain the corresponding evaluation duration based on the exceeded data; Get the first end time based on the evaluation duration and the first start time; An evaluation period is constructed based on a first start time and a first end time.

[0008] In a preferred solution, the step of obtaining multiple abnormal time periods corresponding to high abnormality and low abnormality of daily operation of the power distribution cabinet includes: The time when the daily operation of the power distribution cabinet is judged to be highly abnormal or less abnormal is marked as the abnormal time point; Get the time interval between every two adjacent abnormal time points and mark it as the time interval; Get the standard time interval; Determine whether the abnormal time interval is greater than the standard time interval. If the abnormal time interval is greater than the standard time interval, mark the start time of the abnormal time interval as the end time of the daily operation fluctuation period, and mark the end time of the abnormal time interval as the start time of the daily operation fluctuation period; Each daily operation fluctuation period is obtained according to the start time of the adjacent daily operation fluctuation period and the end time of the daily operation fluctuation period.

[0009] In a preferred embodiment, the step of obtaining the power data of each electrical unit during the daily operation fluctuation period, determining whether the power data of each electrical unit meets the first preset condition, and if not, marking it as an abnormal electrical unit, includes: Obtain power data for each electrical unit during daily operating fluctuation periods; Obtaining corresponding electrical unit power values ​​according to electrical unit power data; Get the power evaluation interval value of the electrical unit; Determine whether the electrical unit power value is within the unit power evaluation interval value; If the electrical unit power value is within the unit power evaluation interval, the electrical unit is judged to be normal; If the electrical unit power value is not within the unit power evaluation interval value and is greater than the upper limit value of the unit power evaluation interval value, the electrical unit power is determined to be high and is marked as an abnormal electrical unit; If the electric unit power value is not within the unit power evaluation interval value and is less than the lower limit value of the unit power evaluation interval value, the power of the electric unit is determined to be low and is marked as an abnormal electric unit.

[0010] In a preferred embodiment, the step of obtaining the current data and the corresponding temperature data of each abnormal electrical unit, and obtaining the current weight value and the temperature weight value of the corresponding abnormal electrical unit according to the current data and the corresponding temperature data, respectively, comprises: Obtaining current data of each abnormal electrical unit during an evaluation period; Acquire multiple corresponding current values ​​according to the current data; Get the current evaluation function; Inputting a plurality of current values ​​into a current evaluation function and marking an output result as a current evaluation value; Acquire corresponding temperature data according to the current data of each abnormal electrical unit; Acquire corresponding multiple temperature values ​​according to the temperature data; Get the temperature evaluation function; Input a plurality of temperature values ​​into a temperature evaluation function, and mark the output result as a temperature evaluation value; The corresponding current weight value and temperature weight value are obtained according to the current evaluation value and the temperature evaluation value respectively.

[0011] In a preferred embodiment, the step of respectively obtaining the corresponding current weight value and temperature weight value according to the current evaluation value and the temperature evaluation value comprises: Obtaining a current weight table, wherein the current weight table includes a plurality of current evaluation interval values ​​and a current weight value corresponding to each current evaluation interval value; Obtaining a corresponding target current evaluation interval value according to the current evaluation value; Obtain the corresponding current weight value from the current weight table according to the target current evaluation interval value; Obtaining a temperature weight table, wherein the temperature weight table includes a plurality of temperature evaluation interval values ​​and a temperature weight value corresponding to each temperature evaluation interval value; Obtain the corresponding target temperature evaluation interval value according to the temperature evaluation value; The corresponding temperature weight value is obtained from the temperature weight table according to the target temperature evaluation interval value.

[0012] In a preferred embodiment, the step of obtaining the operation risk value of the power distribution cabinet according to the current weight value, the temperature weight value, and the electrical unit power data includes: Obtaining corresponding power factor according to electrical unit power data; Get the risk function; The current weight value, the temperature weight value, and the power factor are input into the risk function, and the output result is marked as the operation risk value.

[0013] The present invention also provides a power distribution cabinet power performance testing system, which is used for the above-mentioned power distribution cabinet power performance testing method, comprising: Fluctuation module, used to obtain daily operation data of the power distribution cabinet, and obtain daily operation fluctuation period according to the daily operation data; An abnormal module, used to obtain the power data of each electrical unit during the daily operation fluctuation period, determine whether the power data of each electrical unit meets the first preset condition, and if not, mark it as an abnormal electrical unit; A weight module is used to obtain the current data and the corresponding temperature data of each abnormal electrical unit, and obtain the current weight value and the temperature weight value of the corresponding abnormal electrical unit according to the current data and the corresponding temperature data; The risk module is used to obtain the operation risk value of the distribution cabinet according to the current weight value, the temperature weight value, and the electrical unit power data; The judgment module is used to judge whether the operation risk value meets the preset value. If not, the distribution cabinet is judged to be abnormal, an inspection report is generated and an alarm signal is issued.

[0014] And, a power distribution cabinet power performance test terminal, comprising: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the power performance inspection method of the power distribution cabinet.

[0015] The technical effects achieved by the present invention are: The present invention can timely discover abnormal electrical units and prevent failures from occurring by real-time monitoring of data such as power, current, and temperature of the distribution cabinet, thereby ensuring stable operation of the distribution cabinet. By comprehensively considering the current and temperature weight values ​​and combining them with power data, the operating risks of the distribution cabinet can be evaluated more comprehensively and accurately, avoiding misjudgments caused by single data anomalies, discovering and locating potential electrical unit failures in advance, reducing the probability of overall failures, and thus reducing maintenance costs and downtime. Inspection reports can be automatically generated and alarm signals can be issued, thereby reducing the workload of manual inspections and improving operation and maintenance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of the method provided by the present invention; Figure 2 It is a system module diagram provided by the present invention. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0018] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" that appears in different places in this specification does not refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0020] Secondly, the present invention is described in detail in conjunction with schematic diagrams. When describing the embodiments of the present invention in detail, for the convenience of explanation, the schematic diagrams are only examples and should not limit the scope of protection of the present invention.

[0021] Please see attached Figure 1 As shown, a method for testing the power performance of a distribution cabinet is provided, comprising: S1. Obtain daily operation data of the power distribution cabinet, and obtain daily operation fluctuation period according to the daily operation data; S2, obtaining power data of each electrical unit during the daily operation fluctuation period, determining whether the power data of each electrical unit meets the first preset condition, and if not, marking it as an abnormal electrical unit; S3, obtaining current data and corresponding temperature data of each abnormal electrical unit, and obtaining a current weight value and a temperature weight value of the corresponding abnormal electrical unit according to the current data and the corresponding temperature data; S4. Obtaining the operation risk value of the power distribution cabinet according to the current weight value, the temperature weight value, and the electrical unit power data; S5. Determine whether the operation risk value meets the preset value. If not, determine that the power distribution cabinet is abnormal, generate an inspection report and send out an alarm signal.

[0022] As in the above steps S1 to S5, by obtaining the daily operation data of the distribution cabinet, the power fluctuations of the electrical system in different time periods are found, and the key fluctuation periods are identified to ensure that the inspection focus is on the period with greater potential risks. During the fluctuation period, the power data of the electrical units are checked one by one to see if they meet the preset standards. When the power of a unit is abnormal, it is marked as an abnormal unit, and the current and temperature data of the unit are further collected. By obtaining the current and temperature weights of the abnormal unit, the operation risk value of the distribution cabinet is calculated by combining the current weight, temperature weight and power data of the electrical unit to quantify the overall health status of the distribution cabinet. When the operation risk value exceeds the preset threshold, it is judged that the distribution cabinet may have In the event of a potential fault, it generates an inspection report and sends out an alarm signal to remind maintenance personnel to carry out maintenance in a timely manner. By real-time monitoring of the power, current, temperature and other data of the distribution cabinet, it can promptly detect abnormal electrical units, prevent faults from occurring, and ensure the stable operation of the distribution cabinet. By comprehensively considering the current and temperature weight values ​​and combining them with the power data, it can more comprehensively and accurately assess the operating risks of the distribution cabinet, avoid misjudgments caused by single data anomalies, detect and locate potential electrical unit failures in advance, reduce the probability of overall failures, and thus reduce maintenance costs and downtime. It can automatically generate inspection reports and send out alarm signals, reducing the workload of manual inspections and improving operation and maintenance efficiency.

[0023] In a preferred embodiment, the step of obtaining daily operation data of the power distribution cabinet and obtaining the daily operation fluctuation period according to the daily operation data includes: S101, constructing an evaluation period; S102, obtaining daily operation data of the power distribution cabinet within the construction evaluation period, and obtaining corresponding multiple electrical daily operation values ​​from the daily operation data; S103, obtaining the electrical daily operation evaluation interval value; S104, judging whether each electrical daily operation value is within the electrical daily operation evaluation interval value; If the electrical daily operation value is within the electrical daily operation evaluation interval, the daily operation of the power distribution cabinet is determined to be stable; If the daily electrical operation value is not within the daily electrical operation evaluation interval and is greater than the upper limit of the daily electrical operation evaluation interval, the daily operation of the power distribution cabinet is determined to be highly abnormal; If the electrical daily operation value is not within the electrical daily operation evaluation interval value and is less than the lower limit of the electrical daily operation evaluation interval value, the daily operation of the distribution cabinet is judged to be low abnormal; S105, obtaining multiple abnormal time periods corresponding to high abnormality and low abnormality of daily operation of the power distribution cabinet; S106, obtaining the total number of abnormal times during each abnormal period when the daily operation of the power distribution cabinet is highly abnormal and low abnormal; S107, obtaining the number of abnormal thresholds for a time period; S108, determining whether the total number of abnormal times in a time period exceeds the abnormal times threshold for the time period; If the total number of abnormalities in a time period exceeds the threshold number of abnormalities in a time period, it is determined to be a daily operation fluctuation period of the distribution cabinet; If the total number of abnormalities in a time period does not exceed the abnormality threshold number in the time period, it is determined that the distribution cabinet is operating normally on a daily basis.

[0024] As in the above steps S101 to S108, first, a time period is defined as an evaluation period for monitoring the daily operation of the distribution cabinet. This time period can be dynamically adjusted according to the actual operation characteristics of the distribution cabinet to ensure the rationality of the evaluation period. During the evaluation period, the operation data of each electrical unit of the distribution cabinet are collected to obtain multiple daily electrical operation values. These values ​​include key parameters such as current, voltage, and power. Based on historical data or design specifications, the normal operation evaluation interval of the electrical unit is determined. The upper and lower limits of this interval are used to determine whether the operation of the electrical unit is stable to ensure that each unit works within the specified range. It is determined one by one whether the daily operation value of each electrical unit is within the evaluation interval. If the operation value is within the interval, it indicates that the distribution cabinet is operating stably; if it exceeds the interval, it is classified according to the direction of the excess and is determined as "high abnormality" or "low abnormality" for subsequent further analysis. Statistics are taken for all time periods determined as high abnormality or low abnormality, and the number of occurrences of each abnormal time period is recorded to evaluate the frequency of abnormality. A threshold number is set to determine whether the time period is within the evaluation interval. Whether the total number of abnormal periods in the evaluation period exceeds the threshold, if it exceeds the threshold number, it is determined to be the daily operation fluctuation period of the distribution cabinet, indicating that the operation of the distribution cabinet in this period is relatively unstable, otherwise, it is considered that the daily operation of the distribution cabinet is normal. Through real-time monitoring of daily operation data, it is possible to accurately judge the high or low abnormalities in the operation of the distribution cabinet, avoiding the misjudgment caused by relying only on single-time data. At the same time, counting the number of abnormal periods can identify the fluctuation period that really needs attention. By introducing the period abnormality threshold, it is avoided that sporadic or short-term abnormalities trigger alarms. Only when the abnormalities accumulate to a certain extent, it is determined to be a fluctuation period, reducing the occurrence of false alarms. By constructing a dynamic evaluation period, it can quickly respond to changes in the operation of the distribution cabinet, ensuring that potential risks can be discovered in time during daily operation and preventing the occurrence of faults. By continuously monitoring and evaluating the operating status of the distribution cabinet, high and low abnormalities can be discovered in time, ensuring that the distribution cabinet is always operating in the best working state, and improving the overall stability and reliability of the power system.

[0025] In a preferred embodiment, the step of constructing the evaluation period includes: S1011. Obtain daily operation data of the power distribution cabinet; S1012. Obtain daily standard operation range data of the power distribution cabinet; S1013, determining whether the daily operation data of the power distribution cabinet exceeds the daily standard operation range data of the power distribution cabinet; If the daily operation data of the distribution cabinet exceeds the daily standard operation interval data of the distribution cabinet, the time when the daily operation data of the distribution cabinet exceeds the daily standard operation interval data of the distribution cabinet is marked as the first start time; S1014, obtaining daily operation data of the distribution cabinet that exceeds the daily standard operation interval data of the distribution cabinet, and marking it as exceeding data; S1015, obtaining corresponding evaluation duration according to the exceeded data; S1016. Obtain a first end time according to the evaluation duration and the first start time; S1017: Construct an evaluation period according to the first start time and the first end time.

[0026] As in the above steps S1011 to S1017, first, obtain the daily operation data of the distribution cabinet and the corresponding daily standard operation range data. The daily operation data includes various electrical parameters of the distribution cabinet under normal conditions (such as current, voltage, power, etc.), and the standard operation range represents the upper and lower limits of these parameters under normal conditions. Compare the actual daily operation data of the distribution cabinet with the standard operation range. If the operation data at a certain moment exceeds the standard range (whether it is higher than the upper limit or lower than the lower limit), record this time point as the start time of the abnormal event, mark it as the first start time, and continuously monitor and record the data that exceeds the standard range. These are marked as exceeded data. These data reflect the operation status of the distribution cabinet under abnormal conditions and are used for subsequent evaluation. According to the exceeded data, calculate the abnormality of this section. The duration of the normal operating state is called the evaluation duration, which is used to determine the duration of the abnormal state. According to the evaluation duration and the first start time, the end time of the abnormal operating state is calculated and marked as the first end time, and the time span of the abnormal event is determined. Finally, the evaluation period is constructed according to the first start time and the first end time. The evaluation period represents the specific time range when the distribution cabinet is in the abnormal operating state, which is convenient for subsequent fault analysis and processing. By recording the first start time and the first end time, the specific time period when the distribution cabinet has abnormalities during daily operation can be accurately identified, which is helpful for fault location and problem troubleshooting. By continuously monitoring the comparison of operating data with the standard operating range, it is possible to record and construct the evaluation period in real time when the abnormality occurs, ensuring that the abnormal state of the distribution cabinet can be identified in time.

[0027] In a preferred embodiment, the step of obtaining multiple abnormal time periods corresponding to high abnormality and low abnormality of daily operation of the power distribution cabinet includes: S1051, marking the time when the daily operation of the power distribution cabinet is determined to be highly abnormal or less abnormal as the abnormal time point; S1052, obtaining the time interval between every two adjacent abnormal time points, and marking it as the time interval; S1053, obtaining a standard time interval; S1054, determining whether the abnormal time interval is greater than the standard time interval, if the abnormal time interval is greater than the standard time interval, marking the start time of the abnormal time interval as the end time of the daily operation fluctuation period, and marking the end time of the abnormal time interval as the start time of the daily operation fluctuation period; S1055. Obtain each daily operation fluctuation period according to the start time of adjacent daily operation fluctuation periods and the end time of the daily operation fluctuation periods.

[0028] The start time of the first abnormal time interval is the start time of the daily operation fluctuation period, and the end time of the last abnormal time interval is the end time of the daily operation fluctuation period.

[0029] As in the above steps S1051 to S1055, when the daily operation data of the distribution cabinet is judged to be highly abnormal or low abnormal, the specific time point at which the abnormality occurs is recorded and marked as the abnormal time point. These time points are used to identify the occurrence and duration of the abnormality. The time difference between each two adjacent abnormal time points is calculated and marked as the time interval, which is used to judge the continuity of the abnormality. A standard time interval is pre-set, that is, the standard for measuring the continuity of the abnormal state. If the interval between two adjacent abnormal time points is less than the standard time interval, they are considered to belong to the same fluctuation period; if the time interval is greater than the standard time interval, the abnormal event is considered to be scattered. The abnormal time period is divided by comparing the size of each abnormal time interval with the standard time interval. If the time interval is greater than the standard time interval, the current abnormal time point is The end time of the fluctuation period is taken as the end time of the fluctuation period, and the next abnormal time point is taken as the start time of the next fluctuation period. According to the time interval between each abnormal time point, a series of fluctuation periods are constructed. The time mark of the first abnormal time point is taken as the start time of the first fluctuation period, and the time mark of the last abnormal time point is taken as the end time of the last fluctuation period. Ensure that each abnormal fluctuation period is accurately marked. By marking the time interval between each two adjacent abnormal time points, the daily operation fluctuation period of the distribution cabinet can be accurately divided to avoid misjudgment caused by the dispersion of abnormal time points, thereby improving the ability to identify abnormal conditions. By accurately marking the start time and end time of each fluctuation period, the operation and maintenance personnel can clearly understand the operating status of the distribution cabinet in a specific time period, which is helpful for targeted abnormal processing and improving operation and maintenance efficiency.

[0030] In a preferred embodiment, the step of obtaining the power data of each electrical unit during the daily operation fluctuation period, determining whether the power data of each electrical unit meets the first preset condition, and if not, marking it as an abnormal electrical unit, includes: S201, obtaining power data of each electrical unit during the daily operation fluctuation period; S202, acquiring a corresponding electrical unit power value according to the electrical unit power data; S203, obtaining the power evaluation interval value of the electrical unit; S204, determining whether the electrical unit power value is within the unit power evaluation interval value; If the electrical unit power value is within the unit power evaluation interval, the electrical unit is judged to be normal; If the electrical unit power value is not within the unit power evaluation interval value and is greater than the upper limit value of the unit power evaluation interval value, the electrical unit power is determined to be high and is marked as an abnormal electrical unit; If the electric unit power value is not within the unit power evaluation interval value and is less than the lower limit value of the unit power evaluation interval value, the power of the electric unit is determined to be low and is marked as an abnormal electric unit.

[0031] As in the above steps S201 to S204, first, the power data of each electrical unit is collected from the daily operation fluctuation period. The daily operation fluctuation period indicates the time period when there are obvious fluctuations or abnormalities in the distribution cabinet. Acquiring the data in this time period helps to accurately judge the abnormal situation of the electrical unit. The specific power value of each electrical unit is extracted from the acquired power data. These power values ​​represent the working status of the electrical unit at a specific moment. When each electrical unit is operating normally, its power value should be within a reasonable range, which is called the unit power evaluation interval value. A reasonable power evaluation interval value is set for each electrical unit, which is usually set based on historical operation data and equipment operation specifications, and the actual power value of each electrical unit is compared with its corresponding The evaluation interval is used for comparison. If the power value is within the evaluation interval, it means that the electrical unit is working normally. If the power value is higher than the upper limit of the evaluation interval, it means that the power of the unit has increased abnormally, and it is marked as an abnormal electrical unit with high power. If the power value is lower than the lower limit of the evaluation interval, it means that the power of the unit has decreased abnormally, and it is marked as an abnormal electrical unit with low power. By performing detailed analysis on the power data of each electrical unit, the working status of each unit in the distribution cabinet can be monitored in real time, and electrical units with abnormal power can be accurately identified, reducing the complexity of overall troubleshooting. Introducing the unit power evaluation interval value as a judgment standard can help deal with short-term fluctuations or load changes in operation, reduce the occurrence of false alarms, and ensure that alarms are issued only when real abnormalities occur.

[0032] In a preferred embodiment, the step of obtaining the current data and the corresponding temperature data of each abnormal electrical unit, and obtaining the current weight value and the temperature weight value of the corresponding abnormal electrical unit according to the current data and the corresponding temperature data, respectively, comprises: S301, obtaining current data of each abnormal electrical unit during an evaluation period; S302, acquiring corresponding multiple current values ​​according to the current data; S303, obtaining a current evaluation function; S304, inputting a plurality of current values ​​into a current evaluation function, and marking an output result as a current evaluation value; S305, acquiring corresponding temperature data according to the current data of each abnormal electrical unit; S306, acquiring corresponding multiple temperature values ​​according to the temperature data; S307, obtaining a temperature evaluation function; S308, inputting a plurality of temperature values ​​into a temperature evaluation function, and marking an output result as a temperature evaluation value; S309 , obtaining corresponding current weight values ​​and temperature weight values ​​according to the current evaluation value and the temperature evaluation value respectively.

[0033] As in the above steps S301 to S309, first, the current data of each abnormal electrical unit is collected during the evaluation period. The evaluation period is the period during which the distribution cabinet is determined to be abnormal through the previous steps. It is necessary to further analyze the specific performance of the abnormal unit during this period, and extract multiple current values ​​from the acquired current data. These data represent the current changes of the abnormal electrical unit during the evaluation period. A current evaluation function is used. The current evaluation function is , where P represents the current evaluation value, i represents the number of multiple current values, where i=1, 2, 3…n, It is represented as the i-th current value. Multiple current values ​​are input into the current evaluation function. The output result is the current evaluation value, which is used to measure the current state of the electrical unit. At the same time, the temperature data of the abnormal electrical unit during the evaluation period is also collected. The temperature data is closely related to the current data. Excessive temperature is usually the result of abnormal current. Multiple temperature values ​​are extracted from the temperature data. These values ​​reflect the temperature changes of the abnormal electrical unit. Similar to the current evaluation, the temperature evaluation function is used to calculate the temperature state. The temperature evaluation function is , where W represents the temperature evaluation value, and f represents the number of multiple temperature values, where f=1, 2, 3…d, Represented as the f+1th temperature value, It is represented as the fth temperature value. Multiple temperature values ​​will be input into the temperature evaluation function, and the temperature evaluation value will be obtained through function calculation. Finally, the current weight value and the temperature weight value are calculated respectively according to the current evaluation value and the temperature evaluation value. These weight values ​​are used to further analyze the operation risk of the abnormal electrical unit. Through the comprehensive analysis of the current data and the temperature data, the state of the abnormal electrical unit can be more accurately identified. Current and temperature are two important indicators of abnormal electrical equipment. By combining the data of the two for analysis, it can effectively reduce misjudgment, improve the accuracy of fault detection, avoid false alarms under a single indicator, and improve the reliability of the detection system.

[0034] In a preferred embodiment, the step of respectively acquiring the corresponding current weight value and temperature weight value according to the current evaluation value and the temperature evaluation value comprises: S3091, obtaining a current weight table, wherein the current weight table includes a plurality of current evaluation interval values ​​and a current weight value corresponding to each current evaluation interval value; S3092, obtaining a corresponding target current evaluation interval value according to the current evaluation value; S3093, obtaining a corresponding current weight value from a current weight table according to the target current evaluation interval value; S3094, obtaining a temperature weight table, wherein the temperature weight table includes a plurality of temperature evaluation interval values ​​and a temperature weight value corresponding to each temperature evaluation interval value; S3095, obtaining a corresponding target temperature evaluation interval value according to the temperature evaluation value; S3096. Obtain a corresponding temperature weight value from the temperature weight table according to the target temperature evaluation interval value.

[0035] As in the above steps S3091 to S3096, first, a pre-established current weight table is called, which records the correspondence between different current evaluation interval values ​​and current weight values. The weight table is established based on the statistical analysis of the current variation range under normal operation of the equipment, covering the interval range corresponding to different current evaluation values. According to the current evaluation value calculated in the previous step, the interval value corresponding to the evaluation value is searched in the current weight table. Each current evaluation interval value represents a current range, and the evaluation value will be matched to a specific interval. Once the interval in which the current evaluation value is located is determined, the current weight value corresponding to the interval will be extracted from the current weight table. The current weight value is used to characterize the weight of the current state of the abnormal electrical unit in the overall evaluation, reflecting its importance relative to other units. Similar to the current weight table, the temperature weight table will also be called. The temperature weight table records the correspondence between different temperature evaluation interval values ​​and temperature weight values. The temperature weight value is also based on the equipment Analysis of temperature historical data to ensure that the weight setting is reasonable and accurate. According to the temperature evaluation value in the previous step, find the interval value corresponding to the evaluation value in the temperature weight table. The setting of the temperature evaluation interval value is similar to that of the current, representing the operating status of the equipment under different temperature ranges. The temperature weight value corresponding to the target temperature evaluation interval value is extracted from the temperature weight table. The temperature weight value also plays an important role in the comprehensive evaluation. It is used to balance the joint influence of current and temperature on the state of the electrical unit. By corresponding the current and temperature data to the preset evaluation interval and evaluating it through the weight value, the operating status of the electrical unit can be more accurately reflected. The setting of the weight value ensures that the influence of current and temperature changes under different conditions on abnormal conditions can be reasonably reflected. Through the preset weight table, data matching and weight calculation can be automatically performed, which improves the efficiency of fault detection. Without manual intervention, the status evaluation of the abnormal unit can be completed quickly, which significantly improves the real-time performance of equipment monitoring.

[0036] In a preferred embodiment, the step of obtaining the operation risk value of the power distribution cabinet according to the current weight value, the temperature weight value, and the electrical unit power data includes: S401, obtaining a corresponding power factor according to the electrical unit power data; S402, obtaining a risk function; S403: input the current weight value, the temperature weight value and the power factor into the risk function, and mark the output result as the operation risk value.

[0037] As in the above steps S401 to S403, first, according to the power data of each electrical unit, the corresponding power factor is calculated. The power factor is a parameter used to measure the power output efficiency of the equipment, reflecting the ratio between the actual power and the apparent power. The lower the power factor, the worse the energy efficiency of the equipment, which means that there is a potential electrical problem. A risk function is preset, and the risk function is F=ψ*α*β, where F represents the operation risk value, ψ represents the power factor, α represents the current weight value, and β represents the temperature weight value. The current weight value, temperature weight value and power factor of the current electrical unit calculated in the previous step are used as input and substituted into the risk function. In the risk function, the current weight value and the temperature weight value reflect the abnormal degree of current and temperature during equipment operation, while the power factor is a key indicator of equipment energy efficiency. The risk function calculates the equipment's operating risk value based on the input current weight value, temperature weight value and power factor. By combining the three key parameters of current, temperature and power factor, the operating status of the electrical unit can be more comprehensively evaluated. Compared with using only a single parameter, the combination of multiple parameters makes the equipment's risk value calculation more accurate and reliable. By calculating the equipment's operating risk value, the calculation of the operating risk value can help operation and maintenance personnel discover potential problems in advance, so as to take corresponding preventive measures and avoid serious equipment failures.

[0038] Please see attached Figure 2 As shown, the present invention also provides a power distribution cabinet power performance testing system, which is used for the above-mentioned power distribution cabinet power performance testing method, comprising: Fluctuation module, used to obtain daily operation data of the power distribution cabinet, and obtain daily operation fluctuation period according to the daily operation data; An abnormal module, used to obtain the power data of each electrical unit during the daily operation fluctuation period, determine whether the power data of each electrical unit meets the first preset condition, and if not, mark it as an abnormal electrical unit; A weight module is used to obtain the current data and the corresponding temperature data of each abnormal electrical unit, and obtain the current weight value and the temperature weight value of the corresponding abnormal electrical unit according to the current data and the corresponding temperature data; The risk module is used to obtain the operation risk value of the distribution cabinet according to the current weight value, the temperature weight value, and the electrical unit power data; The judgment module is used to judge whether the operation risk value meets the preset value. If not, the distribution cabinet is judged to be abnormal, an inspection report is generated and an alarm signal is issued.

[0039] As mentioned above, the fluctuation module is responsible for extracting information from the daily operation data of the distribution cabinet. By constructing an evaluation period, it identifies the operation stability of the distribution cabinet in different periods. If the operation data exceeds the preset normal range, it is identified as a fluctuation period, which means that the distribution cabinet may have an operation abnormality. The abnormal module obtains the power data of each electrical unit during the fluctuation period, and compares it with the preset power interval value to determine whether there is a power abnormality. If the power data is higher or lower than the normal interval, the electrical unit is marked as an abnormal unit and the relevant data is recorded. The weight module further analyzes the current and temperature data of each abnormal electrical unit. Through the current weight table and the temperature weight table, the module converts the current and temperature data into weight values. The weight value reflects the degree of abnormality of the current and temperature, which provides an important reference for subsequent risk assessment. The risk module calculates the operation risk value of the distribution cabinet by combining the current weight value, the temperature weight value and the power data of the electrical unit. The module uses a pre-defined risk function and integrates multiple parameters to output a value representing the current risk level of the distribution cabinet. The operation risk value is used to judge Whether there is a potential fault risk in the power distribution cabinet at present, the judgment module judges whether the operating status of the power distribution cabinet meets the preset standard according to the operating risk value. If the operating risk value exceeds the standard range, it is judged that the power distribution cabinet is abnormal, and a detailed inspection report is generated. At the same time, an alarm signal is issued to notify the relevant operation and maintenance personnel to deal with it in time. Through the collaborative work of multiple modules, the power distribution cabinet can be fully tested. Whether it is operation fluctuations, electrical unit power, or current and temperature abnormalities, the system can perform accurate detection and analysis to ensure that the various power performances of the power distribution cabinet are within the normal range. Through the abnormal module and weight module, the system can quickly identify the power, current and temperature abnormalities of the electrical unit, and further refine the analysis through the weight value. This multi-level abnormal identification mechanism can help the system determine the problem more accurately and improve the efficiency of fault location. Through real-time monitoring of the operating risk value, the system can help the operation and maintenance personnel discover potential problems in advance and intervene early, which not only improves the operating safety of the distribution cabinet, but also extends the service life of the equipment and reduces the maintenance and replacement costs.

[0040] And, a power distribution cabinet power performance test terminal, comprising: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the power performance inspection method of the power distribution cabinet.

[0041] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. A method for testing the power performance of a distribution cabinet, characterized in that: include: Obtain daily operation data of the power distribution cabinet, and obtain daily operation fluctuation period based on the daily operation data; Obtaining power data of each electrical unit during the daily operation fluctuation period, determining whether the power data of each electrical unit meets the first preset condition, and if not, marking it as an abnormal electrical unit; Acquire current data and corresponding temperature data of each abnormal electrical unit, and acquire current weight value and temperature weight value of the corresponding abnormal electrical unit according to the current data and the corresponding temperature data; Obtain the operation risk value of the power distribution cabinet based on the current weight value, temperature weight value, and electrical unit power data; Determine whether the operation risk value meets the preset value. If not, the distribution cabinet is judged to be abnormal, an inspection report is generated and an alarm signal is issued.

2. The power performance testing method of a power distribution cabinet according to claim 1, characterized in that: The step of obtaining daily operation data of the power distribution cabinet and obtaining the daily operation fluctuation period according to the daily operation data includes: Build assessment periods; Obtain daily operation data of the power distribution cabinet within the construction evaluation period, and obtain corresponding multiple electrical daily operation values ​​from the daily operation data; Obtain the electrical daily operation assessment interval value; Determine whether each electrical daily operation value is within the electrical daily operation evaluation interval value; If the electrical daily operation value is within the electrical daily operation evaluation interval, the daily operation of the power distribution cabinet is determined to be stable; If the daily electrical operation value is not within the daily electrical operation evaluation interval and is greater than the upper limit of the daily electrical operation evaluation interval, the daily operation of the power distribution cabinet is determined to be highly abnormal; If the electrical daily operation value is not within the electrical daily operation evaluation interval value and is less than the lower limit of the electrical daily operation evaluation interval value, the daily operation of the distribution cabinet is judged to be low abnormal; Obtain multiple abnormal time periods corresponding to high abnormality and low abnormality of daily operation of the power distribution cabinet; Obtain the total number of abnormal times during each abnormal period when the daily operation of the distribution cabinet is highly abnormal or less abnormal; Get the number of abnormal thresholds for a period; Determine whether the total number of abnormalities in a time period exceeds the abnormality threshold number in the time period; If the total number of abnormalities in a time period exceeds the threshold number of abnormalities in a time period, it is determined to be a daily operation fluctuation period of the distribution cabinet; If the total number of abnormalities in a time period does not exceed the abnormality threshold number in the time period, it is determined that the distribution cabinet is operating normally on a daily basis.

3. The power performance testing method of a power distribution cabinet according to claim 1, characterized in that: The step of constructing an evaluation period includes: Obtain daily operation data of the power distribution cabinet; Obtain daily standard operating range data of the power distribution cabinet; Determine whether the daily operation data of the power distribution cabinet exceeds the daily standard operation range data of the power distribution cabinet; If the daily operation data of the distribution cabinet exceeds the daily standard operation interval data of the distribution cabinet, the time when the daily operation data of the distribution cabinet exceeds the daily standard operation interval data of the distribution cabinet is marked as the first start time; Obtain the daily operation data of the distribution cabinet that exceeds the daily standard operation range data of the distribution cabinet, and mark it as exceeded data; Obtain the corresponding evaluation duration based on the exceeded data; Get the first end time based on the evaluation duration and the first start time; An evaluation period is constructed based on a first start time and a first end time.

4. The power performance testing method of a power distribution cabinet according to claim 2 is characterized in that: The step of obtaining multiple abnormal time periods corresponding to high abnormality and low abnormality of daily operation of the power distribution cabinet includes: The time when the daily operation of the power distribution cabinet is judged to be highly abnormal or less abnormal is marked as the abnormal time point; Get the time interval between every two adjacent abnormal time points and mark it as the time interval; Get the standard time interval; Determine whether the abnormal time interval is greater than the standard time interval. If the abnormal time interval is greater than the standard time interval, mark the start time of the abnormal time interval as the end time of the daily operation fluctuation period, and mark the end time of the abnormal time interval as the start time of the daily operation fluctuation period; Each daily operation fluctuation period is obtained according to the start time of the adjacent daily operation fluctuation period and the end time of the daily operation fluctuation period.

5. The method for testing the power performance of a distribution cabinet according to claim 1, characterized in that: The step of obtaining the power data of each electrical unit during the daily operation fluctuation period, determining whether the power data of each electrical unit meets the first preset condition, and if not, marking it as an abnormal electrical unit, includes: Obtain power data for each electrical unit during daily operating fluctuation periods; Obtaining corresponding electrical unit power values ​​according to electrical unit power data; Get the power evaluation interval value of the electrical unit; Determine whether the electrical unit power value is within the unit power evaluation interval value; If the electrical unit power value is within the unit power evaluation interval, the electrical unit is judged to be normal; If the electrical unit power value is not within the unit power evaluation interval value and is greater than the upper limit value of the unit power evaluation interval value, the electrical unit power is determined to be high and is marked as an abnormal electrical unit; If the electric unit power value is not within the unit power evaluation interval value and is less than the lower limit value of the unit power evaluation interval value, the power of the electric unit is determined to be low and is marked as an abnormal electric unit.

6. The method for testing the power performance of a power distribution cabinet according to claim 2, characterized in that: The step of obtaining the current data and the corresponding temperature data of each abnormal electrical unit, and respectively obtaining the current weight value and the temperature weight value of the corresponding abnormal electrical unit according to the current data and the corresponding temperature data, comprises: Obtaining current data of each abnormal electrical unit during an evaluation period; Acquire multiple corresponding current values ​​according to the current data; Get the current evaluation function; Inputting a plurality of current values ​​into a current evaluation function and marking an output result as a current evaluation value; Acquire corresponding temperature data according to the current data of each abnormal electrical unit; Acquire corresponding multiple temperature values ​​according to the temperature data; Get the temperature evaluation function; Input a plurality of temperature values ​​into a temperature evaluation function, and mark the output result as a temperature evaluation value; The corresponding current weight value and temperature weight value are obtained according to the current evaluation value and the temperature evaluation value respectively.

7. The method for testing the power performance of a power distribution cabinet according to claim 6, characterized in that: The step of respectively acquiring the corresponding current weight value and temperature weight value according to the current evaluation value and the temperature evaluation value comprises: Obtaining a current weight table, wherein the current weight table includes a plurality of current evaluation interval values ​​and a current weight value corresponding to each current evaluation interval value; Obtaining a corresponding target current evaluation interval value according to the current evaluation value; Obtain the corresponding current weight value from the current weight table according to the target current evaluation interval value; Obtaining a temperature weight table, wherein the temperature weight table includes a plurality of temperature evaluation interval values ​​and a temperature weight value corresponding to each temperature evaluation interval value; Obtain the corresponding target temperature evaluation interval value according to the temperature evaluation value; The corresponding temperature weight value is obtained from the temperature weight table according to the target temperature evaluation interval value.

8. The method for testing the power performance of a distribution cabinet according to claim 1, characterized in that: The step of obtaining the operation risk value of the power distribution cabinet according to the current weight value, the temperature weight value, and the electrical unit power data includes: Obtaining corresponding power factor according to electrical unit power data; Get the risk function; The current weight value, the temperature weight value, and the power factor are input into the risk function, and the output result is marked as the operation risk value.

9. A power distribution cabinet power performance test system, applied to the power distribution cabinet power performance test method according to any one of claims 1 to 8, characterized in that: include: Fluctuation module, used to obtain daily operation data of the power distribution cabinet, and obtain daily operation fluctuation period according to the daily operation data; An abnormal module, used to obtain the power data of each electrical unit during the daily operation fluctuation period, determine whether the power data of each electrical unit meets the first preset condition, and if not, mark it as an abnormal electrical unit; A weight module is used to obtain the current data and the corresponding temperature data of each abnormal electrical unit, and obtain the current weight value and the temperature weight value of the corresponding abnormal electrical unit according to the current data and the corresponding temperature data; The risk module is used to obtain the operation risk value of the distribution cabinet according to the current weight value, the temperature weight value, and the electrical unit power data; The judgment module is used to judge whether the operation risk value meets the preset value. If not, the distribution cabinet is judged to be abnormal, an inspection report is generated and an alarm signal is issued.

10. A power distribution cabinet power performance test terminal, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for testing the power performance of a distribution cabinet as described in any one of claims 1 to 8.

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