Arc fault detection method and device, electronic device and storage medium

Abstract

The embodiment of the invention provides an arc fault detection method and equipment, electronic equipment and a storage medium, and relates to the technical field of power system fault detection. The method comprises the following steps: carrying out current sampling on a target power system to obtain a target three-phase current signal; performing wavelet signal analysis based on the target three-phase current signal to obtain a current transient high-frequency component; performing negative sequence component calculation based on the target three-phase current signal to obtain a three-phase current negative sequence component; performing component fusion based on the three-phase current negative-sequence component and the current transient high-frequency component to generate a current negative-sequence break variable; and carrying out threshold comparison based on the current negative sequence break variable so as to carry out fault detection on the target power system. According to the embodiment of the invention, the timeliness and sensitivity of arc fault detection can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system fault detection, and in particular to an arc fault detection method and device, an electronic device, and a storage medium. BACKGROUND

[0002] In power equipment and power systems (such as distribution boxes and power grids), arc faults are one of the main causes of equipment damage and system failure. When an arc fault occurs in power equipment or a power system, a high-temperature arc flame can be generated, which can cause a fire or even an explosion. The occurrence of an arc fault is usually accompanied by the generation of a transient high-frequency current pulse, such as a high-frequency current pulse that lasts only a few milliseconds. However, current arc fault detection methods mainly rely on steady-state feature analysis, and are slow to respond to transient features such as high-frequency current pulses, making it difficult to detect arc faults in a timely manner.

[0003] Therefore, how to improve the timeliness and sensitivity of arc fault detection has become a technical problem to be solved. SUMMARY

[0004] The main purpose of the embodiments of the present application is to propose an arc fault detection method and device, an electronic device, and a storage medium, which aims to improve the timeliness and sensitivity of arc fault detection and achieve early warning of arc faults.

[0005] To achieve the above-mentioned purpose, a first aspect of the embodiments of the present application proposes an arc fault detection method, which comprises:

[0006] sampling a current of a target power system to obtain a target three-phase current signal;

[0007] performing wavelet signal analysis based on the target three-phase current signal to obtain a current transient high-frequency component;

[0008] performing negative sequence component calculation based on the target three-phase current signal to obtain a three-phase current negative sequence component;

[0009] performing component fusion based on the three-phase current negative sequence component and the current transient high-frequency component to generate a current negative sequence mutation variable;

[0010] performing threshold comparison based on the current negative sequence mutation variable to detect a fault of the target power system.

[0011] In some embodiments, the target three-phase current signal is a plurality of target three-phase current signals, each target three-phase current signal corresponds to a sampling time point, and the target three-phase current signal at each sampling time point corresponds to a current transient high-frequency component and a three-phase current negative sequence component;

[0012] The component fusion based on the three-phase current negative sequence component and the current transient high-frequency component generates a current negative sequence mutation variable, and the component fusion includes:

[0013] For each sampling time point in the same current sampling period, time domain convolution calculation is performed based on the three-phase current negative sequence component of the sampling time point and the current transient high-frequency component of each sampling time point before the sampling time point to obtain a convolution negative sequence component.

[0014] Based on the convolution negative sequence component of each sampling time point, the current negative sequence mutation variable is determined.

[0015] In some embodiments, the current sampling period is multiple;

[0016] The determination of the current negative sequence mutation variable based on the convolution negative sequence component of each sampling time point includes:

[0017] Based on the time interval between adjacent sampling time points, a current mutation time length is determined; wherein the current mutation time length is less than or equal to the time interval;

[0018] For each current sampling period, differential calculation is performed based on the change value of the convolution negative sequence component within the current mutation time length in the same current sampling period and the current mutation time length to obtain the current negative sequence mutation variable corresponding to each current sampling period.

[0019] In some embodiments, the threshold comparison based on the current negative sequence mutation variable to detect faults of the target power system includes:

[0020] Based on the current negative sequence mutation variable of each current sampling period in adjacent N current sampling periods and a preset current rise rate threshold, threshold comparison is performed; wherein N is a positive integer;

[0021] If the current negative sequence mutation variable of each current sampling period in adjacent N current sampling periods is greater than the current rise rate threshold, it is determined that the target power system has an arc fault.

[0022] In some embodiments, the wavelet signal analysis based on the target three-phase current signal to obtain a current transient high-frequency component includes:

[0023] A multi-layer wavelet decomposition of the target three-phase current signal is performed through a Mallat decomposition algorithm to obtain a plurality of current high-frequency detail coefficients;

[0024] Wavelet reconstruction is performed on the plurality of current high-frequency detail coefficients through a Mallat reconstruction algorithm to obtain the current transient high-frequency component.

[0025] In some embodiments, the negative sequence component calculation based on the target three-phase current signal comprises:

[0026] performing coordinate system transformation on the target three-phase current signal to obtain a two-phase current signal; wherein the two-phase current signal comprises a first two-phase current component and a second two-phase current component;

[0027] performing orthogonal phase shift on the first two-phase current component to obtain a first orthogonal current component, and performing orthogonal phase shift on the second two-phase current component to obtain a second orthogonal current component;

[0028] determining a first initial negative sequence component based on the first two-phase current component and the first orthogonal current component, and determining a second initial negative sequence component based on the second two-phase current component and the second orthogonal current component;

[0029] determining a two-phase negative sequence component by combining the first initial negative sequence component and the second initial negative sequence component, and performing inverse coordinate system transformation on the two-phase negative sequence component to obtain the three-phase current negative sequence component.

[0030] In some embodiments, the current sampling on the target power system to obtain a target three-phase current signal comprises:

[0031] selecting, based on a preset arc current frequency threshold, a candidate sampling frequency greater than a preset multiple of the arc current frequency threshold from a plurality of preset candidate sampling frequencies to obtain a target sampling frequency;

[0032] sampling the current of the target power system according to the target sampling frequency to obtain an original three-phase current signal;

[0033] determining the arc current frequency threshold as a cutoff frequency, and performing low-pass filtering on the original three-phase current signal based on the cutoff frequency to obtain the target three-phase current signal.

[0034] In some embodiments, after the threshold comparison between the current negative sequence abrupt change variable of each of the N adjacent current sampling periods and the preset current rise rate threshold, the method further comprises:

[0035] if the current negative sequence abrupt change variable of each of the N adjacent current sampling periods is greater than the current rise rate threshold, then performing incremental calculation on the current negative sequence abrupt change variable of each of the two adjacent current sampling periods in the N current sampling periods to obtain N-1 initial negative sequence abrupt change increments;

[0036] If the average value of the N-1 initial negative sequence mutation increments is greater than or equal to a preset current increment threshold, it is determined that an arc fault occurs in the target power system.

[0037] To achieve the above object, a second aspect of the embodiment of the present application provides an arc fault detection device, which is used to execute the method of the first aspect, and the device comprises:

[0038] a current sampling unit, a filtering unit, a digital-to-analog conversion unit and a digital signal processing unit.

[0039] The current sampling unit, the filtering unit, the digital-to-analog conversion unit and the digital signal processing unit are electrically connected in sequence.

[0040] To achieve the above object, a third aspect of the embodiment of the present application provides an electronic device, which comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the method of the first aspect.

[0041] To achieve the above object, a fourth aspect of the embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the method of the first aspect.

[0042] The arc fault detection method and device, the electronic device and the storage medium provided by the present application can extract the instantaneous high-frequency current caused by the transient process such as arc fault by sampling the current of the target power system, obtaining the target three-phase current signal, and performing wavelet signal analysis based on the target three-phase current signal to obtain the current transient high-frequency component. The negative sequence component caused by the fault in the three-phase circuit can be extracted by calculating the negative sequence component based on the target three-phase current signal to determine whether there is a fault in the target power system. Then, the current negative sequence mutation variable is generated by component fusion based on the three-phase current negative sequence component and the current transient high-frequency component, so that the instantaneous change characteristics of the current negative sequence component can be accurately captured to reflect the arc fault, so that the arc fault can be detected in time, the timeliness and sensitivity of the arc fault detection are improved, and the early warning of the arc fault is realized. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 is a flowchart of the arc fault detection method provided by the present application;

[0044] Figure 2 is a flowchart of step 101 in Figure 1

[0045] Figure 3 ​is a flowchart of step 102 in Figure 1

[0046] Figure 4 is a flowchart of step 103 in Figure 1

[0047] Figure 5 is a system block diagram of a second-order generalized integrator;

[0048] Figure 6 is a system block diagram of a calculation process of negative sequence component calculation;

[0049] Figure 7 is a flowchart of step 104 in Figure 1

[0050] Figure 8 is a flowchart of step 502 in Figure 7

[0051] Figure 9 is a flowchart of step 105 in Figure 1

[0052] Figure 10 is a flowchart of an application example provided by the embodiments of the present application;

[0053] Figure 11 is a structural schematic diagram of an arc fault detection device provided by the embodiments of the present application;

[0054] Figure 12 is a hardware structural schematic diagram of an electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0055] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0056] It should be noted that although the functional modules are divided in the device schematic diagram, and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a manner different from the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification and claims and the above-described drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application, and are not intended to limit the present application. ​​​​​

[0058] First, the terms involved in this application are analyzed:

[0059] Arc fault: refers to the gas ionization discharge phenomenon caused by insulation damage, poor contact or environmental factors in the power system. Arc fault may cause electrical fire, equipment damage and other hazards.

[0060] The arc fault detection method and device, electronic device and storage medium provided by the embodiments of the application are specifically described as follows. First, the arc fault detection method in the embodiments of the application is described.

[0061] Figure 1 is an optional flowchart of the arc fault detection method provided by the embodiments of the application, Figure 1 The method in the method can include but is not limited to steps 101-105.

[0062] Step 101, current sampling is performed on the target power system to obtain a target three-phase current signal;

[0063] Step 102, wavelet signal analysis is performed based on the target three-phase current signal to obtain a current transient high-frequency component;

[0064] Step 103, negative sequence component calculation is performed based on the target three-phase current signal to obtain a three-phase current negative sequence component;

[0065] Step 104, component fusion is performed based on the three-phase current negative sequence component and the current transient high-frequency component to generate a current negative sequence mutation variable;

[0066] Step 105, threshold comparison is performed based on the current negative sequence mutation variable to detect the fault of the target power system.

[0067] The beneficial effects of the embodiments of the application include but are not limited to: by sampling the current of the target power system to obtain a target three-phase current signal, and performing wavelet signal analysis based on the target three-phase current signal to obtain a current transient high-frequency component, the instantaneous high-frequency current caused by the transient process such as arc fault can be extracted for subsequent fault detection. Based on the target three-phase current signal, the negative sequence component calculation is performed to obtain a three-phase current negative sequence component, which can extract the negative sequence component caused by the fault in the three-phase circuit to determine whether there is a fault in the target power system. Then, based on the three-phase current negative sequence component and the current transient high-frequency component, the component fusion is performed to generate a current negative sequence mutation variable, which can accurately capture the instantaneous change characteristics of the current negative sequence component to reflect the arc fault, so as to timely detect the arc fault, improve the timeliness and sensitivity of the arc fault detection, and realize the early warning of the arc fault.

[0068] In step 101 of some embodiments, the target power system refers to a power system in which arc fault needs to be detected. Specifically, the target power system can be a power grid. In another embodiment, any power device in the target power system can also be current sampled to detect arc fault, for example, any one of the power devices including a generator, a distribution box, and the like.

[0069] It should be noted that the current in the target power system is a three-phase alternating current. The target three-phase current signal is a three-phase current signal sampled from the target power system. In some embodiments, the target power system can be synchronously sampled. It should be noted that synchronous sampling refers to that the sampling frequency is strictly synchronized with the fundamental frequency of the current signal or an integer multiple thereof, so as to ensure that a fixed number of current signals are collected in each period.

[0070] In step 102 of some embodiments, the current transient high-frequency component is a high-frequency component obtained based on wavelet signal analysis of the target three-phase current signal. It should be noted that the transient high-frequency component is a component caused by a sudden event (such as fault, load mutation, etc.) in the power system, and the transient high-frequency component is mainly generated by a transient process.

[0071] In step 103 of some embodiments, the three-phase current negative sequence component is a negative sequence component obtained based on negative sequence component calculation of the target three-phase current signal. It should be noted that the negative sequence component refers to a component with the same amplitude but a phase difference of 120 degrees in the three-phase current. The negative sequence component is often caused by circuit fault, which will cause the operating efficiency of the power system to decrease. By analyzing the negative sequence component, it can be determined whether there is a circuit fault (such as arc fault) in the target power system to take appropriate measures for repair.

[0072] In step 104 of some embodiments, the current negative sequence mutation variable is a current mutation variable obtained by component fusion based on the three-phase current negative sequence component and the current transient high-frequency component. The current negative sequence mutation variable is used to represent the instantaneous change characteristics of the current, such as the change amplitude of the current within 5 microseconds, etc.

[0073] In step 105 of some embodiments, if the current negative sequence mutation variable is greater than or equal to a preset threshold (such as the current rise rate threshold below), it is determined that the target power system has an arc fault. Otherwise, if the current negative sequence mutation variable is less than the preset threshold, it is determined that the target power system does not have an arc fault.

[0074] Please refer to Figure 2 In some embodiments, step 101 can include but is not limited to steps 201 to 203:

[0075] At step 201, based on the preset arc current frequency threshold, a candidate sampling frequency greater than a preset multiple of the arc current frequency threshold is selected from a plurality of preset candidate sampling frequencies, to obtain a target sampling frequency.

[0076] At step 202, the target power system is current-sampled at the target sampling frequency to obtain an original three-phase current signal.

[0077] At step 203, the arc current frequency threshold is determined as a cutoff frequency, and the original three-phase current signal is low-pass filtered based on the cutoff frequency to obtain a target three-phase current signal.

[0078] The embodiment has the advantage that by selecting a candidate sampling frequency greater than a preset multiple (such as 2 times) of the arc current frequency threshold as the target sampling frequency from a plurality of preset candidate sampling frequencies, the sampling frequency condition indicated by the Nyquist theorem is met, signal spectrum aliasing is avoided, and complete capture of high-frequency components of the current signal is ensured. Moreover, the arc current frequency threshold is used as the cutoff frequency to low-pass filter the original three-phase current signal, so that noise and irrelevant high-frequency components higher than the threshold are filtered out, and only effective frequency band signals that can represent arc fault characteristics are retained, so that subsequent more accurate analysis of high-frequency components reflecting arc faults contained in the target three-phase current signal is facilitated, and the accuracy of arc detection is improved.

[0079] In step 201 of some embodiments, the arc current frequency threshold is the highest frequency of the target three-phase current signal, and the preset multiple can be two. It should be noted that the sampling frequency condition indicated by the Nyquist theorem is that in order to restore a continuous signal without distortion, the sampling frequency must be at least twice the highest frequency of the signal.

[0080] Specifically, at the moment of arc fault occurrence (also known as the moment of arc ignition), since the frequency of the high-frequency current pulse generated in the target power system is high, in order to capture the high-frequency components in the current, the Nyquist theorem needs to be met, and the highest frequency of the high-frequency current pulse (i.e., the arc current frequency threshold) is twice the sampling frequency for synchronous sampling of the target power system. For example, assuming that the frequency of the high-frequency current pulse belongs to 1 to 100 kHz (kilohertz), the arc current frequency threshold is 100 kHz, and the target power system needs to be synchronously sampled at a sampling frequency of 200 kHz. In this case, the target sampling frequency is 200 kHz.

[0081] In step 202 of some embodiments, the original three-phase current signal is a three-phase current signal sampled at a target sampling frequency for a target power system. Specifically, the original three-phase current signal at multiple sampling time points can be obtained by sampling the target power system at the target sampling frequency in each current sampling period.

[0082] In step 203 of some embodiments, the original three-phase current signal can be low-pass filtered by a 5th order Butterworth low-pass filter based on a cutoff frequency to obtain a target three-phase current signal, so as to eliminate aliasing noise. The low-pass filtering can also be performed by other types of filters or filtering methods, which are not limited thereto.

[0083] Please refer to Figure 3 In some embodiments, step 102 can include but is not limited to steps 301-302:

[0084] In step 301, the target three-phase current signal is subjected to multi-layer wavelet decomposition by a Mallat decomposition algorithm to obtain multiple current high-frequency detail coefficients.

[0085] In step 302, the multiple current high-frequency detail coefficients are subjected to wavelet reconstruction by a Mallat reconstruction algorithm to obtain a current transient high-frequency component.

[0086] The embodiment has the advantages that the target three-phase current signal is subjected to multi-layer wavelet decomposition by the Mallat decomposition algorithm to obtain multiple current high-frequency detail coefficients, so that the current signal can be separated according to different frequency bands, the high-frequency detail coefficients can represent the instantaneous current mutation characteristics caused by arc fault, and the interference of low-frequency components in the current signal can be suppressed. Then, the multiple current high-frequency detail coefficients are subjected to wavelet reconstruction by the Mallat reconstruction algorithm to obtain the current transient high-frequency component, so that the instantaneous high-frequency current caused by the transient process such as arc fault can be accurately extracted, high-precision input is provided for subsequent arc fault detection, the timeliness and sensitivity of arc fault detection are improved, and early warning of arc fault is realized.

[0087] In step 301 of some embodiments, the target three-phase current signal can be subjected to multi-layer wavelet decomposition by a Mallat algorithm using a db4 wavelet basis function to obtain four current high-frequency detail coefficients. The current high-frequency detail coefficients can include a first detail coefficient d1, a second detail coefficient d2, a third detail coefficient d3, and a fourth detail coefficient d4.

[0088] It should be noted that the wavelet decomposition is a process of decomposing a signal (such as a target three-phase current signal) into approximation coefficients and detail coefficients. The approximation coefficients reflect the overall trend and low-frequency components of the signal, and the detail coefficients reflect the local changes and high-frequency details of the signal. The basis of wavelet decomposition is the wavelet basis function (referred to as wavelet basis). In some embodiments, through simulation experiments, it can be known that the signal-to-noise ratio of the current high-frequency detail coefficients (d1-d4) extracted by the db4 wavelet basis function is significantly higher than that of other wavelet basis functions, so the db4 wavelet is adopted. Since the energy concentration of the arc fault characteristic frequency band (i.e. the frequency band of the current high-frequency detail coefficients) obtained by wavelet decomposition to the 4th layer is the highest (the energy ratio is greater than 85%), and the calculation complexity is controllable (the time consumption of the Mallat reconstruction process is less than or equal to 5 milliseconds), so the wavelet decomposition is set to the 4th layer. In some embodiments, the scale parameter of wavelet decomposition is 16, the frequency resolution is 781 Hz (hertz), and the arc fault characteristic frequency band covered by the current high-frequency detail coefficients (d1-d4) includes 25-100 kHz.

[0089] In step 302 of some embodiments, the plurality of current high-frequency detail coefficients can be wavelet reconstructed by a Mallat reconstruction algorithm. In another embodiment, wavelet reconstruction can also be performed by other types of signal reconstruction algorithms, without limitation.

[0090] Please refer to Figure 4 In some embodiments, step 103 can include but is not limited to steps 401-404:

[0091] Step 401, performing coordinate system transformation on the target three-phase current signal to obtain a two-phase current signal; wherein the two-phase current signal includes a first two-phase current component and a second two-phase current component;

[0092] Step 402, performing orthogonal phase shift on the first two-phase current component to obtain a first orthogonal current component, and performing orthogonal phase shift on the second two-phase current component to obtain a second orthogonal current component;

[0093] Step 403, determining a first initial negative sequence component based on the first two-phase current component and the first orthogonal current component, and determining a second initial negative sequence component based on the second two-phase current component and the second orthogonal current component;

[0094] Step 404, determining a two-phase negative sequence component by combining the first initial negative sequence component and the second initial negative sequence component, and performing coordinate system inverse transformation on the two-phase negative sequence component to obtain a three-phase current negative sequence component.

[0095] The embodiment has the advantages that the two-phase current signals are obtained by performing coordinate system transformation on the target three-phase current signals, so as to reduce the complexity of subsequent operation and reduce signal processing delay. The first two-phase current component and the second two-phase current component in the two-phase current signals are respectively phase-shifted to generate the first quadrature current component and the second quadrature current component, so that the quadrature components required for calculating the negative sequence component can be separated by phase adjustment. The two-phase negative sequence component is determined based on the first two-phase current component, the first quadrature current component, the second two-phase current component and the second quadrature current component, so that the negative sequence component caused by the arc fault can be extracted to determine whether there is a fault in the target power system. The two-phase negative sequence component is transformed into a three-phase current negative sequence component, so that the subsequent fault analysis requirement in the three-phase stationary coordinate system can be adapted, so as to improve the timeliness and sensitivity of arc fault detection and realize early warning of arc fault.

[0096] In step 401 of some embodiments, the target three-phase current signal is a current signal in a three-phase stationary coordinate system. The two-phase current signal is a current signal in a two-phase stationary coordinate system. Specifically, the target three-phase current signal can be transformed by a Clark transformation method.

[0097] In some embodiments, the process of transforming the target three-phase current signal by coordinate system is shown in the following formula:

[0098]

[0099] In the formula, i α represents the first two-phase current component, i β represents the second two-phase current component; i a_f represents the first three-phase current component, i b_f represents the second three-phase current component, and i c_f represents the third three-phase current component. It should be noted that the target three-phase current signal includes the first three-phase current component i a_f , the second three-phase current component i b_f and the third three-phase current component i c_f .

[0100] In step 402 of some embodiments, the quadrature phase shift refers to shifting the phase of the signal by 90 degrees in the time domain. It should be noted that the first two-phase current component and the first quadrature current component are orthogonal to each other, and the second two-phase current component and the second quadrature current component are orthogonal to each other.

[0101] In some embodiments, the first two-phase current component (or the second two-phase current component) can be quadrature phase-shifted by a double second-order generalized integral (DSOGI) method. For example, SOGI (second-order generalized integrator) can be used for quadrature phase shift.

[0102] For example, such as Figure 5 As shown, taking the calculation process of the first orthogonal current component as an example, the first orthogonal current component can be determined by the following formula:

[0103] qi α (k)=i′ α (k-1)*Wn+qi α (k-1),

[0104] In the formula, qi α (k) represents the first orthogonal current component at time point k, qi α (k-1) represents the first orthogonal current component at time point k-1; i α (k-1) represents the first two-phase current components at time point k-1; where q = e -jπ / 2 ,qi α This indicates that the first two-phase current component i in the time domain α Perform a 90° phase shift; Wn represents the natural frequency of the target power system; i′ α (k-1) represents the first two-phase current components at time point k-1. In some embodiments, i′ α (k-1) is defined as shown in the following formula:

[0105] i′ α (k-1)=[2*(i α -i′ α (k-2))-qi α (k-2)]*Wn+i′ α (k-2),

[0106] In the formula, i α This represents the first two-phase current component, specifically the two-phase current component at time point k-1; i′ α (k-2) represents the intermediate current component at time point k-2; qi α (k-2) represents the first orthogonal current component at time point k-2. The meanings of the other parameters can be found in the detailed description of the formula above, and will not be repeated here.

[0107] It should be noted that the calculation process of the second orthogonal current component is similar to that of the first orthogonal current component described above, and will not be repeated here.

[0108] Specifically, in Figure 5In some embodiments, K = 2, Wn= 2 * pi * 50. 1 / s = 1. In some embodiments, i' can represent a first two-phase current component, and qi can represent a first quadrature current component. In another embodiment, i' can represent a second two-phase current component, and qi can represent a second quadrature current component.

[0109] In step 403 of some embodiments, the first initial negative sequence component and the second initial negative sequence component can be determined by the following equations:

[0110]

[0111] wherein, represents the first initial negative sequence component, represents the second initial negative sequence component; i α represents the first two-phase current component; i β represents the second two-phase current component; qi α represents the first quadrature current component; qi β represents the second quadrature current component.

[0112] In step 404 of some embodiments, the two-phase negative sequence component includes the first initial negative sequence component and the second initial negative sequence component. In some embodiments, the two-phase negative sequence component in the two-phase stationary coordinate system can be coordinate-transformed by an inverse Clark transformation method to obtain a three-phase current negative sequence component in the three-phase stationary coordinate system.

[0113] In some embodiments, the process of coordinate-transforming the two-phase negative sequence component is shown in the following equation:

[0114]

[0115] wherein, represents the three-phase current negative sequence component; represents the two-phase negative sequence component, wherein, represents the first initial negative sequence component, represents the second initial negative sequence component.

[0116] In some embodiments, as shown in Figure 6 the first two-phase current component and the second two-phase current component, i.e., Ia and Iβ in Figure 6 , can be obtained by performing a Clark transformation on a target three-phase current signal, i.e., Iabc in Figure 6 . The first quadrature current component, i.e., qIa in Figure 6 , and the first two-phase current component, i.e., Ia in Figure 6Ia') in the second two-phase current component (i.e. Figure 6 qIβ) in the second two-phase current component (i.e. Figure 6 Iβ') in the second two-phase current component. Then, a first initial negative sequence component Ia- and a second initial negative sequence component Iβ- are generated, where Ia- = 1 / 2*(Ia'+qIβ) and Iβ- = 1 / 2*(Iβ'-qIa). Finally, a reverse Clark transformation is performed on the two-phase negative sequence component composed of the first two-phase current component and the second orthogonal current component, to obtain a three-phase current negative sequence component, i.e. Figure 6 I2(t) in the third three-phase current signal.

[0117] Referring to Figure 7 In some embodiments, the target three-phase current signal is multiple, each target three-phase current signal corresponds to a sampling time point, and the target three-phase current signal of each sampling time point corresponds to a current transient high-frequency component and a three-phase current negative sequence component;

[0118] Step 104 can include, but is not limited to, steps 501-502:

[0119] Step 501, for each sampling time point in the same current sampling period, based on the three-phase current negative sequence component of the sampling time point and the current transient high-frequency components of each sampling time point before the sampling time point, a time domain convolution calculation is performed to obtain a convolution negative sequence component;

[0120] Step 502, based on the convolution negative sequence component of each sampling time point, a current negative sequence mutation variable is determined.

[0121] The embodiment has the advantages that, by performing a time domain convolution calculation for each sampling time point in the same current sampling period, based on the three-phase current negative sequence component of the sampling time point and the current transient high-frequency components of each sampling time point before the sampling time point, a convolution negative sequence component is obtained, which can capture the correlation between the negative sequence component and the high-frequency transient component in the time dimension, and amplify the saliency of the fault feature through convolution. Based on the convolution negative sequence component of each sampling time point, a current negative sequence mutation variable is determined, which can aggregate the convolution results at each sampling time point, comprehensively represent the dynamic change trend of the negative sequence component in the arc fault occurrence process, enhance the instantaneous change characteristics of the current during the arc fault, and thus improve the timeliness and sensitivity of the arc fault detection, and realize early warning of the arc fault.

[0122] In some embodiments, the current negative sequence mutation variable is defined as shown in the following formula:

[0123]

[0124] In the formula, i 2_hf(n) represents the current negative sequence abrupt variable; i hf (n-k) represents the current transient high-frequency component at sampling time point n-k; i2(k) represents the three-phase current negative sequence component at sampling time point k. N represents the number of sampling time points in the same current sampling period.

[0125] In step 501 of some embodiments, as in the above example, i hf (n-k)*i2(k) represents the convolution negative sequence component at sampling time point n.

[0126] In step 502 of some embodiments, the convolution negative sequence components at respective sampling time points can be summed to obtain the current negative sequence abrupt variable.

[0127] In some embodiments, the current sampling period can be a power frequency period. The length of the current sampling period can be used as the window length of the time-domain convolution. For example, the length of the power frequency period is 20 ms (milliseconds). Assuming that the sampling rate is 200 kHz, the sampling time points in one power frequency period are 4000, that is, N = 4000. In some embodiments, the sliding step length of the time-domain convolution is 5 ms (1000 sampling points).

[0128] It should be noted that the arc fault transient process usually lasts for tens of milliseconds, such as 10 ms, and therefore the current sampling period is set to the power frequency period of 20 ms, which can completely capture the transient abrupt process.

[0129] Referring to Figure 8 In some embodiments, the current sampling period is multiple; step 502 can include but is not limited to steps 601 to 602:

[0130] Step 601, determining the current abrupt length based on the time interval between adjacent sampling time points; wherein the current abrupt length is less than or equal to the time interval;

[0131] Step 602, for each current sampling period, based on the change value of the convolution negative sequence component in the current abrupt length in the same current sampling period and the current abrupt length, performing differential calculation to obtain the current negative sequence abrupt variable corresponding to each current sampling period.

[0132] The advantage of this embodiment is that by determining the current abrupt length based on the time interval between adjacent sampling time points, and then for each current sampling period, based on the change value of the convolution negative sequence component in the current abrupt length and the current abrupt length, performing differential calculation, the instantaneous change rate of the convolution negative sequence component can be extracted, the abrupt characteristics of the negative sequence component at the initial stage of the fault are amplified through differentiation, thereby improving the recognition sensitivity of the weak arc signal, and further improving the timeliness and sensitivity of the arc fault detection, and realizing the early warning of the arc fault.

[0133] In step 601 of some embodiments, the current mutation duration is less than or equal to a time interval between adjacent sampling time points. For example, assuming that the time interval between the sampling time points is 20 ms (milliseconds), the current mutation duration is less than or equal to 20 ms. In some embodiments, the current mutation duration can be 5 microseconds.

[0134] In step 602 of some embodiments, the current negative sequence mutation quantity is defined as shown in the following formula:

[0135]

[0136] In the formula, Δi2 represents the current negative sequence mutation quantity; di 2_hf represents the change value of the convolution negative sequence component; d t represents the current mutation duration.

[0137] Please refer to Figure 9 In some embodiments, step 105 can include, but is not limited to, steps 701 to 702:

[0138] Step 701, performing threshold comparison based on the current negative sequence mutation quantity of each current sampling period in the adjacent N current sampling periods and a preset current rise rate threshold; wherein N is a positive integer;

[0139] Step 702, if the current negative sequence mutation quantity of each current sampling period in the adjacent N current sampling periods is greater than the current rise rate threshold, determining that the target power system has an arc fault.

[0140] The advantage of this embodiment is that by continuously comparing the current negative sequence mutation quantity of each period in the adjacent N current sampling periods with the preset current rise rate threshold, the false appearance caused by transient interference (such as load fluctuation and electromagnetic noise) can be effectively reduced, and the reliability of the fault criterion is improved through multi-period consistency verification. Specifically, when the current negative sequence mutation quantity of N consecutive periods is greater than the threshold, it is determined that there is an arc fault, which can verify the continuous growth trend of the negative sequence component caused by the arc fault, avoid false judgment of the fault, and improve the stability and reliability of the arc fault detection.

[0141] In step 701 of some embodiments, the current rise rate threshold is a threshold for determining whether an arc fault occurs. For example, the current rise rate threshold can be 50 A / ms (amperes per millisecond). In some embodiments, N is 3. N can also be other positive integers, without being limited thereto.

[0142] In step 702 of some embodiments, assuming N is 3, and the current negative sequence mutation quantity of each current sampling period is greater than the current rise rate threshold in the consecutive 3 current sampling periods, it is determined that the target power system has an arc fault. In some embodiments, if it is determined that the target power system has an arc fault, an arc fault warning can be triggered, such as sending an alarm message to the maintenance personnel of the target power system.

[0143] In some embodiments, after step 701, the arc fault detection method further comprises:

[0144] If the current negative sequence mutation quantity of each current sampling period in the adjacent N current sampling periods is greater than the current rise rate threshold, the incremental calculation is performed on the current negative sequence mutation quantity of each adjacent two current sampling periods in the N current sampling periods, to obtain N-1 initial negative sequence mutation increments.

[0145] If the average value of the N-1 initial negative sequence mutation increments is greater than or equal to the preset current increment threshold, it is determined that the target power system has an arc fault.

[0146] The advantage of this embodiment is that, considering the high miss rate of single threshold comparison in a high noise scenario, after verifying that the current negative sequence mutation quantity in the consecutive N current sampling periods is greater than the current rise rate threshold, the incremental calculation is performed on the current negative sequence mutation quantity of each adjacent two current sampling periods for secondary verification, to further determine whether the change of the current conforms to the current rise trend of the arc, thereby improving the reliability of arc fault detection.

[0147] Please refer to Figure 10 In an application example, the three-phase current signals are synchronously sampled at a sampling frequency of 200 kHz, that is, the original three-phase current signals in the above. Then, the original three-phase current signals are low-pass filtered by a 5th order Butterworth filter to obtain the filtered signals, that is, the target three-phase current signals in the above. Based on the target three-phase current signals, the wavelet multi-resolution analysis is performed to obtain the transient high-frequency component, that is, the current transient high-frequency component in the above. At the same time, based on the target three-phase current signals, the negative sequence component fast calculation is performed to obtain the negative sequence component time domain signal, that is, the three-phase current negative sequence component in the above. Then, the time domain convolution is performed based on the transient high-frequency component and the negative sequence component time domain signal to obtain the enhanced negative sequence component, that is, the convolution negative sequence component in the above. Based on the enhanced negative sequence component, the enhanced negative sequence mutation quantity is calculated, that is, the current negative sequence mutation quantity in the above. If the enhanced negative sequence mutation quantity greater than the threshold is detected in the consecutive 3 power frequency periods, it is determined that an arc fault occurs.

[0148] Please refer to Figure 11 The embodiments of the present application also provide an arc fault detection device, which can implement the arc fault detection method described above, and the arc fault detection device comprises:

[0149] The current sampling unit 1101, the filtering unit 1102, the digital-to-analog conversion unit 1103 and the digital signal processing unit 1104 are sequentially electrically connected.

[0150] The current sampling unit 1101, the filtering unit 1102, the digital-to-analog conversion unit 1103 and the digital signal processing unit 1104 are sequentially electrically connected.

[0151] In some embodiments, the current sampling unit 1101 is an electronic element for collecting the current of the target power system. For example, the current sampling unit 1101 can include any one of the following electronic elements: an ammeter, a multimeter, a current sampling resistor, etc. The filtering unit 1102 is used to filter the interference signals in the current collected by the current sampling unit 1101. The digital-to-analog conversion unit 1103 is used to perform digital-to-analog conversion on the current signal.

[0152] In some embodiments, the digital-to-analog conversion unit 1103 can be an ADS8688 chip with 24-bit resolution. The digital-to-analog conversion unit 1103 can also include other types of electronic elements, without being limited thereto.

[0153] In some embodiments, the digital signal processing unit 1104 can include a DSP (Digital Signal Processing) chip. For example, the DSP chip can be a TMS320F28335 chip supporting floating-point operations.

[0154] The specific implementation of the arc fault detection device is basically the same as the specific embodiments of the arc fault detection method described above, and will not be repeated here.

[0155] The embodiments of the present application also provide an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor implements the arc fault detection method described above when executing the computer program. The electronic device can include any intelligent terminal such as a tablet computer or a vehicle-mounted computer.

[0156] Please refer to Figure 12 , Figure 12 The hardware structure of the electronic device of another embodiment is illustrated, which includes:

[0157] The processor 1201 can be implemented in a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, etc., and is used to execute related programs to implement the technical solutions provided by the embodiments of the present application.

[0158] The memory 1202 can be implemented in the form of a Read-Only Memory (ROM), a static storage device, a dynamic storage device, or a Random Access Memory (RAM), etc. The memory 1202 can store an operating system and other application programs. When the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the related program codes are stored in the memory 1202 and are called and executed by the processor 1201 to implement the arc fault detection method of the embodiments of the present application;

[0159] The input / output interface 1203 is configured to realize information input and output.

[0160] The communication interface 1204 is configured to realize the communication interaction between the device and other devices. The communication can be realized by a wired manner (for example, a USB, a network cable, etc.) or a wireless manner (for example, a mobile network, WIFI, Bluetooth, etc.).

[0161] The bus 1205 is configured to transmit information between various components (for example, the processor 1201, the memory 1202, the input / output interface 1203, and the communication interface 1204) of the device.

[0162] The processor 1201, the memory 1202, the input / output interface 1203, and the communication interface 1204 are connected to each other through the bus 1205 to realize the communication connection between the device.

[0163] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the arc fault detection method described above.

[0164] The memory is a non-transitory computer readable storage medium, which can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory can include a high-speed random access memory and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0165] It should be noted that the non-company software tools or components appearing in the embodiments of the present application are only examples for introduction and do not represent actual use.

[0166] The embodiments described in the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0167] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than those shown in the figures, or combine certain steps, or different steps.

[0168] The device embodiments described above are merely illustrative, and the units described as separate components can or can not be physically separated, that is, can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0169] Those skilled in the art can understand that all or some of the steps in the above disclosed method, the function modules / units in the system and the device can be implemented as software, firmware, hardware and their appropriate combinations.

[0170] The terms "first", "second", "third", "fourth" and the like (if any) in the specification of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0171] It should be understood that, in the application, "at least one" refers to one or more, and "multiple" refers to two or more. "And / or" is used to describe the association relationship of the associated objects, which means that there can be three relationships, for example, "A and / or B" can represent three cases of only A, only B and A and B existing at the same time, wherein A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after it. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can represent a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b and c can be single or multiple.

[0172] In several embodiments provided in the application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the above units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between devices or units, which can be electrical, mechanical or other forms.

[0173] The units described above as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on multiple network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0174] In addition, the functional units in each embodiment of the application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0175] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0176] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, and are not limited to the scope of the embodiments of the present application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. An arc fault detection method characterized by, The method comprises: current sampling of a target power system to obtain target three-phase current signals; wavelet signal analysis based on the target three-phase current signals to obtain current transient high-frequency components; negative sequence component calculation based on the target three-phase current signals to obtain three-phase current negative sequence components; component fusion based on the three-phase current negative sequence components and the current transient high-frequency components to generate current negative sequence sudden variables; threshold comparison based on the current negative sequence sudden variables to detect faults of the target power system.

2. The method of claim 1, wherein, The target three-phase current signals are multiple, each of the target three-phase current signals corresponds to a sampling time point, and the target three-phase current signal of each sampling time point corresponds to a current transient high-frequency component and a three-phase current negative sequence component. The component fusion based on the three-phase current negative sequence components and the current transient high-frequency components to generate current negative sequence sudden variables comprises: For each sampling time point in the same current sampling period, time domain convolution calculation is performed based on the three-phase current negative sequence component of the sampling time point and the current transient high-frequency components of each sampling time point before the sampling time point to obtain convolution negative sequence components; The current negative sequence sudden variables are determined based on the convolution negative sequence components of each sampling time point.

3. The method of claim 2, wherein, The current sampling period is multiple; The determination of the current negative sequence sudden variables based on the convolution negative sequence components of each sampling time point comprises: The current sudden change duration is determined based on the time interval between adjacent sampling time points; wherein the current sudden change duration is less than or equal to the time interval; For each current sampling period, differential calculation is performed based on the change value of the convolution negative sequence components within the current sudden change duration in the same current sampling period and the current sudden change duration to obtain the current negative sequence sudden variable corresponding to each current sampling period.

4. The method of claim 3, wherein, The threshold comparison based on the current negative sequence sudden variables to detect faults of the target power system comprises: Threshold comparison is performed based on the current negative sequence sudden variables of each current sampling period in adjacent N current sampling periods and a preset current rise rate threshold; wherein N is a positive integer; If the current negative sequence sudden variables of each current sampling period in adjacent N current sampling periods are all greater than the current rise rate threshold, it is judged that the target power system has an arc fault.

5. The method according to any one of claims 1 to 4, characterized in that, The wavelet signal analysis based on the target three-phase current signals to obtain current transient high-frequency components comprises: Multi-layer wavelet decomposition of the target three-phase current signals is performed through a Mallat decomposition algorithm to obtain multiple current high-frequency detail coefficients; Wavelet reconstruction of the multiple current high-frequency detail coefficients is performed through a Mallat reconstruction algorithm to obtain the current transient high-frequency components.

6. The method according to any one of claims 1 to 4, characterized in that, The negative sequence component calculation based on the target three-phase current signals to obtain three-phase current negative sequence components comprises: The target three-phase current signal is subjected to coordinate system transformation to obtain a two-phase current signal; wherein the two-phase current signal comprises a first two-phase current component and a second two-phase current component; The first two-phase current component is subjected to orthogonal phase shift to obtain a first orthogonal current component, and the second two-phase current component is subjected to orthogonal phase shift to obtain a second orthogonal current component; A first initial negative sequence component is determined based on the first two-phase current component and the first orthogonal current component, and a second initial negative sequence component is determined based on the second two-phase current component and the second orthogonal current component; A combination of the first initial negative sequence component and the second initial negative sequence component is determined as a two-phase negative sequence component, and the two-phase negative sequence component is subjected to inverse coordinate system transformation to obtain the three-phase current negative sequence component.

7. The method according to any one of claims 1 to 4, characterized in that, The target power system is subjected to current sampling to obtain a target three-phase current signal, comprising: Based on a preset arc current frequency threshold, a preset multiple of the arc current frequency threshold is selected from a plurality of preset candidate sampling frequencies to obtain a target sampling frequency; The target power system is subjected to current sampling according to the target sampling frequency to obtain an original three-phase current signal; The arc current frequency threshold is determined as a cutoff frequency, and the original three-phase current signal is subjected to low-pass filtering based on the cutoff frequency to obtain the target three-phase current signal.

8. An arc fault detection apparatus characterized by comprising: The device is used to execute the method of any one of claims 1 to 7, and the device comprises: a current sampling unit, a filtering unit, a digital-to-analog conversion unit and a digital signal processing unit; The current sampling unit, the filtering unit, the digital-to-analog conversion unit and the digital signal processing unit are electrically connected in sequence.

9. An electronic device, comprising: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the method of any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. The computer program is executed by the processor to realize the method of any one of claims 1 to 7.

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