Equipment abnormity monitoring method, system and equipment and storage medium

Abstract

The invention relates to the field of equipment operation monitoring, in particular to an equipment abnormity monitoring method, which circularly executes the following steps in the working period of equipment: acquiring residual current data of an equipment loop at the current moment; comparing the residual current data with a current reference threshold; if the residual current data exceeds the current reference threshold, generating alarm information based on the residual current data; if the residual current data does not exceed a current reference threshold value, storing the residual current data to a database; and analyzing the residual current data in the database by taking the time T as an analysis period, and determining a health state prediction result of the equipment loop according to a data change trend of the residual current data. The invention further provides an equipment abnormity monitoring system, equipment and a storage medium. According to the invention, a worker can conveniently monitor the change process of the health state of the equipment loop and predict the safety problem of the equipment loop in advance.

Description

Technical Field

[0001] The present invention relates to the field of equipment operation monitoring, and in particular to an equipment abnormality monitoring method, system, equipment and storage medium. Background Art

[0002] The work requirements of the power industry place the safe and stable operation of the power grid in a crucial position. As the hub node of the power grid, the substation usually brings great inconvenience to production and life when the low-voltage distribution network fails. Therefore, ensuring the safe and stable operation of the power supply system is the key to the daily operation and maintenance process of the substation. In the daily operation and maintenance process of the substation, it is necessary to monitor the output power, efficiency, stability and other aspects of the power supply system of the equipment in the low-voltage distribution network in the station; in the prior art, the health of the equipment circuit is usually judged by the residual current of the equipment circuit. The residual current of the equipment circuit refers to the current whose current vector sum of each phase (including the neutral line) in the low-voltage distribution line is not zero. This current usually leaks to the ground through the human body or other paths when the electrical equipment fails, forming a current inconsistent with the normal current.

[0003] In the prior art, the residual current data of the equipment loop is usually collected in real time through a current transformer; one current transformer is used to test the current of the three live wires of the three-phase AC power supply, and another current transformer is used to test the neutral wire current, and then the currents measured by the two current transformers are vector-synthesized to obtain the residual current of the equipment loop; when the residual current of the equipment loop exceeds a preset threshold range, it is determined that the equipment loop has leakage, and when the residual current of the equipment loop is within the preset threshold range, it is determined that the equipment loop is in a normal state.

[0004] However, under natural conditions, the process of a device circuit changing from healthy to leaking is a process in which the line gradually ages and deteriorates. The abnormality detection system in the prior art can only warn of the health of the device circuit when the residual current reaches the set threshold, and will only issue an alarm after an abnormality occurs. It is unable to determine the gradual deterioration of the healthy insulation condition of the device circuit and the cause of the leakage, and there is a lag in the early warning of abnormal equipment conditions. Summary of the invention

[0005] In order to facilitate the staff to monitor the health status change process of the equipment loop and predict the safety problems of the equipment loop in advance, a method, system, device and storage medium for equipment abnormality monitoring are provided.

[0006] In order to achieve the above-mentioned object of the present invention, according to a first aspect of the present invention, the present invention provides a method for monitoring equipment abnormality.

[0007] The present invention provides a method for monitoring abnormality of equipment, which cyclically performs the following steps during the operation of the equipment:

[0008] Get the residual current data of the equipment circuit at the current moment;

[0009] Compare the residual current data with the current reference threshold:

[0010] If the residual current data exceeds the current reference threshold, generating an alarm message based on the residual current data;

[0011] If the residual current data does not exceed the current reference threshold, the residual current data is saved in the database, and the residual current data in the database is analyzed with time T as the analysis period, and the health status prediction result of the equipment loop is determined according to the data change trend of the residual current data.

[0012] Optionally, the alarm information includes a fault type;

[0013] The generating of warning information based on the residual current data comprises:

[0014] Obtain historical residual current data within a preset time period P before the current moment, where P is an integer;

[0015] Using the x-axis to represent time and the y-axis to represent historical residual current, obtaining the slope change characteristics of the historical residual current data within a preset time period P, and determining the slope change type of the residual current data according to the slope change characteristics, wherein the slope change types include a sudden change type and a slow change type;

[0016] Determine the fault type of the equipment circuit based on the slope change type:

[0017] If the slope change type of the residual current data is a sudden change, it is predicted that the fault type of the equipment circuit is that the power supply cable of the equipment is damaged by external force;

[0018] If the slope change type of the residual current data is a slow change type, the predicted fault type of the equipment circuit is natural aging of the equipment power supply cable or repeated grounding of the neutral line.

[0019] Optionally, if the slope change type is a slow change type, historical load current data of the device within a preset time period P before the current moment is obtained;

[0020] Calculate the correlation coefficient between the historical residual current data and the historical load current data within a preset time period P;

[0021] Compare the correlation coefficient to the correlation coefficient reference threshold:

[0022] If the correlation coefficient is greater than the correlation coefficient reference threshold, the fault type of the predicted equipment circuit is repeated grounding of the neutral line;

[0023] If the correlation coefficient is less than or equal to the correlation coefficient reference threshold, the fault type of the predicted device circuit is the natural aging of the device power supply cable.

[0024] Optionally, if the correlation coefficient is greater than a correlation coefficient reference threshold, the number of single-phase loads in the device is obtained, and if the number of single-phase loads is greater than or equal to 1, it is determined that the fault type of the device loop is a repeated neutral grounding setting.

[0025] Optionally, the analyzing the residual current data in the database with time T as the analysis period, and determining the health status prediction result of the equipment loop according to the data change trend of the residual current data, includes:

[0026] Retrieve the residual current data obtained within the most recent time T from the database and calculate the mean value I of the residual current data in the current analysis period av e;

[0027] According to the mean value I of the residual current data of the current analysis cycle ave Determine the growth rate R of the residual current data;

[0028] The health status prediction result of the equipment circuit is determined according to the growth rate R of the residual current data.

[0029] Optionally, the calculation formula for the growth rate R of the residual current data is: Among them, I ave0 is the initial mean value of the residual current data, which is the mean value of the residual current data of the first analysis cycle after the equipment loop power supply system enters the normal operating state.

[0030] Optionally, determining the health status prediction result of the equipment loop according to the growth rate R of the residual current data includes:

[0031] Processing the growth rate R of the residual current data of M consecutive analysis cycles to generate a growth rate change curve;

[0032] The health status of the equipment loop is determined according to the changing trend of the growth rate change curve, and the health status prediction result of the equipment loop is obtained:

[0033] If the growth rate R curve of the residual current data of M consecutive analysis cycles is increasing, it is determined that there is a risk of line aging in the equipment circuit;

[0034] If the growth rate R curve of the residual current data of M consecutive analysis cycles fluctuates, it is determined that the equipment circuit is operating normally.

[0035] In order to solve the above problems, the present invention further provides a device abnormality monitoring system, the system comprising:

[0036] An acquisition module is used to acquire residual current data of a device circuit;

[0037] Comparison module, used to compare the residual current data with the current reference threshold:

[0038] If the residual current data exceeds the current reference threshold, generating an alarm message based on the residual current data;

[0039] If the residual current data does not exceed the current reference threshold, the residual current data is saved in a database;

[0040] The analysis module is used to analyze the residual current data in the database with time T as the analysis period, and determine the health status prediction result of the equipment circuit according to the data change trend of the residual current data.

[0041] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0042] at least one processor; and,

[0043] a memory communicatively connected to the at least one processor; wherein,

[0044] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned device abnormality monitoring method.

[0045] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one computer program is stored. The at least one computer program is executed by a processor in an electronic device to implement the above-mentioned device abnormality monitoring method.

[0046] In summary, this application includes the following beneficial technical effects:

[0047] The health status of the equipment circuit is judged based on the residual current data of the equipment circuit. When the residual current data is monitored to exceed the current reference threshold, it means that the equipment circuit has a fault, and an alarm message is issued to prompt the staff so that the staff can check the problem of the equipment circuit in time; if the residual current data exceeds the current reference threshold, the residual current data exceeding the current reference threshold is saved to the database, and the latest residual current data of the equipment circuit is regularly retrieved from the database for analysis; the operating status of the equipment circuit is predicted based on the data change trend of the residual current data. The staff can judge whether there is a risk in the equipment circuit based on the prediction result of the health status of the equipment circuit, and predict the safety problems of the equipment circuit in advance; when there is an abnormality in the change trend of the residual current data, the staff can check and evaluate the status of the equipment circuit in advance, so that the staff can monitor the change process of the health status of the equipment circuit;

[0048] The type of fault is inferred by using the changes in the residual current data in the equipment circuit, and the fault type of the equipment circuit is informed to the staff when the alarm information is issued, so that the staff can quickly understand the fault type of the equipment circuit after receiving the alarm information, thereby improving the efficiency of the staff in troubleshooting and repairing the equipment circuit. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic diagram of a process flow of a method for monitoring abnormality of equipment provided by an embodiment of the present invention;

[0050] Figure 2 A schematic diagram of the installation position of the current transformer when measuring residual current data when powered by a single power supply;

[0051] Figure 3 Installation schematic diagram of the current transformer for measuring residual current data when dual power supply is used;

[0052] Figure 4 A schematic diagram of a process for determining a health status prediction result of a device circuit according to a data change trend of residual current data provided by an embodiment of the present invention;

[0053] Figure 5 A functional module diagram of a device abnormality monitoring system provided by an embodiment of the present invention;

[0054] Figure 6 A schematic diagram of the structure of an electronic device for implementing the device abnormality monitoring method provided in one embodiment of the present invention.

[0055] Figure numerals: 10, processor; 11, memory; 12, communication bus; 13, communication interface; 51, acquisition module; 52, comparison module; 53, analysis module.

[0056] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0057] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0058] In the description of the present invention, it is necessary to understand that the terms "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0059] In the description of the present invention, unless otherwise specified and limited, it should be noted that the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a mechanical connection or an electrical connection, or it can be the internal connection between two components. It can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to the specific circumstances.

[0060] Reference Figure 1 FIG. 1 is a flow chart of a method for monitoring abnormality of equipment provided by an embodiment of the present invention. In this embodiment, the following steps are executed cyclically during the operation of the equipment:

[0061] S1. Obtain the residual current data of the device circuit at the current moment.

[0062] A current transformer (CT) is usually used to collect residual current data in the equipment circuit. Specifically, the power supply mode of the equipment circuit includes single power supply and dual power supply.

[0063] Figure 2 This is a schematic diagram of the installation position of the current transformer when measuring residual current data when the single power supply system includes three live wires and one neutral wire. Figure 2, A line, B line and C line are three live wires, which are responsible for transmitting electricity; N line is the zero line, and N line, as the neutral point, is responsible for connecting the three-phase loads; the full name of PE line in English is Protecting Earthing, which stands for protective grounding wire, providing electrical safety protection for the equipment circuit.

[0064] When monitoring the equipment loop of a single-power supply system, use a current transformer (named CT1) to test the currents of the three live wires A, B and C, and use another current transformer (named CT2) to test the neutral wire current. Then, the currents measured by the two current transformers are vector-synthesized to obtain the residual current data of the equipment loop.

[0065] Residual current I in the equipment circuit of a single power supply system S The synthesis calculation formula is:

[0066]

[0067] Where, I1 is the effective value of the current measured by the current transformer CT1, in mA; I2 is the phase of the current measured by the current transformer CT1 relative to the reference voltage, in rad; I2 is the effective value of the current measured by the current transformer CT2, It is the phase of the current measured by current transformer CT2 relative to the reference voltage.

[0068] Figure 3 The schematic diagram of the installation position of the current transformer for measuring the residual current data when dual power supply is used. The dual power supply system has two power supply circuits, each of which includes three live wires A, B, and C, a neutral wire, and a PE wire. When monitoring the equipment circuit of the dual power supply system, for each power supply circuit, a current transformer is used to test the current of the three live wires A, B, and C, and another current transformer is used to test the neutral wire current. The current transformer for measuring the live wire current in the first power supply circuit is named CT3, and the current transformer for measuring the neutral wire current in the first power supply circuit is named CT4; the current transformer for measuring the live wire current in the second power supply circuit is named CT5, and the current transformer for measuring the neutral wire current in the second power supply circuit is named CT6. The currents measured by the four current transformers are vector synthesized to obtain the residual current data of the equipment circuit of the dual power supply system.

[0069] The calculation formula for the residual current ID in the equipment circuit of the dual power supply system is:

[0070]

[0071] Among them, I3 is the effective value of the current measured by the current transformer CT3, is the phase of the current measured by the current transformer CT3 relative to the reference voltage; I4 is the effective value of the current measured by the current transformer CT4, is the phase of the current measured by the current transformer CT4 relative to the reference voltage; I5 is the effective value of the current measured by the current transformer CT5, is the phase of the current measured by the current transformer CT5 relative to the reference voltage; I6 is the effective value of the current measured by the current transformer CT6, It is the phase of the current measured by current transformer CT6 relative to the reference voltage.

[0072] The calculation method of the residual current data in the equipment loop of the multi-power supply system is consistent with the calculation method of the residual current data of the single power supply system and the dual power supply system mentioned above; through the description of the calculation method of the residual current data of the single power supply system and the dual power supply system, technical personnel in this field can clearly know the calculation method of the residual current data of the multi-power supply system, and for the sake of brevity of the specification, this embodiment will not be repeated.

[0073] S2. Compare the residual current data of the equipment circuit with the current reference threshold:

[0074] If the residual current data exceeds the current reference threshold, an alarm message is generated based on the residual current data;

[0075] If the residual current data does not exceed the current reference threshold, the residual current data is saved in the database, and the residual current data in the database is analyzed with time T as the analysis period, and the health status prediction result of the equipment circuit is determined according to the data change trend of the residual current data.

[0076] Wherein, T is a positive integer, and the alarm information includes the faulty device number, the fault type of the device circuit, and the fault time, etc. The fault types include the following situations: the power supply cable of the device is damaged by external force, the power supply cable of the device is naturally aged, and the neutral line is repeatedly grounded.

[0077] In this embodiment, the steps of generating alarm information based on residual current data include:

[0078] Obtain historical residual current data within a preset time period P before the current moment, where P is an integer;

[0079] Using the x-axis to represent time and the y-axis to represent historical residual current, obtaining the slope change characteristics of the historical residual current data within a preset time period P, and determining the slope change type of the residual current data according to the slope change characteristics;

[0080] The slope change type includes a sudden change type and a slow change type, wherein the sudden change type refers to the situation where there is a sudden increase in the local slope and the waveform of the slope k is relatively steep. When the slope of a certain sampling point exceeds the reference value, it is determined that the local slope of the sampling point suddenly increases; the staff can set the size of the slope reference value according to the actual situation, and this embodiment does not limit it. If there is no sudden increase in the local slope or the waveform of the slope k fluctuates up and down, the slope change type is determined to be a slow change type.

[0081] The slope represents the average rate of change of the residual current in the device circuit from the last sampling time point to the current sampling time point; in this embodiment, the calculation formula of the slope k is: Among them, t1 is the sampling time of the previous sampling point, I1 is the residual current data of the previous sampling point; t2 is the sampling time of the current sampling point, I2 is the residual current data of the current sampling point.

[0082] In a preferred implementation of this embodiment, the slopes of multiple historical residual current data within a preset time period P before the current moment are obtained to determine the slope change characteristics, thereby reducing the impact of a sudden change in the slope of the residual current data at a certain moment due to voltage instability on the prediction results and improving the accuracy of the slope change characteristic prediction results.

[0083] When processing the slopes of multiple historical residual current data within a preset time period P before the current moment, the first and last difference value, cumulative value, mean value or median value of the slope k of multiple historical residual current data within the preset time period P before the current moment can be used to determine the slope change characteristics of the historical residual current data within the preset time period P before the current moment.

[0084] The calculation formula for the accumulated value Acc of the slope k is:

[0085] Wherein, t represents the total number of slopes of multiple historical residual current data within a preset time period P before the current moment, and t is a positive integer; k i is the slope of the i-th historical residual current data in the preset time period P before the current moment, k i Can be positive or negative.

[0086] Since the power supply voltage is unstable when the power supply system is supplying power to the equipment, the change curve of the historical residual current data under normal conditions should be fluctuating, and the slope of the historical residual current data should have positive and negative values; therefore, when the equipment loop is in a normal state or the slope change type is a slow change type, the cumulative value of the slope k of multiple historical residual current data in the preset time period P before the current moment is much smaller than the cumulative value of the slope k when the slope change type is a sudden change type.

[0087] The accumulated value Acc of the slope k of multiple historical residual current data in the preset time period P before the current moment is used to judge the slope change characteristics of the historical residual current data in the preset time period P. This can make the change characteristics of the equipment loop slope k more sensitively identified, and further improve the accuracy of the slope change type judgment result.

[0088] The steps of generating warning information based on residual current data include:

[0089] Determine the fault type of the equipment circuit based on the slope change type:

[0090] If the slope change type of the residual current data is a mutation type, the predicted fault type of the equipment circuit is that the equipment power supply cable is damaged by external force; for example, the equipment power supply cable is damaged due to construction or gnawed by rats.

[0091] If the slope change type of the residual current data is a slow change type, the predicted fault type of the equipment circuit is natural aging of the equipment power supply cable or repeated grounding of the neutral line.

[0092] Specifically, if it is determined that the slope change type is a slow change type, then the load current data of the device circuit is obtained;

[0093] Calculating a correlation coefficient between the residual current data and the load current data collected synchronously with the residual current data;

[0094] Compare the correlation coefficient to the correlation coefficient reference threshold:

[0095] If the correlation coefficient is greater than the correlation coefficient reference threshold, the fault type of the predicted equipment circuit is repeated grounding of the neutral line;

[0096] If the correlation coefficient is less than or equal to the correlation coefficient reference threshold, the fault type of the predicted device circuit is the natural aging of the device power supply cable.

[0097] In this embodiment, the calculation formula of the correlation coefficient between the residual current data and the load current data collected synchronously with the residual current data is:

[0098]

[0099] Among them, i is the index of the residual current data collected by the current transformer, It is the characteristic data set of residual current data in the equipment circuit; I 2i It is a characteristic data set of load current data collected synchronously with residual current data in the equipment circuit; is the variance of the residual current data in the equipment loop, is the variance of the load current data in the equipment loop.

[0100] It should be noted that it is necessary to control the current transformer to synchronously collect the residual current data and load current data of the equipment circuit; in addition, in order to improve the calculation accuracy of the correlation coefficient of the residual current data and the load current data, the current transformer is controlled to continuously collect multiple residual current data and multiple load current data within a period of time, and use multiple sets of current data to calculate the correlation coefficient of the residual current data and the load current data.

[0101] The inventors have found in long-term practice that the insulation of the cable to the ground deteriorates after aging, which will lead to a decrease in the resistance to the ground, while the voltage at both ends of the cable is constant. Therefore, the residual current data of the cable will change regularly after aging; and aging is a slowly changing process. The leakage current caused by aging is relatively stable and fluctuates less with the load. When the neutral line is repeatedly grounded, the residual current size is closely related to whether the three phases ABC at the load end are balanced. The correlation coefficient between the residual current data and the load current data can be used to quickly identify and distinguish between cable aging faults and neutral line repeated grounding faults.

[0102] In a preferred embodiment of the present application, if the correlation coefficient is greater than the correlation coefficient reference threshold, the number of single-phase loads in the device is obtained. If the number of single-phase loads is greater than or equal to 1, the fault type of the device loop is determined to be a repeated neutral grounding setting.

[0103] In the case of repeated grounding of the zero point, when there are single-phase loads among the loads, these single-phase loads will be directly connected to the neutral line, which will cause the current on the neutral line to increase, thereby increasing the judgment confidence of the fault prediction result that the fault type of the equipment loop is set as repeated grounding of the neutral line.

[0104] The changes in the residual current data and load current data in the equipment circuit are used to infer the type of fault that has occurred and inform the staff; when the staff receives the alarm information of the line fault, they can quickly understand the fault type of the equipment circuit, which can improve the efficiency of the staff in troubleshooting and repairing the equipment circuit.

[0105] Reference Figure 4 Specifically, the step of determining the health status prediction result of the equipment loop according to the data change trend of the residual current data includes:

[0106] S31, retrieve the residual current data obtained within the most recent time T from the database, and calculate the mean value I of the residual current data in the current analysis period ave ;

[0107] The trend of slow change is determined by counting the mean value of the period. In this embodiment, the mean value is ave The calculation formula is the value

[0108] Among them, I kis the kth residual current value in the analysis cycle, and n represents the total number of residual current values ​​collected in one analysis cycle.

[0109] For example, if there are data from the past 50 days in the database, and every 10 days is an analysis cycle, then the 1st to 10th day is an analysis cycle, the 11th to 20th day is an analysis cycle, ..., the 41st to 50th day is an analysis cycle; 2000 residual current values ​​are collected in each analysis cycle (i.e. 10 days), and the mean value of the residual current data of the analysis cycle is calculated based on the 2000 residual current values ​​collected in the analysis cycle.

[0110] S32, according to the mean value I of the residual current data of the current analysis cycle ave Determine the growth rate R of the residual current data;

[0111] The calculation formula for the growth rate R of the residual current data is: Among them, I ave0 is the initial mean value of the residual current data, which is the mean value of the residual current data of the first analysis cycle after the equipment loop power supply system enters the normal operating state.

[0112] S33. Determine the health status prediction result of the equipment circuit according to the growth rate R of the residual current data.

[0113] The health status prediction result of the equipment circuit is determined according to the growth rate R of the residual current data, including:

[0114] Processing the growth rate R of the residual current data of M consecutive analysis cycles to generate a growth rate change curve;

[0115] The health status of the equipment loop is determined according to the changing trend of the growth rate change curve, and the health status prediction result of the equipment loop is obtained:

[0116] If the growth rate R curve of the residual current data of M consecutive analysis cycles is increasing, it is determined that there is a risk of line aging in the equipment circuit;

[0117] If the growth rate R curve of the residual current data of M consecutive analysis cycles fluctuates, it is determined that the equipment circuit is operating normally.

[0118] In a preferred implementation of this embodiment, after determining the health status prediction result of the device loop according to the growth rate R of the residual current data, the method further includes:

[0119] The growth rate R of the residual current data is compared with a growth rate reference threshold, and when the growth rate R of the residual current data exceeds the growth rate reference threshold, an early warning message is issued.

[0120] When the growth rate of residual current data is too large, it proves that the risk of equipment circuit aging is high, and early warning information is sent to the staff in advance; after receiving the early warning information, the staff can evaluate and detect the health status of the equipment circuit in advance, and check the potential risks of the equipment circuit in advance, thereby reducing the possibility of affecting production and life due to equipment power supply system failures, and reducing the possibility of economic losses due to power supply system failures.

[0121] Reference Figure 5 Based on the same inventive concept, an embodiment of the present invention provides a device abnormality monitoring system.

[0122] The device abnormality monitoring system described in the present invention can be loaded in an electronic device. According to the functions implemented, the device abnormality monitoring system includes an acquisition module 51, a comparison module 52 and an analysis module 53, wherein the acquisition module 51 can acquire the residual current data of the device loop; the comparison module 52 can compare the residual current data with the current reference threshold: if the residual current data exceeds the current reference threshold, an alarm message is generated based on the residual current data; if the residual current data does not exceed the current reference threshold, the residual current data is saved to the database; the analysis module 53 can analyze the residual current data in the database with time T as the analysis period, and determine the health status prediction result of the device loop according to the data change trend of the residual current data.

[0123] The module described in the present invention may also be referred to as a unit, which refers to a series of computer program segments that can be executed by a processor of an electronic device and can complete fixed functions, and is stored in a memory of the electronic device.

[0124] The various variations and specific examples of the equipment abnormality monitoring method provided in the above embodiment are also applicable to the equipment abnormality monitoring system of this embodiment. Through the above detailed description of the equipment abnormality monitoring method, those skilled in the art can clearly know the implementation method of the equipment abnormality monitoring system in this embodiment. For the sake of brevity of the specification, it will not be described in detail here.

[0125] The present application also discloses an electronic device, such as Figure 6 , which is a schematic diagram of the structure of an electronic device for a method for monitoring device abnormality according to an embodiment of the present invention. The electronic device may include at least one processor 10, a memory 11 connected to the at least one processor for communication, a communication bus 12, and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a method program for monitoring device abnormality.

[0126] In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (such as the executed device abnormality monitoring method, etc.), and calls the data stored in the memory 11 to execute various functions of the electronic device and process data.

[0127] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 may also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory 11 may also include both an internal storage unit of the electronic device and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device, such as the code of the device abnormality monitoring method program, but also be used to temporarily store data that has been output or is to be output.

[0128] The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0129] The communication interface 13 is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0130] Figure 6 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 6 The structure shown does not constitute a limitation on the electronic device, and may include fewer or more components than shown, or combine certain components, or arrange the components differently. For example, although not shown, the electronic device may also include a power supply (such as a battery) for supplying power to each component. Preferably, the power supply may be logically connected to at least one processor 10 through a power management device, so that functions such as charging management, discharging management, and power consumption management are implemented through the power management device. The power supply may also include any components such as one or more DC or AC power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0131] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited by this structure.

[0132] Furthermore, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile.

[0133] The present application embodiment provides a computer-readable storage medium, for example, including: any entity or device, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM) that can carry the computer program code. The computer-readable storage medium stores a computer program that can be loaded by a processor and execute the device abnormality monitoring method of the above embodiment.

[0134] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", "an implementation", "a preferred implementation" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0135] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A method for monitoring equipment abnormality, characterized in that: The following steps are performed cyclically during the operation of the device: Get the residual current data of the equipment circuit at the current moment; Compare the residual current data with the current reference threshold: If the residual current data exceeds the current reference threshold, generating an alarm message based on the residual current data; If the residual current data does not exceed the current reference threshold, the residual current data is saved in the database, and the residual current data in the database is analyzed with time T as the analysis period, and the health status prediction result of the equipment loop is determined according to the data change trend of the residual current data.

2. The device abnormality monitoring method according to claim 1, characterized in that: The warning information includes the fault type; The generating of warning information based on the residual current data comprises: Obtain historical residual current data within a preset time period P before the current moment, where P is an integer; Using the x-axis to represent time and the y-axis to represent historical residual current, obtaining the slope change characteristics of the historical residual current data within a preset time period P, and determining the slope change type of the residual current data according to the slope change characteristics, wherein the slope change types include a sudden change type and a slow change type; Determine the fault type of the equipment circuit based on the slope change type: If the slope change type of the residual current data is a sudden change, it is predicted that the fault type of the equipment circuit is that the power supply cable of the equipment is damaged by external force; If the slope change type of the residual current data is a slow change type, the predicted fault type of the equipment circuit is natural aging of the equipment power supply cable or repeated grounding of the neutral line.

3. The device abnormality monitoring method according to claim 2, characterized in that: If the slope change type is a slow change type, then the historical load current data of the device in the preset time period P before the current moment is obtained; Calculate the correlation coefficient between the historical residual current data and the historical load current data within a preset time period P; Compare the correlation coefficient to the correlation coefficient reference threshold: If the correlation coefficient is greater than the correlation coefficient reference threshold, the fault type of the predicted equipment circuit is repeated grounding of the neutral line; If the correlation coefficient is less than or equal to the correlation coefficient reference threshold, the fault type of the predicted device circuit is the natural aging of the device power supply cable.

4. The device abnormality monitoring method according to claim 3, characterized in that: If the correlation coefficient is greater than the correlation coefficient reference threshold, the number of single-phase loads in the device is obtained. If the number of single-phase loads is greater than or equal to 1, it is determined that the fault type of the device circuit is a repeated neutral grounding setting.

5. The device abnormality monitoring method according to any one of claims 1 to 4, characterized in that: The residual current data in the database is analyzed with time T as the analysis period, and the health status prediction result of the equipment circuit is determined according to the data change trend of the residual current data, including: Retrieve the residual current data obtained within the most recent time T from the database and calculate the mean value I of the residual current data in the current analysis period ave ; According to the mean value I of the residual current data of the current analysis cycle ave Determine the growth rate R of the residual current data; The health status prediction result of the equipment circuit is determined according to the growth rate R of the residual current data.

6. The device abnormality monitoring method according to claim 5, characterized in that: The calculation formula for the growth rate R of the residual current data is: Among them, I ave0 is the initial mean value of the residual current data, which is the mean value of the residual current data of the first analysis cycle after the equipment loop power supply system enters the normal operating state.

7. The device abnormality monitoring method according to claim 5, characterized in that: The step of determining the health status prediction result of the equipment loop according to the growth rate R of the residual current data includes: Processing the growth rate R of the residual current data of M consecutive analysis cycles to generate a growth rate change curve; The health status of the equipment loop is determined according to the changing trend of the growth rate change curve, and the health status prediction result of the equipment loop is obtained: If the growth rate R curve of the residual current data of M consecutive analysis cycles is increasing, it is determined that there is a risk of line aging in the equipment circuit; If the growth rate R curve of the residual current data of M consecutive analysis cycles fluctuates, it is determined that the equipment circuit is operating normally.

8. A device abnormality monitoring system, used to implement the device abnormality monitoring method according to any one of claims 1 to 7, characterized in that: include: An acquisition module (51), used for acquiring residual current data of a device circuit; A comparison module (52) is used to compare the residual current data with a current reference threshold: If the residual current data exceeds the current reference threshold, generating an alarm message based on the residual current data; If the residual current data does not exceed the current reference threshold, the residual current data is saved in a database; The analysis module (53) is used to analyze the residual current data in the database with time T as the analysis period, and determine the health status prediction result of the equipment loop according to the data change trend of the residual current data.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor (10); and, a memory (11) communicatively connected to the at least one processor (10); The memory (11) stores a computer program executable by the at least one processor (10), and the computer program is executed by the at least one processor (10) so that the at least one processor (10) can execute the equipment abnormality monitoring method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer storage medium stores a computer program; when the computer program is executed by a processor, the device abnormality monitoring method according to any one of claims 1 to 7 is implemented.

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