Fault arc detection method, device and equipment and storage medium

Abstract

The invention relates to the technical field of power safety monitoring, in particular to a fault arc detection method, device and equipment and a storage medium, and the method comprises the steps: obtaining a current time sequence array of a power system in a current sampling period; and determining a current mutation coefficient of the power system according to the current time sequence array and a preset current effective value, and performing arc fault detection on the power system according to the current mutation coefficient. According to the invention, the accuracy of fault arc detection is obviously improved.

Description

Technical Field

[0001] The present application relates to the technical field of power safety monitoring, and in particular to a fault arc detection method, device, equipment and storage medium. Background Art

[0002] With the rapid development of the power industry and the popularization of smart grids, the safe and stable operation of power systems has become increasingly important. Arc faults are one of the common safety hazards in power systems. Their rapid and accurate detection and location are of great significance for preventing fires, protecting equipment, and ensuring power supply reliability.

[0003] However, the current mainstream arc fault detection technology compares the parameter values ​​obtained based on the measurement of parameters such as current and voltage with the fixed arc judgment threshold to determine whether there is an arc fault. However, this traditional arc fault detection technology has certain limitations in practical applications. On the one hand, the monitoring and calculation of multiple parameters requires a large amount of computing resources; on the other hand, the occurrence of arc faults has a certain duration, and the parameter values ​​obtained only by measurement cannot capture the timing characteristics of arc faults, resulting in poor accuracy of arc fault detection.

[0004] Therefore, how to improve the accuracy of fault arc detection is a technical problem that needs to be solved urgently. Summary of the invention

[0005] The main purpose of the present application is to provide a method, device, equipment and storage medium for fault arc detection, aiming to improve the accuracy of fault arc detection.

[0006] To achieve the above object, the present application provides a fault arc detection method, the fault arc detection method comprising:

[0007] Obtain the current time series array of the power system in the current sampling period;

[0008] A current mutation coefficient of the power system is determined according to the current time series array and a preset current effective value, and arc fault detection is performed on the power system according to the current mutation coefficient.

[0009] In one embodiment, the current time series array includes a plurality of current time series signals arranged in chronological order, and the step of determining the current mutation coefficient of the power system based on the current time series array and a preset current effective value includes:

[0010] Accumulating total current signal values ​​between the current time series signals, and determining a current signal mean value according to the total current signal value and the number of current samplings of the current time series array;

[0011] After determining that the current signal mean value is greater than or equal to a preset current effective value, determining the current jump degree of the power system according to the current jump value corresponding to the target time sequence signal, wherein the target time sequence signal is any one of the multiple current time sequence signals;

[0012] The current mutation coefficient of the power system is determined according to the current jump degree.

[0013] In one embodiment, the step of determining the current jump degree of the power system according to the current jump value corresponding to the target timing signal includes:

[0014] Obtaining a current jump value corresponding to a target timing signal;

[0015] Taking the current timing signal after the target timing signal as the next target timing signal, returning to execute the step of obtaining the current jump value corresponding to the target timing signal, and accumulating the signal accumulation number of the target timing signal;

[0016] Until the accumulated number of signals reaches the difference between the current sampling number and the preset signal number, the accumulated number of signals is determined to be the valid signal number of the current timing array, and the current jump value corresponding to the target timing signal of the valid signal number is used as the current jump degree of the power system.

[0017] In one embodiment, the step of obtaining the current jump value corresponding to the target timing signal includes:

[0018] Determine a continuous time sequence signal after the target time sequence signal, and perform sum processing according to each of the current time sequence signals in the continuous time sequence signal to obtain a current signal sum value;

[0019] Determine the preset signal quantity as the number of timing signals corresponding to the continuous timing signal, take the number of timing signals as the product multiple of the target timing signal, and obtain the current product value of the target timing signal;

[0020] The current jump value corresponding to the target timing signal is determined according to the current difference between the current signal sum value and the current product value, and the sampling interval time of the current timing array.

[0021] In one embodiment, the step of determining the current mutation coefficient of the power system according to the current jump degree includes:

[0022] Determine the number of valid signals of the current timing array, the current jump degree being the current jump value corresponding to the target timing signal of the number of valid signals;

[0023] Performing summation processing according to the current jump values ​​corresponding to the target timing signals to obtain a total current jump value, and determining a current jump mean value according to the total current jump value and the number of valid signals;

[0024] The current jump difference between the current jump value corresponding to each of the target time sequence signals and the current jump mean is accumulated to obtain the current mutation coefficient of the power system.

[0025] In one embodiment, the step of performing arc fault detection on the power system according to the current mutation coefficient includes:

[0026] The current mutation coefficient is stored as the current mutation coefficient of the current sampling period, and the current time series array of the next sampling period of the current sampling period is obtained, and the step of determining the current mutation coefficient of the power system according to the current time series array and the preset current effective value is returned to obtain the target mutation coefficient of the next sampling period of the current sampling period;

[0027] Determine a mutation absolute difference between the target mutation coefficient and the current mutation coefficient, and detect whether the mutation absolute difference exceeds a preset arc occurrence threshold;

[0028] If the mutation absolute difference exceeds the arc occurrence threshold, it is determined that an arc fault occurs in the power system;

[0029] If the sudden change absolute difference does not exceed the arc occurrence threshold, it is determined that no arc fault occurs in the power system.

[0030] In one embodiment, after determining that no arc fault occurs in the power system, the arc fault detection method includes:

[0031] The next sampling cycle of the current sampling cycle is used as the next current sampling cycle, and the target mutation coefficient is used as the current mutation coefficient of the next current sampling cycle, and the step of obtaining the current timing array of the next sampling cycle of the current sampling cycle is returned to be executed.

[0032] In addition, to achieve the above-mentioned purpose, the present application also provides a fault arc detection device, the fault arc detection device comprising:

[0033] An acquisition module, used for acquiring a current time series array of the power system in a current sampling period;

[0034] The detection module is used to determine the current mutation coefficient of the power system according to the current time series array and a preset current effective value, and perform arc fault detection on the power system according to the current mutation coefficient.

[0035] Each functional module of the arc fault detection device of the present application implements the steps of the arc fault detection method of the present application as described above during operation.

[0036] In addition, to achieve the above-mentioned purpose, the present application also provides a device, which includes a memory, a processor, and a fault arc detection program stored in the memory and executable on the processor, and the fault arc detection program implements the steps of the above-mentioned fault arc detection method when executed by the processor.

[0037] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, which is a computer-readable storage medium, and a fault arc detection program is stored on the computer-readable storage medium. When the fault arc detection program is executed by the processor, the steps of the above-mentioned fault arc detection method are implemented.

[0038] The present application provides a fault arc detection method that optimizes the traditional arc fault detection technology in a targeted manner, significantly improving the accuracy of fault arc detection. Specifically, the fault arc detection method provided in the present application obtains the current time series array of the power system in the current sampling period, and accurately obtains the current mutation coefficient of the power system based on the current time series array and the preset current effective value, thereby avoiding the computing power consumption caused by multi-parameter monitoring and complex algorithms in the traditional arc fault detection method; next, since the current mutation coefficient can accurately reflect the severity of the current fluctuation in the timing, the arc fault of the power system can be efficiently detected based on the current mutation coefficient, which can effectively prevent the arc fault false alarm and omission caused by the comparison of the parameter values ​​obtained by multi-parameter monitoring with the static threshold, thereby significantly enhancing the accuracy of fault arc detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flow chart of the first embodiment of the fault arc detection method of the present application;

[0040] Figure 2 It is a schematic diagram of a normal current waveform involved in an embodiment of a fault arc detection method of the present application;

[0041] Figure 3 It is a schematic diagram of a fault arc current waveform involved in an embodiment of a fault arc detection method of the present application;

[0042] Figure 4 The normal current solution K involved in the first embodiment of the arc fault detection method of the present application i Schematic diagram;

[0043] Figure 5 The arc fault detection method of the present application involves the arc fault solution K i Schematic diagram;

[0044] Figure 6 The normal current solution X involved in the first embodiment of the fault arc detection method of the present application i Schematic diagram;

[0045] Figure 7 The arc fault detection method of the present application is related to the arc fault solution X i Schematic diagram;

[0046] Figure 8 It is a schematic diagram of a detection process involved in an embodiment of a fault arc detection method of the present application;

[0047] Fig. 9 It is a structural schematic diagram of a fault arc detection device involved in an embodiment of the present application;

[0048] Fig.10 This is a schematic diagram of the structure of the arc fault detection device involved in the embodiment of the present application.

[0049] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0050] The present application embodiment provides a fault arc detection method, referring to Figure 1 As shown, Figure 1 It is a flow chart of the first embodiment of the fault arc detection method of the present application.

[0051] Here, exemplary embodiments are described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application.

[0052] With the continuous development of social economy, the number of fire accidents has also continued to rise year-on-year. The main cause of electrical fires is the internal wiring of the house, such as electrical wiring, socket wiring, internal wiring of household appliances and power cords. Under long-term load operation, the insulation layer of the wires ages or the insulation is damaged, which can easily cause series-parallel arc faults between lines or line-to-ground short circuit faults. Compared with the characteristic of increased short-circuit current in short-circuit faults, the current amplitude in the line is small when a low-voltage fault arc occurs and is easily affected by grid noise. Traditional circuit detection devices cannot effectively detect line fault arcs, so the protection fails. The conductive path formed after the insulation material is broken down causes the arc to continue to burn. The local high temperature generated during the burning can easily ignite the surrounding combustibles and cause a fire, which seriously threatens the safety of life and property.

[0053] Most of the existing AC fault arc detection technologies are based on comparing the parameter values ​​obtained by measuring parameters such as current and voltage with a fixed arc judgment threshold to determine whether an arc fault exists. Specifically, by comparing the measured parameter value with the fixed arc judgment threshold, if the parameter value is less than the arc judgment threshold, it is determined that no arc occurs, otherwise an arc occurs; however, in actual use, the arc occurs for a certain duration, and the arc current waveform is different from the ordinary current waveform in the time series. The use of a single threshold judgment ignores the time sequence difference between the arc current and the ordinary current, resulting in inaccurate arc fault detection, and all current calculations increase computing power consumption.

[0054] Therefore, in order to solve the above-mentioned defects of the traditional arc fault detection technology, the present application provides a fault arc detection method, device, equipment and storage medium.

[0055] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, a database system, etc., or a device capable of realizing the above functions, such as a fault arc detection device, etc. The following takes the fault arc detection device as an example to illustrate this embodiment and the following embodiments.

[0056] The arc fault detection method of the present application includes the following implementation steps S10 to S20.

[0057] Step S10: Acquire the current time series array of the power system in the current sampling period.

[0058] In this embodiment, the present application provides an ADC sampling module on the circuit for powering the load from the power system, and obtains the current timing array on the power supply circuit from the power system to the load in the current sampling period through the ADC (Analog-to-Digital Converter) sampling module, thereby avoiding the computing power consumption caused by multi-parameter monitoring and complex algorithms in traditional arc fault detection methods, and saving computing power resources of the power system.

[0059] It should be noted that the current sampling period can be understood as the sampling time spent collecting the current timing array at the preset sampling frequency, wherein the preset sampling frequency can be customized according to application requirements, and this application does not impose any restrictions here. The current timing array can be understood as a number of current timing signals collected from the start time node to the end time node of the sampling time.

[0060] In a specific embodiment, after determining that the sampling initialization of the ADC sampling module is completed, that is, when determining that the ADC sampling module is in the ADC sampling start-up state, the current signal on the power supply circuit from the power system to the load is sampled and recorded through the ADC sampling module, and a one-dimensional timing array Sn (i.e., a current timing array) is defined to store a number of current timing signals collected by the ADC sampling module at a preset sampling frequency. Exemplarily, if the preset sampling frequency is 40Khz, the ADC sampling module collects a current timing signal with a data volume (i.e., the number of current samplings) of n=3200 at 40Khz. Among them, n=3200 current timing signals are 4 complete current cycles, Figure 2 The figure shows the normal current waveform of n=3200 current timing signals. Figure 3 Shown is the fault arc current waveform of n=3200 current timing signals.

[0061] Step S20: determining a current mutation coefficient of the power system according to the current time series array and a preset current effective value, and performing arc fault detection on the power system according to the current mutation coefficient.

[0062] In this embodiment, the mean value processing is performed according to the number of current samples collected by the current timing array and the ADC sampling module at a preset sampling frequency, so that the current signal mean value between each current timing signal can be accurately obtained; next, the current signal mean value is judged by the preset current effective value, and after determining that the current signal mean value is greater than or equal to the preset current effective value, it is determined that the power system is in the power supply state, and the current jump degree of the power system in the power supply state is determined according to the current timing array; next, the current mutation coefficient of the power system is obtained according to the current jump degree. Since the current mutation coefficient can accurately reflect the severity of the current fluctuation in timing, the arc fault of the power system can be efficiently detected based on the current mutation coefficient, which can effectively prevent the arc fault false alarm and missed alarm caused by the comparison of the parameter value obtained by multi-parameter monitoring with the static threshold, thereby significantly enhancing the accuracy of fault arc detection.

[0063] In summary, the present application provides a fault arc detection method that optimizes the traditional arc fault detection technology in a targeted manner, significantly improving the accuracy of fault arc detection. Specifically, the fault arc detection method provided in the present application obtains the current time series array of the power system in the current sampling period, and accurately obtains the current mutation coefficient of the power system based on the current time series array and the preset current effective value, thereby avoiding the computing power consumption caused by multi-parameter monitoring and complex algorithms in the traditional arc fault detection method; next, since the current mutation coefficient can accurately reflect the severity of the current fluctuation in time series, the arc fault of the power system can be efficiently detected based on the current mutation coefficient, which can effectively prevent the arc fault false alarm and omission caused by the comparison of the parameter values ​​obtained by multi-parameter monitoring with the static threshold, thereby significantly enhancing the accuracy of fault arc detection.

[0064] Further, based on the first embodiment of the arc fault detection method of the present application, a second embodiment of the arc fault detection method of the present application is proposed. In some feasible embodiments, the current time series array includes a plurality of current time series signals arranged in chronological order, and the above step S20: determining the current mutation coefficient of the power system according to the current time series array and the preset current effective value, also includes the following implementation steps S201 to S203.

[0065] Step S201 : accumulating total current signal values ​​between the current time series signals, and determining a current signal average value according to a preset total current signal value and the number of current samplings of the current time series array.

[0066] In this embodiment, the total value of the current signal between each current timing signal is accumulated, and the total value of the current signal and the number of current samples in the current timing array are calculated according to a preset mean processing algorithm. The mean value of the current signal can be accurately calculated to provide accurate and reliable data support for subsequent evaluation of whether the power system is in a power supply state.

[0067] It should be noted that the preset mean processing algorithm is shown in the following formula (1).

[0068]

[0069] in, represents the total value of the current signal accumulated between each current timing signal; n represents the number of current sampling; Sn represents the current timing array, which includes multiple current timing signals arranged in chronological order.

[0070] Step S202: after determining that the current signal mean value is greater than or equal to a preset current effective value, determining the current jump degree of the power system according to the current jump value corresponding to the target timing signal, wherein the target timing signal is any one of the multiple current timing signals.

[0071] In this embodiment, after determining that the mean value of the current signal is greater than or equal to the preset current effective value, it is determined that the power system is in a power supply state, and the target timing signal in the current timing array is calculated according to the preset jump degree solution algorithm, so that the current jump value corresponding to the target timing signal can be accurately calculated; next, the current jump degree of the power system in the power supply state can be accurately obtained according to the current jump value corresponding to the target timing signal.

[0072] It should be noted that the target timing signal is any one of the multiple current timing signals. The preset jump degree solution algorithm is shown in the following formula (2).

[0073] K i =[(S i+1 +S i+2 +S i+3 )-3S i ] / S t ...Formula (2)

[0074] Among them, Ki can be understood as the current jump value corresponding to the target timing signal; S i It can be understood as the target timing signal, that is, the i-th current timing signal; S i+1 It can be understood as the i+1th current timing signal; S i+2 It can be understood as the i+2th current timing signal; S i+3 It can be understood as the i+3th current timing signal; S t It can be understood as the sampling interval of the current timing array. The sampling interval can be understood as the time interval between each current timing signal and the next current timing signal. For example, the time interval between each current timing signal and the next current timing signal under the preset sampling frequency of 40 kHz is 0.0025 seconds; (S i+1 +S i+2 +S i+3 ) can be understood as the current sum value between three consecutive current timing signals after the target timing signal (i.e., the current signal sum value), and (S i+1 +S i+2 +S i+3 ) is only a feasible implementation mode of the present application, that is, the number of timing signals after the target timing signal in (*) can be customized according to application requirements, which can be (S i+1 +Si+2 +S i+3 +S i+4 ) or (S i+1 +S i+2 ), etc., this application does not impose any limitation here.

[0075] Step S203: determining a current mutation coefficient of the power system according to the current jump degree.

[0076] Based on the degree of current jump, the current mutation coefficient of the power system can be accurately obtained, avoiding the computing power consumption caused by the complex algorithm corresponding to multiple parameters in the traditional arc fault detection method; next, since the current mutation coefficient can accurately reflect the severity of the current fluctuation in time series, efficient detection of arc faults in the power system is carried out based on the current mutation coefficient, which can effectively prevent the false alarm and omission of arc faults caused by the comparison of parameter values ​​obtained by multi-parameter monitoring with static thresholds, thereby significantly enhancing the accuracy of fault arc detection.

[0077] Furthermore, in some feasible embodiments, the above step S202: determining the current jump degree of the power system according to the current jump value corresponding to the target timing signal, further includes the following implementation steps S2021-S2023:

[0078] Step S2021: obtaining a current jump value corresponding to a target timing signal;

[0079] In this embodiment, after calculating the target timing signal according to the preset jump degree solution algorithm, the current jump value corresponding to the target timing signal can be accurately obtained. The current jump reflects the large fluctuation of the target timing signal within the current timing node and is an important indicator for evaluating whether there is a fault arc current in the power system.

[0080] Step S2022: taking the current timing signal after the target timing signal as the next target timing signal, returning to execute the step of obtaining the current jump value corresponding to the target timing signal, and accumulating the signal accumulation number of the target timing signal;

[0081] In this embodiment, the current timing signal after the target timing signal is taken as the next target timing signal, and the step of obtaining the current jump value corresponding to the target timing signal is returned to be executed, and the cumulative number of signals of the target timing signal is accumulated. That is to say, the current timing signals in the current timing array are traversed one by one in chronological order, that is, each current timing signal in the current timing array is set as the target timing signal in chronological order, and the step of obtaining the current jump value corresponding to the target timing signal is executed, and the number of processed target timing signals (that is, the cumulative number of signals) is accumulated, so that the fluctuation corresponding to each current timing signal can be fully evaluated.

[0082] Step S2023: until the accumulated number of signals reaches the difference between the current sampling number and the preset signal number, determine that the accumulated number of signals is the valid signal number of the current timing array, and use the current jump value corresponding to the target timing signal of the valid signal number as the current jump degree of the power system.

[0083] In this embodiment, since the preset signal number refers to the number of timing signals corresponding to the continuous timing signals after the target timing signal, the difference number between the current sampling number and the preset signal number is determined, and after it is detected that the cumulative number of signals reaches the difference number, the cumulative number of signals is determined to be the number of valid signals in the current timing array, and the current jump value corresponding to the target timing signal of the valid signal number is used as the current jump degree of the power system, which not only accurately reflects the current fluctuation of the power system, but also provides reliable data support for subsequent fault arc detection.

[0084] Exemplarily, since the ADC sampling module collects n=3200 current time series signals at 40Khz (i.e., the number of current samples), the current time series array includes 3200 current time series signals arranged in chronological order, and according to the preset jump degree solution algorithm, it can be known that the number of time series signals after the target time series signal is 3. Specifically, the jump degree solution calculation is performed on the 3200 current time series signals according to the preset jump degree solution algorithm, and the current jump value corresponding to the i=3197 current time series signals arranged in chronological order is calculated as the current jump degree of the power system, where, Figure 4 The figure shows the normal current solution K i Graphic, Figure 5 The figure shows the arc fault solution K i Picture.

[0085] Furthermore, in some feasible embodiments, the above step S2021: obtaining the current jump value corresponding to the target timing signal, also includes the following implementation steps A10 to A30.

[0086] Step A10: determining a continuous timing signal after the target timing signal, and performing summation processing according to each of the current timing signals in the continuous timing signal to obtain a current signal sum value.

[0087] Step A20: Determine that the preset signal quantity is the number of timing signals corresponding to the continuous timing signal, and use the number of timing signals as a product multiple of the target timing signal to obtain a current product value of the target timing signal;

[0088] Step A30: determining a current jump value corresponding to the target timing signal according to a current difference between the current signal sum value and the current product value, and a sampling interval of the current timing array.

[0089] In this embodiment, after determining the continuous timing signals after the target timing signal, the current sum value of the continuous timing signals after the target timing signal is obtained by calculation, and the current product value of the target timing signal is obtained by taking the number of timing signals corresponding to the continuous timing signals as the product multiple of the target timing signal, the current difference between the current signal sum value and the current product value is determined, and based on the proportional data between the current difference value and the sampling interval time of the current timing array, the current jump value corresponding to the target timing signal can be accurately obtained, which significantly improves the accuracy of the current jump value calculation, and thus the current jump degree of the power system can be accurately fed back in real time.

[0090] Furthermore, in some other feasible embodiments, the above step S203: determining the current mutation coefficient of the power system according to the current jump degree, may also include the following implementation steps S2031 to S2032.

[0091] Step S2031: determining the number of valid signals of the current timing array, wherein the current jump degree is a current jump value corresponding to the target timing signal of the number of valid signals;

[0092] Step S2032: performing summation processing according to the current jump values ​​corresponding to the target timing signals to obtain a total current jump value, and determining a current jump mean value according to the total current jump value and the number of valid signals.

[0093] In this embodiment, after determining that the current jump degree is the current jump value corresponding to the target timing signal of the number of valid signals in the current timing array, the current jump values ​​corresponding to each target timing signal are summed up to obtain the total current jump value, and the total current jump value and the number of valid signals are averaged according to a preset jump mean solution algorithm to accurately obtain the current jump mean.

[0094] It should be noted that the preset jump mean solution algorithm is shown in the following formula (3).

[0095]

[0096] Where i is the number of valid signals in the current timing array; is the total current jump value, Ki is the current jump value corresponding to the i-th current timing signal (ie, the target timing signal), and P is the current jump mean value.

[0097] Step S2033: accumulating the current jump difference between the current jump value corresponding to each of the target timing signals and the current jump mean value to obtain the current mutation coefficient of the power system.

[0098] In this embodiment, jump feature extraction is performed on the current jump difference between the current jump value corresponding to each target timing signal and the current jump mean according to a preset jump feature algorithm to obtain the jump difference feature corresponding to each target timing signal; next, the jump difference feature corresponding to each target timing signal is accumulated according to the preset mutation coefficient algorithm to accurately obtain the current mutation coefficient of the power system.

[0099] It should be noted that the preset jump feature algorithm is shown in the following formula (4).

[0100] X i =Sign(K i -P)......Formula (4)

[0101] Wherein, Ki is the current jump value corresponding to the i-th current timing signal (i.e., the target timing signal); P is the current jump mean; X i is the jump difference feature corresponding to each target timing signal, that is, the jump difference feature corresponding to the i-th current timing signal, where: Figure 6 This is the normal current Xi diagram, that is Figure 6 The current mutation coefficient is -101. Figure 7 is the fault arc Xi diagram, that is Figure 7 The data coefficient current mutation coefficient shown is -297.

[0102] The preset mutation coefficient algorithm is shown in the following formula (5).

[0103] T=(X1+X2+···+X i )......Formula (5)

[0104] Among them, T is the current mutation coefficient of the power system, X i is the jump difference feature corresponding to the i-th current timing signal, X1 is the jump difference feature corresponding to the first current timing signal, and X2 is the jump difference feature corresponding to the second current timing signal.

[0105] Furthermore, in some feasible embodiments, the above step S30: the step of performing arc fault detection on the power system according to the current mutation coefficient, may also include the following implementation steps S301 to S304.

[0106] Step S301: store the current mutation coefficient as the current mutation coefficient of the current sampling period, obtain the current timing array of the next sampling period of the current sampling period, return to execute the step of determining the current mutation coefficient of the power system based on the current timing array and the preset current effective value, and obtain the target mutation coefficient of the next sampling period of the current sampling period.

[0107] In this embodiment, the current mutation coefficient is stored as the current mutation coefficient of the current sampling cycle, and the current time series array of the next sampling cycle of the current sampling cycle is obtained, and the step of determining the current mutation coefficient of the power system according to the current time series array and the preset current effective value is returned to obtain the target mutation coefficient of the next sampling cycle of the current sampling cycle. Exemplarily, after the current mutation coefficient T is stored as the current mutation coefficient T1 of the current sampling cycle, the current time series array of the next sampling cycle of the current sampling cycle is obtained, and the step of determining the current mutation coefficient of the power system according to the current time series array and the preset current effective value is returned to obtain the current mutation coefficient T of the next sampling cycle of the current sampling cycle, and the current mutation coefficient T of the next sampling cycle of the current sampling cycle is used as the target mutation coefficient T2, thereby providing accurate and reliable current mutation coefficient T1 and target mutation coefficient T2 for subsequent arc fault detection.

[0108] Step S302: determining the absolute difference between the target mutation coefficient and the current mutation coefficient, and detecting whether the absolute difference exceeds a preset arc occurrence threshold.

[0109] It should be noted that the preset arc occurrence threshold can be customized according to application requirements, and this application does not impose any restrictions here.

[0110] In this embodiment, by comparing the difference in mutation coefficients between the current cycle and the next cycle, that is, calculating the absolute difference in mutation between the target mutation coefficient and the current mutation coefficient, it is detected whether the absolute difference in mutation exceeds the preset arc occurrence threshold, thereby achieving accurate detection of arc faults in the power system.

[0111] Step S303: If the sudden change absolute difference exceeds the arc occurrence threshold, it is determined that an arc fault occurs in the power system.

[0112] In this embodiment, when it is detected that the mutation absolute difference exceeds the preset arc occurrence threshold, the power system is triggered to quickly respond to the detection result that the mutation absolute difference is greater than the arc occurrence threshold, and accurately determine that an arc fault has occurred in itself, thereby effectively improving the safety monitoring level and fault response speed of the power system.

[0113] Step S304: If the sudden change absolute difference does not exceed the arc occurrence threshold, it is determined that no arc fault occurs in the power system.

[0114] In this embodiment, if the mutation absolute difference does not exceed the preset arc occurrence threshold, it can be determined that no fault occurs in the power system, thereby ensuring the accuracy and reliability of fault arc detection.

[0115] Further, in some feasible embodiments, after the above step S304: determining that no arc fault occurs in the power system, the arc fault detection method may further include the following implementation step B10.

[0116] Step B10: taking the next sampling cycle of the current sampling cycle as the next current sampling cycle, and taking the target mutation coefficient as the current mutation coefficient of the next current sampling cycle, and returning to execute the step of obtaining the current timing array of the next sampling cycle of the current sampling cycle.

[0117] In this embodiment, after determining that no arc fault has occurred in the current power system, a very clever strategy is adopted to continuously monitor the state of the system. Specifically, the next sampling period of the current sampling period is set as the new current sampling period, and the target mutation coefficient calculated previously is used as the current mutation coefficient of the new period (i.e., the new current sampling period). Then, the step of obtaining the current timing array of the next sampling period of the current sampling period is returned to continue monitoring the current state of the power system. This cyclic monitoring mechanism not only ensures the real-time update of the power system state, but also greatly improves the accuracy and timeliness of arc fault detection. By continuously iterating this process, the system can continuously track the current changes of the power system, and once any abnormality or potential fault is detected, it can respond quickly, thereby significantly improving the accuracy of fault arc detection and effectively ensuring the safe and stable operation of the power system.

[0118] Further, in another embodiment, referring to Figure 8 , Figure 8 It is a schematic diagram of the detection process involved in an embodiment of the fault arc detection method of the present application. Figure 8 The process steps shown include step A to step J.

[0119] Step A: First, the sampling of the ADC sampling module is initialized, mainly including ADC sampling startup.

[0120] Step B, sample and record the current signal on the power supply circuit from the power system to the load, define a current signal sampling one-dimensional array (i.e., current time series array) Sn, and if the preset sampling frequency is 40Khz, collect current sampling number (n=3200 current time series signals).

[0121] Step C: judge the current signal mean value I of the current timing array Sn. When the current signal mean value I is greater than or equal to the preset current effective value Z, proceed to step D. If the current signal mean value I is less than the preset current effective value Z, return to step B and perform sampling again. Where n = 3200).

[0122] Step D: If the current signal mean value I is greater than or equal to the preset current effective value Z, the current time series array Sn is further transformed and solved, and the formula is K i =[(S i+1 +S i+2 +S i+3 )-3S i ] / S t , where S t It can be understood as the sampling interval of the current timing array. The sampling interval can be understood as the time interval between each current timing signal and the next current timing signal. At 40 kHz, St = 0.0025 seconds. After conversion and solution, K with i = 3197 data is formed. i .

[0123] Step E: After step D, calculate the current jump mean value P1 and the current mutation coefficient T1 of the current cycle, and the solution formula is: Wherein i=3197, the current mutation coefficient T1 calculation formula is Xi=Sign(Ki-P1), T1=(X1+X2+···+Xi); after calculating the current mutation coefficient T1, record it and keep it.

[0124] Step F: Enter the next round of current signal acquisition, the current sampling quantity and sampling frequency are the same as step B.

[0125] Step G: Determine the current signal mean value I of the current timing array Sn in the next sampling cycle of the current sampling cycle. When the current signal mean value I is greater than or equal to the preset current effective value Z, proceed to the next step H. If it is less than the preset current effective value Z, return to step B to resample and record T1.

[0126] Step H: If it is greater than or equal to, the current timing array Sn of the next sampling cycle of the current sampling cycle is further transformed and solved. The formula is K i =[(S i+1 +S i+2 +S i+3 )-3S i ] / S t , where S tIt can be understood as the sampling interval of the current timing array. The sampling interval can be understood as the time interval between each current timing signal and the next current timing signal. At 40 kHz, St = 0.0025 seconds. After conversion and solution, K with i = 3197 data is formed. i .

[0127] Step I: After solving the H-step, calculate the average value P2 of the next sampling period of the current sampling period and the target mutation coefficient T2. The solution formula is: Wherein i=3197, the current mutation coefficient T1 calculation formula is Xi=Sign(Ki-P2), T2=(X1+X2+···+Xi); after calculating the target mutation coefficient T2, record it and keep it.

[0128] Step J, compare the absolute value of the difference between T1 and T2. When |T2-T1|>Y (the set value Y is the preset arc occurrence threshold), it is determined that an arc has occurred. If the |T2-T1| value is not greater than the set value Y, the T2 value is assigned to T1, and then step F and subsequent steps are executed, and the absolute value of the difference between T1 and T2 is continued to be compared until the end of the arc is detected.

[0129] In summary, the present application provides a fault arc detection method that optimizes the traditional arc fault detection technology in a targeted manner, significantly improving the accuracy of fault arc detection. Specifically, the present application uses a one-dimensional current time series array Sn to calculate the current mutation coefficient. When an arc occurs, the current mutation coefficient will increase significantly, and a more precise fault arc occurrence judgment will be performed. Compared with the traditional real-time Fourier decomposition threshold judgment and wavelet decomposition judgment, it effectively reduces the computing power requirements and improves the accuracy of fault arc identification.

[0130] In addition, the present application also provides a fault arc detection device, please refer to Fig. 9 , Fig. 9 Schematic diagram of the structure of the arc fault detection device involved in the embodiment of the present application. The arc fault detection device provided in the present application includes:

[0131] The acquisition module H01 is used to obtain the current time series array of the power system in the current sampling period;

[0132] The detection module H02 is used to determine the current mutation coefficient of the power system according to the current time series array and the preset current effective value, and perform arc fault detection on the power system according to the current mutation coefficient.

[0133] In addition, the present application also provides a fault arc detection device. Fig.10 , Fig.10The schematic diagram of the structure of the arc fault detection device involved in the embodiment of the present application is shown in FIG. The device in the embodiment of the present application may be a device for locally running the arc fault detection method.

[0134] The present application provides a fault arc detection device, which includes: at least one processor; and a memory that is communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the fault arc detection device method in the above-mentioned embodiment 1.

[0135] Reference below Fig.10 , which shows a schematic diagram of the structure of a fault arc detection device suitable for implementing the embodiment of the present application. The fault arc detection device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The arc fault detection device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0136] like Fig.10As shown, the arc fault detection device may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the arc fault detection device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following devices can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the arc fault detection device to communicate with other devices wirelessly or by wire to exchange data. Although the arc fault detection device with various devices is shown in the figure, it should be understood that it is not required to implement or have all the devices shown. More or fewer devices can be implemented or have alternatively.

[0137] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0138] The arc fault detection device provided by the present application adopts the arc fault detection device method in the above embodiment, which can solve the technical problem of low reliability of the arc fault detection device. Compared with the prior art, the beneficial effects of the arc fault detection device provided by the present application are the same as the beneficial effects of the arc fault detection device method provided by the above embodiment, and other technical features in the arc fault detection device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0139] In addition, the present application provides a computer-readable storage medium on which a fault arc detection program is stored, and when the fault arc detection program is executed by a processor, the steps of the above-mentioned fault arc detection method are implemented.

[0140] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0141] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0142] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0143] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A fault arc detection method, characterized in that: The arc fault detection method comprises: Obtain the current time series array of the power system in the current sampling period; A current mutation coefficient of the power system is determined according to the current time series array and a preset current effective value, and arc fault detection is performed on the power system according to the current mutation coefficient.

2. The arc fault detection method according to claim 1, characterized in that: The current time series array includes a plurality of current time series signals arranged in chronological order, and the step of determining the current mutation coefficient of the power system according to the current time series array and a preset current effective value includes: Accumulating total current signal values ​​between the current time series signals, and determining a current signal mean value according to the total current signal value and the number of current samplings of the current time series array; After determining that the current signal mean value is greater than or equal to a preset current effective value, determining the current jump degree of the power system according to the current jump value corresponding to the target time sequence signal, wherein the target time sequence signal is any one of the multiple current time sequence signals; The current mutation coefficient of the power system is determined according to the current jump degree.

3. The arc fault detection method according to claim 2, characterized in that: The step of determining the current jump degree of the power system according to the current jump value corresponding to the target timing signal comprises: Obtaining a current jump value corresponding to a target timing signal; Taking the current timing signal after the target timing signal as the next target timing signal, returning to execute the step of obtaining the current jump value corresponding to the target timing signal, and accumulating the signal accumulation number of the target timing signal; Until the accumulated number of signals reaches the difference between the current sampling number and the preset signal number, the accumulated number of signals is determined to be the valid signal number of the current timing array, and the current jump value corresponding to the target timing signal of the valid signal number is used as the current jump degree of the power system.

4. The arc fault detection method according to claim 3, characterized in that: The step of obtaining the current jump value corresponding to the target timing signal comprises: Determine a continuous time sequence signal after the target time sequence signal, and perform sum processing according to each of the current time sequence signals in the continuous time sequence signal to obtain a current signal sum value; Determine the preset signal quantity as the number of timing signals corresponding to the continuous timing signal, take the number of timing signals as the product multiple of the target timing signal, and obtain the current product value of the target timing signal; The current jump value corresponding to the target timing signal is determined according to the current difference between the current signal sum value and the current product value, and the sampling interval time of the current timing array.

5. The arc fault detection method according to claim 2, characterized in that: The step of determining the current mutation coefficient of the power system according to the current jump degree comprises: Determine the number of valid signals of the current timing array, the current jump degree being the current jump value corresponding to the target timing signal of the number of valid signals; Performing summation processing according to the current jump values ​​corresponding to the target timing signals to obtain a total current jump value, and determining a current jump mean value according to the total current jump value and the number of valid signals; The current jump difference between the current jump value corresponding to each of the target time sequence signals and the current jump mean is accumulated to obtain the current mutation coefficient of the power system.

6. The arc fault detection method according to claim 1, characterized in that: The step of performing arc fault detection on the power system according to the current mutation coefficient comprises: The current mutation coefficient is stored as the current mutation coefficient of the current sampling period, and the current time series array of the next sampling period of the current sampling period is obtained, and the step of determining the current mutation coefficient of the power system according to the current time series array and the preset current effective value is returned to obtain the target mutation coefficient of the next sampling period of the current sampling period; Determine a mutation absolute difference between the target mutation coefficient and the current mutation coefficient, and detect whether the mutation absolute difference exceeds a preset arc occurrence threshold; If the mutation absolute difference exceeds the arc occurrence threshold, it is determined that an arc fault occurs in the power system; If the sudden change absolute difference does not exceed the arc occurrence threshold, it is determined that no arc fault occurs in the power system.

7. The arc fault detection method according to claim 6, characterized in that: After determining that no arc fault occurs in the power system, the arc fault detection method includes: The next sampling cycle of the current sampling cycle is used as the next current sampling cycle, and the target mutation coefficient is used as the current mutation coefficient of the next current sampling cycle, and the step of obtaining the current timing array of the next sampling cycle of the current sampling cycle is returned to be executed.

8. A fault arc detection device, characterized in that: The arc fault detection device comprises: An acquisition module, used for acquiring a current time series array of the power system in a current sampling period; The detection module is used to determine the current mutation coefficient of the power system according to the current time series array and a preset current effective value, and perform arc fault detection on the power system according to the current mutation coefficient.

9. A fault arc detection device, characterized in that: The arc fault detection device includes a memory, a processor, and an arc fault detection program stored in the memory and executable on the processor. When the processor executes the arc fault detection program, the steps of the arc fault detection method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an arc fault detection program, and when the arc fault detection program is executed by a processor, the steps of the arc fault detection method according to any one of claims 1 to 7 are implemented.

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