Fault arc detection and positioning method, device and computer readable storage medium

Abstract

This invention discloses a method, apparatus, and storage medium for detecting and locating fault arcs. The method includes acquiring low-frequency current signals and high-frequency differential-mode noise signals collected from a mains power monitoring point. A high-frequency notch filter circuit is installed on the mains power inlet line before the monitoring point. The method determines whether a fault arc exists within the monitoring range corresponding to the monitoring point. When a fault arc exists within the monitoring range, it determines whether the arc fault is a fault in a neighboring branch based on a first characteristic value obtained from sampling the low-frequency current signal to identify the degree of low-frequency current abrupt change. If the arc fault is not a fault in a neighboring branch, it determines whether the faulty line location is in the upstream or downstream line based on whether the second and third characteristic values ​​obtained from sampling the high-frequency differential-mode noise signal are disturbed by the high-frequency notch filter. This invention solves the technical problem that the reliability of fault arc detection products is affected by disturbances from neighboring branch arcs and upstream arcs in existing technologies.

Description

Technical Field

[0001] The present invention relates to the field of circuit electronics, and in particular to a method and device for detecting and locating a fault arc, and a computer-readable storage medium. Background Art

[0002] Arc faults are a very important cause of electrical fires. Currently, arc fault detection is mainly carried out through current detection. However, when an arc fault is actually detected, its occurrence location may not be on the line where the arc fault monitoring point is located. For example, the arc fault location may be in an adjacent branch or upstream line of the monitoring point. That is, the current arc fault monitoring method has arc disturbances in adjacent branches and upstream arc disturbances, which affects the reliability of arc fault detection products. Summary of the invention

[0003] The main purpose of the present invention is to provide a method, device and computer-readable storage medium for detecting and locating arc faults, aiming to solve the technical problem in the prior art that the reliability of arc fault detection products is affected by the presence of arc disturbances in adjacent branches and upstream arc disturbances.

[0004] To achieve the above object, the present invention provides a method for detecting and locating an arc fault, the method comprising:

[0005] Obtaining a low-frequency current signal and a high-frequency differential-mode noise signal collected by a mains power monitoring point, wherein a high-frequency trap circuit is provided on the mains power incoming line before the monitoring point;

[0006] Determine whether there is a fault arc within the monitoring range corresponding to the monitoring point;

[0007] When there is a fault arc within the monitoring range, determining whether the arc fault is an adjacent branch arc fault according to a first characteristic value obtained by sampling the low-frequency current signal and used to identify the degree of low-frequency current mutation;

[0008] When the arc fault is not the adjacent branch arc fault, the fault line is located in the upstream line or the subordinate line according to whether the second characteristic value and the third characteristic value obtained by sampling the high-frequency differential mode noise signal are disturbed by the high-frequency notch.

[0009] Optionally, the step of determining whether there is a fault arc within a monitoring range corresponding to the monitoring point includes:

[0010] Determine in sequence whether the second eigenvalue and the third eigenvalue in each unit time in the signal sampling time window are both greater than the corresponding characteristic threshold;

[0011] Wherein, each time it is judged that the second characteristic value and the third characteristic value in the same unit time are both greater than the corresponding characteristic threshold, the counter is incremented by 1; each time it is judged that the second characteristic value or the third characteristic value is not greater than the corresponding characteristic threshold, the counter is decremented by 1;

[0012] During the judgment process, when the value of the counter is greater than a preset value, it is determined that there is a fault arc within the monitoring range.

[0013] Optionally, the step of determining whether the arc fault is an adjacent branch arc fault according to a first characteristic value for identifying a degree of low-frequency current mutation obtained by sampling the low-frequency current signal comprises:

[0014] According to the first characteristic value, it is determined whether the high-frequency mutation and the low-frequency mutation are synchronous; wherein, when the high-frequency mutation and the low-frequency mutation are not synchronous, it is determined that the arc fault is an adjacent branch arc fault.

[0015] Optionally, the step of determining whether the high-frequency mutation and the low-frequency mutation are synchronized according to the first characteristic value includes:

[0016] After all the second characteristic values ​​and the third characteristic values ​​within the signal sampling time window are determined, the time points corresponding to all the positive zero-crossing points of the counter are obtained;

[0017] Obtain a first mean value of all first eigenvalues ​​corresponding to before the moment and a second mean value of all first eigenvalues ​​corresponding to after the moment;

[0018] When the difference between the first mean and the second mean is greater than a preset mutation threshold, determining that the high-frequency mutation and the low-frequency mutation are synchronized;

[0019] When the difference between the first mean and the second mean is smaller than a preset mutation threshold, it is determined that the high-frequency mutation and the low-frequency mutation are not synchronized.

[0020] Optionally, the step of sampling the high-frequency differential mode noise signal to obtain a second eigenvalue and a third eigenvalue includes:

[0021] Mixing the high-frequency differential mode noise signal with a local oscillator frequency signal whose frequency changes periodically per unit time, and filtering the mixed signal; wherein the local oscillator frequencies that change periodically are the first local oscillator frequency, the second local oscillator frequency and the third local oscillator frequency in sequence;

[0022] The high-frequency differential mode noise signal after mixing and filtering is sampled to obtain sampling data corresponding to multiple unit times in the signal sampling time window, and the sampling data corresponding to each unit time is calculated to obtain the second eigenvalue and the third eigenvalue.

[0023] Optionally, the step of determining whether the fault line is located in an upstream line or a subordinate line according to whether the second characteristic value and the third characteristic value obtained by sampling the high-frequency differential mode noise signal are disturbed by the high-frequency notch wave comprises:

[0024] Matching the second eigenvalue and the third eigenvalue with the center frequency corresponding to each of the local oscillator frequencies in sequence, so as to group all the first eigenvalues ​​and the second eigenvalues ​​respectively according to the matched center frequencies;

[0025] calculating a third mean for each group when each center frequency matches the second eigenvalue and a fourth mean for each group when each center frequency matches the second eigenvalue;

[0026] The location of the fault arc is determined to be in the upstream line or the subordinate line according to a preset algorithm, the third mean value and the fourth mean value; the preset algorithm is:

[0027] γ=|AVG(ε n ∈f s1 )-AVG(ε n ∈f sc )|+|AVG(ε n ∈f s2 )-AVG(ε n ∈f sc )|-|AVG(ε n ∈f s2 )-AVG(ε n ∈f s1 )|

[0028] η=|AVG(β n ∈f s1 )-AVG(β n ∈f sc )|+|AVG(β n ∈f s2 )-AVG(β n ∈f sc )|-|AVG(β n ∈f s2 )-AVG(β n ∈f s1 )|

[0029] Among them, β is the second eigenvalue, ε is the third eigenvalue, and f s1 is the center frequency corresponding to the first local oscillator frequency, f sc is the center frequency corresponding to the second local oscillator frequency, f s2 is the center frequency corresponding to the third local oscillator frequency, AVG(β∈f) is the third mean, and AVG(ε∈f) is the fourth mean; when η>η 0 Or γ>γ0 , determine that the arc fault location is in the upstream line.

[0030] Optionally, after all steps, the method further comprises:

[0031] When the arc fault is located in a subordinate line, an alarm action is performed, and the alarm action includes at least one of sending an audible and visual alarm signal, disconnecting the subordinate line, and reporting arc fault information.

[0032] To achieve the above-mentioned purpose, the present invention also provides a fault arc detection and positioning device, which includes: a high-frequency trap circuit, a sampling circuit and a controller. The controller includes a memory, a processor and a fault arc detection and positioning program stored in the memory and executed on the processor. When the fault arc detection and positioning program is executed, the fault arc detection and positioning method as described above is implemented.

[0033] Optionally, the sampling circuit includes a high-frequency sensor for collecting the high-frequency differential mode noise signal, and a sampling end of the high-frequency sensor is connected to a first mains power line and a second mains power line which are opposite to each other and cross each other.

[0034] To achieve the above object, the present invention further provides a computer-readable storage medium, which is stored in a memory and implements the above-mentioned method for detecting and locating an arc fault when executed on a processor.

[0035] The present invention provides a method, device and computer-readable storage medium for detecting and locating a fault arc. The method obtains a low-frequency current signal and a high-frequency differential mode noise signal collected by a mains power monitoring point, and a high-frequency trap circuit is set on the mains power incoming line before the monitoring point; it is determined whether there is a fault arc in the monitoring range corresponding to the monitoring point; when there is a fault arc in the monitoring range, it is determined whether the arc fault is an adjacent branch arc fault according to the first characteristic value obtained by sampling the low-frequency current signal to identify the degree of low-frequency current mutation; when the arc fault is not an adjacent branch arc fault, it is determined whether the fault line is located in the upstream line or the subordinate line according to whether the second characteristic value and the third characteristic value obtained by sampling the high-frequency differential mode noise signal are disturbed by the high-frequency trap. Among them, the location of the fault arc is distinguished by the first characteristic value, the second characteristic value and the third characteristic value, thereby solving the technical problem that the reliability of the fault arc detection product is affected by the presence of the adjacent branch arc disturbance and the upstream arc disturbance in the prior art, and the accurate location of the arc fault can be found in time, thereby improving the reliability of the arc detection product. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only one embodiment of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structure shown in this drawing without paying creative work.

[0037] Figure 1 A schematic diagram of a flow chart of an embodiment of a method for detecting and locating an arc fault according to the present invention;

[0038] Figure 2 for Figure 1 A schematic diagram of a module structure of an arc fault detection and positioning method applied to an arc fault detection and positioning device / circuit;

[0039] Figure 3 for Figure 2 Schematic diagram of optional circuit structure of sampling circuit, controller and alarm unit;

[0040] Figure 4 for Figure 2 Amplitude-frequency response characteristic curve of high-frequency trap circuit in fault arc detection and location device / circuit;

[0041] Figure 5 for Figure 3 Schematic diagram of signal coupling circuit of high frequency sensor, low frequency sensor and high frequency trap circuit in medium fault arc detection and location device / circuit;

[0042] Figure 6 for Figure 2 Schematic diagram of optional circuit structure of high frequency trap circuit in fault arc detection and location device / circuit;

[0043] Figure 7 for Figure 2 A schematic diagram of another optional circuit structure of a sampling circuit, a controller and an alarm unit in a fault arc detection and positioning device / circuit.

[0044] Figure 8 A schematic diagram of a flow chart of another embodiment of a method for detecting and locating an arc fault;

[0045] Fig. 9 When the local oscillator frequency output terminal periodically changes and outputs the local oscillator frequency, the data sampled by the high-frequency sampling terminal of the controller and the timing diagram of the controller extracting the second eigenvalue and the third eigenvalue.

[0046] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings.

[0047] Description of Figure Numbers:

[0048] Label name Label name 10 Sampling circuit 20 Controller 11 Low frequency current sampling circuit 16 Bandpass filter 12 High frequency noise sampling circuit 17 Detector LF Low frequency sensor R resistance 13 Low pass filter C capacitance HF High frequency sensor L inductance 14 High frequency noise signal extraction circuit 30 High frequency trap circuit 15 Mixer 40 Alarm unit DETAILED DESCRIPTION

[0049] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0052] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0053] The present invention provides a method for detecting and locating a fault arc. In one embodiment, referring to Figure 1 , the method comprises the steps of:

[0054] Step S10, obtaining a low-frequency current signal and a high-frequency differential-mode noise signal collected by a mains power monitoring point, wherein a high-frequency trap circuit is provided on the mains power incoming line before the monitoring point;

[0055] Step S20, determining whether there is a fault arc within the monitoring range corresponding to the monitoring point;

[0056] Step S30, when there is a fault arc within the monitoring range, determining whether the arc fault is an adjacent branch arc fault according to a first characteristic value obtained by sampling the low-frequency current signal and used to identify the degree of low-frequency current mutation;

[0057] Step S40, when the arc fault is not the adjacent branch arc fault, determine whether the fault line is located in the upstream line or the subordinate line according to whether the second characteristic value and the third characteristic value obtained by sampling the high-frequency differential mode noise signal are disturbed by the high-frequency notch.

[0058] It should be noted that in the fault arc detection sub-field in the field of electrical safety detection, current sensors are usually set on the neutral line or live line of the power line, and cooperate with the signal conditioning circuit to extract the high-frequency noise signal in the current, and use the characteristic value in the high-frequency noise signal as the characteristic parameter; when the above characteristic parameter exceeds the set threshold, it is determined that an arc fault has occurred in the line. However, in actual applications, we are concerned about whether an arc fault has occurred in the subordinate lines, and the radiation detection range of the mains monitoring point for the existence of arcs includes the subordinate lines, upstream lines and adjacent branches. Therefore, for the above scheme, the arc fault occurring upstream of the monitoring point will also be identified, or when the high-frequency noise signal of the arc in the adjacent branch is coupled to the current branch, it will also cause the monitoring point to identify the arc fault, that is, the existing arc fault detection scheme has upstream arc disturbance and adjacent branch disturbance.

[0059] Traditionally, high-frequency noise signals are collected by high-frequency sensors in a single-line coupling manner. The main component of the sampled high-frequency noise signal is the common-mode signal. Figure 2 In this solution, a sampling circuit 10 capable of collecting low-frequency current signals and high-frequency differential mode noise signals is set at the mains monitoring point, wherein the high-frequency differential mode noise signal is a differential mode current signal, which is coupled with a high-frequency noise signal of more than 100kHz or even more than 1MHz in the line, and can reduce the interference degree of electromagnetic coupling in space after the arc fault of the adjacent branch to a certain extent. The low-frequency current signal can be specifically extracted by low-pass sampling and filtering through the sampling circuit, and the current waveform signal is within 10kHz after sampling and filtering.

[0060] The controller 20 receives the low-frequency current signal and the high-frequency differential mode noise signal, that is, obtains these two signals, which can confirm whether there is a fault arc. This solution can be implemented using existing technology, or the high-frequency differential mode noise signal in this solution can be used for judgment. In the case of a fault arc, the controller 20 extracts the first characteristic value from the low-frequency current signal. The first characteristic value can be any parameter that can describe the degree of mutation of the low-frequency current waveform, such as the cumulative sum of the current values ​​in the calculation window, the maximum value of the current change rate in the window, and the variance of the effective current value, etc. It should also be noted that the calculation window can be set according to actual needs, for example, it can be the power frequency current cycle (50Hz is 20ms). The first characteristic value can be used to determine whether the low-frequency mutation and the high-frequency mutation are synchronized. When they are synchronized, it is determined that it is not an arc fault in the adjacent branch. When the low-frequency mutation is not synchronized with the high-frequency mutation, it is an arc fault in the adjacent branch. It is worth noting that this solution is not about selecting which feature to describe the low-frequency mutation, but about finding the time when the low-frequency mutation occurs, comparing the time when the low-frequency mutation occurs with the time when the high-frequency mutation occurs, and obtaining its synchronization through the controller. In this solution, the mean values ​​of all the first characteristic values ​​before and after the mutation are detected can be compared to determine whether the difference between the two is within a preset range, so as to determine whether the low-frequency mutation and the high-frequency mutation are synchronized. Further, on this basis, a high-frequency trap circuit 30 is also provided, which is provided before the monitoring point where the sampling circuit 10 is located, that is, between the sampling circuit 10 and the mains power supply line. Through the set trap network, the specific noise signal of the specific bandwidth of the upstream line can be blocked from flowing in. Then, when the controller 20 determines that it is not an arc fault in the adjacent branch, it can determine whether the fault location is in the upstream line or the subordinate line according to whether the second characteristic value and the third characteristic value in the high-frequency noise signal are disturbed by the high-frequency trap. In this embodiment, the second characteristic value and the third characteristic value can correspond to the mean and peak-to-peak value of all sampling points in the calculation window.

[0061] This embodiment sets a high-frequency trap circuit 30 in the fault arc detection and positioning circuit, and sets a sampling circuit 10 to collect high-frequency differential mode noise signals and low-frequency current signals, and then uses the first characteristic value, the second characteristic value and the third characteristic value in combination with the controller 20. It can distinguish whether the fault arc occurs in an adjacent branch, a subordinate line or an upstream branch, and distinguish the location of the fault arc, thereby solving the technical problem of the prior art that the reliability of the fault arc detection product is affected by the existence of arc disturbances in adjacent branches and upstream arc disturbances, and can timely discover the accurate location of the arc fault, thereby improving the operating reliability of the fault arc detection product.

[0062] Further, the controller performs an alarm action when determining that the arc fault is located in the subordinate line, and the alarm action includes at least one of sending an audible and visual alarm signal, disconnecting the subordinate line, and reporting arc fault information, and the arc fault information may be reported through a communication port. Figure 2 , an alarm unit 40 can be connected to the output end of the controller 20, so that when the controller 20 confirms that the fault line is located in the subordinate line, the alarm unit 40 is triggered to perform an alarm action, so that the fault arc phenomenon of the subordinate line can be handled immediately. It should be noted that when the fault occurs in the adjacent branch and the upstream line, no action will be taken at this time. This reduces the probability of accidental disconnection of the power branch where a normal fault-free arc occurs, and improves the reliability of the use of the fault arc detection product.

[0063] It should also be noted that the sampling circuit for collecting high-frequency differential mode noise signals and low-frequency current signals and the high-frequency trap circuit for distinguishing upstream lines and downstream branches can be configured according to actual needs. Figures 2 to 5 . The sampling circuit 10 may include a low-frequency current sampling circuit 11 and a high-frequency noise sampling circuit 12; the low-frequency current sampling circuit 11 samples the first mains power, and the low-frequency current sampling circuit 11 is connected to the low-frequency sampling end of the controller 20; the first mains power is also opposite to the second mains power, and crosses through the sampling end of the high-frequency noise sampling circuit 12, and the high-frequency noise sampling circuit 12 is connected to the high-frequency sampling end of the controller 20; the first end of the high-frequency trap circuit 30 is connected to the first mains power incoming line relative to the low-frequency current sampling circuit 11 and the high-frequency noise sampling circuit 12, and the second end of the high-frequency trap circuit 30 is connected to the second mains power incoming line relative to the high-frequency noise sampling circuit 12. The first mains power can be a neutral line or a live line, and the corresponding second mains power is a live line or a neutral line. By separately setting the high-frequency noise sampling circuit 12 and the low-frequency current sampling circuit 11, the corresponding extraction of the current signal is facilitated and the occurrence of interference is reduced.

[0064] The structure of the high-frequency trap circuit 30 can be, for example, a series LRC network, and of course, circuit structures with other equivalent characteristics are also acceptable. The series LRC network can include a resistor R, an inductor L, and a capacitor C; the capacitor C is connected to the first mains power incoming line, the capacitor C is also connected to the first end of the inductor L, the second end of the inductor L is connected to the first end of the resistor R, and the second end of the resistor R is connected to the second mains power incoming line. When used in an AC 110V or AC 220V line, the capacitor C should preferably be a low ESR capacitor with a withstand voltage of more than 1kV.

[0065] The above-mentioned low-frequency current sampling circuit 11 includes a low-frequency sensor LF and a low-pass filter 13; the low-frequency sensor LF is arranged in the first mains power, and the low-frequency sensor LF is also connected to the input end of the low-pass filter 13. The output end of the low-pass filter 13 is connected to the low-frequency sampling end of the controller 20. The magnetic core of the low-frequency sensor LF can be a low-permeability magnetic core, such as iron-silicon-aluminum. Through the settings of the low-frequency sensor LF and the low-pass filter 13, a current signal within 10 kHz can be extracted and sent to the low-frequency sampling end of the controller 20, providing the possibility for the acquisition of low-frequency current signals.

[0066] The above-mentioned high-frequency noise sampling circuit 12 may include a high-frequency sensor HF and a high-frequency noise signal extraction circuit 14; the sampling end of the high-frequency sensor HF is the sampling end of the high-frequency noise sampling circuit 12, the output end of the high-frequency sensor HF is connected to the input end of the high-frequency noise signal extraction circuit 14, and the output end of the high-frequency noise signal extraction circuit 14 is connected to the high-frequency sampling end of the controller 20. The high-frequency sensor HF is changed from the original single-wire coupling to a two-wire coupling method, and the first mains power and the second mains power are opposite to each other and cross through the high-frequency sensor HF to extract differential-mode current signals. The high-frequency sensor HF is preferably a Rogowski coil with a low-permeability magnetic core or a hollow skeleton, which can couple high-frequency noise signals above 100 kHz or even above 1 MHz in the line.

[0067] The structure of the above-mentioned high-frequency noise signal extraction circuit 14 can be set according to actual needs. Refer to Figure 3 , in an embodiment, it may include a mixer 15, a band-pass filter 16, and a detector 17; the first input end of the mixer 15 is connected to the output end of the high-frequency sensor HF, the second input end of the mixer 15 is connected to the local oscillator frequency output end of the controller 20, the output end of the mixer 15 is connected to the input end of the band-pass filter 16, and the output end of the band-pass filter 16 is connected to the input end of the detector 17; the output end of the detector 17 is connected to the high-frequency sampling end of the controller 20.

[0068] It should be noted that the local oscillator frequency output end outputs a local oscillator frequency with a periodically changing frequency, which corresponds to the center frequency of the amplitude-frequency response curve of the high-frequency notch network. Please refer to Figures 2 to 6 , especially Figure 4 , where fc is the center frequency point of the notch network, and the maximum attenuation can be obtained (the gain is -dc); the frequency point f1 is less than the fc frequency, and the gain is -d1; the frequency point f2 is greater than the fc frequency, and the gain is -d2; where, f1 < fc < f2; d1 ≈ d2 < dc. The local oscillator frequency output end of the controller 20 is the MCO port of the controller 20, and the frequency of the output signal can be adjusted, that is, the output local oscillator frequency LO includes (LO = LO 1 , LO c , LO2 ; and LO 1 <LO c <LO 2 ), the signal sampled by the high frequency sensor HF is mixed with different local oscillator frequencies in the mixer 15, so that different components in the output signal of the high frequency sensor HF can be analyzed.

[0069] The above scheme can also use a mixer chip to replace the mixer-bandpass filter-detector to obtain different frequency components. For example, the model of the mixer chip can be SA602A. Or please refer to Figure 7 In another embodiment, the high-frequency noise signal extraction circuit 14 may include three bandpass filters 16 and three detectors 17; the input ends of the three bandpass filters 16 are connected to the output end of the high-frequency sensor HF, the output ends of the three bandpass filters 16 are correspondingly connected to the input ends of the three detectors 17, and the output ends of the three detectors 17 are connected to the high-frequency sampling end of the controller 20; the center frequencies of the three bandpass filters 16 are different. That is, the output of the high-frequency sensor HF passes through three bandpass filters 16 and is correspondingly connected to three detectors 17, so that the characteristic values ​​of three frequency components can be obtained simultaneously in each cycle, and the structure is simple.

[0070] Please continue to combine Figures 2 to 6 , taking the scheme of using detector and mixer as an example. It can be understood that the high frequency sensor HF outputs a broadband noise signal, which is mixed with the local oscillator frequency LO in the mixer 15 and then output through the bandpass filter 16 to obtain a narrowband signal, the center frequency of which is f zd , preferably, the filtering link in which the filter participates should try to control the bandwidth of the narrowband signal within 50kHz; finally, the envelope of the narrowband signal can be obtained through the detector 17 and sent to the high-frequency sampling end for sampling. It is worth noting that: according to the principle of mixing, that is, mixing is the process of converting the signal frequency from one value to another, the new signal obtained is equivalent to the sum and difference frequency of the source signal and the local oscillator LO signal, and the envelope actually describes the broadband noise signal output by the high-frequency sensor HF with a frequency of f S The ingredients of S =LO ± f zd Correspondingly, in this embodiment, we focus on monitoring the three frequency components output by the high-frequency sensor, the three frequency components output by the high-frequency sensor HF:

[0071] Center frequency f Sc The components: f1<(f Sc =LO c ±f zd ≈fc) <f2

[0072] Center frequency fS1 The composition of: f1≈(f S1 =LO 1 ±f zd ) <fc

[0073] Center frequency f S2 The composition of: fc<(f S2 =LO 2 ±f zd )≈f2

[0074] That is, the sampling circuit and the controller, for example, the controller can control itself and / or the sampling circuit, and the process of obtaining the second eigenvalue and the third eigenvalue based on the above structure includes: mixing the high-frequency differential mode noise signal with the local oscillator frequency signal whose frequency changes periodically according to the unit time, and filtering the mixed signal; wherein the periodically changed local oscillator frequencies are the first local oscillator frequency LO1, the second local oscillator frequency LOc and the third local oscillator frequency LO2 in sequence; sampling the high-frequency differential mode noise signal after mixing and filtering to obtain sampling data corresponding to multiple unit times in the signal sampling time window, and calculating the sampling data corresponding to each unit time to obtain the second eigenvalue and the third eigenvalue.

[0075] Through the internal structure design of the high-frequency trap circuit 30, the high-frequency noise sampling circuit 12 and the low-frequency current sampling circuit 11, a detailed structural implementation scheme for fault arc detection is given, wherein the high-frequency noise sampling circuit 12 can periodically extract the second eigenvalue and the third eigenvalue of different frequency components through the mixer-filter-detection structural design, providing a technical basis for fault arc position diagnosis.

[0076] Further, see Figure 8 In another embodiment of the arc fault detection and location method, the method comprises:

[0077] Step S10, obtaining a low-frequency current signal and a high-frequency differential mode noise signal collected by a mains power monitoring point;

[0078] Step S21, sequentially judging whether the second characteristic value and the third characteristic value in each unit time in the signal sampling time window are both greater than the corresponding characteristic threshold value; wherein, each time it is judged that the second characteristic value and the third characteristic value in the same unit time are both greater than the corresponding characteristic threshold value, the counter is incremented by 1; each time it is judged that the second characteristic value or the third characteristic value is not greater than the corresponding characteristic threshold value, the counter is decremented by 1;

[0079] Step S22, during the judgment process, when the value of the counter is greater than a preset value, it is determined that there is a fault arc within the monitoring range;

[0080] Step S31, determining whether the high-frequency mutation and the low-frequency mutation are synchronized according to the first characteristic value;

[0081] Step S32, when the high-frequency mutation and the low-frequency mutation are not synchronized, determining that the arc fault is an adjacent branch arc fault;

[0082] Step S41, when the high-frequency mutation and the low-frequency mutation are synchronized, the second eigenvalue and the third eigenvalue are matched with the center frequency corresponding to each of the local oscillator frequencies in sequence, so as to group all the first eigenvalues ​​and the second eigenvalues ​​respectively according to the matched center frequencies;

[0083] Step S42, calculating a third mean value of each group when each center frequency matches the second eigenvalue and a fourth mean value of each group when each center frequency matches the second eigenvalue;

[0084] Step S43, determining whether the position of the fault arc is in an upstream line or a subordinate line according to a preset algorithm, the third mean value and the fourth mean value; the preset algorithm is:

[0085] γ=|AVG(ε n ∈f s1 )-AVG(ε n ∈f sc )|+|AVG(ε n ∈f s2 )-AVG(ε n ∈f sc )|-|AVG(ε n ∈f s2 )-AVG(ε n ∈f s1 )|

[0086] η=|AVG(β n ∈f s1 )-AVG(β n ∈f sc )|+|AVG(β n ∈f s2 )-AVG(β n ∈f sc )|-|AVG(β n ∈f s2 )-AVG(β n ∈f s1 )|

[0087] Among them, β is the second eigenvalue, ε is the third eigenvalue, and f s1 is the center frequency corresponding to the first local oscillator frequency, f sc is the center frequency corresponding to the second local oscillator frequency, f s2is the center frequency corresponding to the third local oscillator frequency, AVG(β∈f) is the third mean, and AVG(ε∈f) is the fourth mean; when η>η 0 Or γ>γ 0 , determine that the arc fault location is in the upstream line.

[0088] In this embodiment, the low-frequency sampling end of the controller in the mains monitoring point can continuously perform sampling at the sampling frequency Fs. Taking the above-mentioned industrial frequency current cycle as the calculation window as an example, a low-frequency current signal with a unit data length of N can be collected and the first eigenvalue can be extracted. The controller can continuously cache data within 1 second, where 1 second is the signal sampling time window. Of course, it can also be other time lengths. When caching data within 1 second, 50 first eigenvalues ​​can be extracted and stored. The high-frequency sampling end of the controller also continuously samples at the sampling frequency Fs, and the calculation window, unit data length and signal sampling time window are consistent with the above. The corresponding controller can also store 50 consecutive second eigenvalues ​​and third eigenvalues. It should be noted that please refer to Fig. 9 , we take the power frequency current cycle as the basic unit to update the local oscillator frequency in sequence...→LO 1 →LO c →LO 2 →…, repeating the cycle, the high-frequency differential mode noise signal actually extracted also has different frequency components…→f s1 →f sc →f s2 →…, the corresponding calculations are also based on LO 1 ,LO c ,LO 2 The second and third eigenvalues ​​of are respectively denoted as (characteristic 2, β) and (characteristic 3, ε).

[0089] When performing arc fault diagnosis, if the second eigenvalue is greater than the corresponding threshold β within a calculation window, 0 And the third eigenvalue is greater than the corresponding value ε 0 , the count value MU is incremented by 1, otherwise, it is decremented by 1; the calculation window slides over time, and when the value of the counter MU changes from 0 to 1, that is, it crosses zero positively, the moment TS can be recorded. In the judgment process, once the value of the counter MU is greater than the threshold MU0 When an arc fault occurs, it is determined that there is an arc current signal in the line, but the location of the arc fault cannot be determined, that is, it cannot be determined that the arc fault must have occurred in the subordinate line. Further, if an arc fault is considered to have occurred, the arc fault flag can be set to 1, that is, ArcFaultSomeWhere=1.

[0090] When it is determined that there is an arc fault, the controller can obtain the time TS corresponding to all the positive zero-crossing points of the counter; obtain the first mean of all the first eigenvalues ​​corresponding to the time before the time TS and the second mean of all the first eigenvalues ​​corresponding to the time after the time TS, that is, calculate the mean of the first eigenvalues ​​before the time TS and the mean of the first eigenvalues ​​after the time TS. Still taking the collection of 50 first eigenvalues ​​as an example, the corresponding calculation method of the first mean and the second mean is as follows:

[0091]

[0092]

[0093] Among them, α avg1 is the first mean, α avg2 is the second mean, TS is the time corresponding to the positive zero crossing point, and α is the first eigenvalue.

[0094] When the difference between the first mean and the second mean is greater than the preset mutation threshold, it is determined that the high-frequency mutation and the low-frequency mutation are synchronized; when the difference between the first mean and the second mean is less than the preset mutation threshold, it is determined that the high-frequency mutation and the low-frequency mutation are not synchronized. Continuing to use the above parameters, that is, α avg2 -α avg1 >η 0 , where η 0 is the preset mutation threshold, then Sync=1, it is determined that the high-frequency mutation is synchronized with the low-frequency mutation, and at this time, there is an arc fault in the non-adjacent branch. avg2 -α avg1 <η 0 , the synchronization flag can be set to Sync=0, and the high-frequency mutation is considered to be out of sync with the low-frequency mutation, indicating an arc fault in a non-subordinate line. No further alarm or line disconnection processing is performed. In this case, it is generally considered that an arc fault has occurred in an adjacent branch. It should be noted that for the convenience of calculation, the difference here generally refers to the size of the gap between the two, which is a positive number. In practice, the first mean can be subtracted from the second mean, or the second mean can be subtracted from the first mean. The corresponding mutation threshold is set according to the actual algorithm.

[0095] It is understandable that when Sync=1, the high-frequency mutation is synchronized with the low-frequency mutation. At this time, it is impossible to distinguish whether the arc fault occurs in the upstream or the subordinate line. This solution analyzes the second and third eigenvalues, that is, whether the high-frequency signal mean and amplitude are affected by the upstream notch network, to identify whether the arc fault occurs in the upstream or the subordinate line.

[0096] The implementation method is to further analyze the characteristics of the 50 consecutive second and third eigenvalues ​​in the cache; since arc noise is similar to pink noise, that is, the amplitude and frequency are approximately inversely proportional to 1 / f, within a narrow frequency band, we approximately assume that the amplitude values ​​are equal, that is, the frequency components f1, fc, f2 and their vicinity in the arc noise are approximately equal in amplitude. When the upstream high-frequency signal passes through the notch network and flows through the high-frequency sensor, signals of different frequencies will be attenuated to different degrees; please refer to Figure 4 , the closer the frequency component to fc is, the greater the attenuation is. Based on the above description, the local oscillator frequency is periodically changed, and the second and third eigenvalues ​​of different frequency components are correspondingly extracted. Since a high-frequency notch network is set at the front end of the high-frequency transformer, once the arc fault occurs in the upstream line, the high-frequency signal flowing through the high-frequency sensor will be suppressed. The degree of suppression is compared with the amplitude-frequency response curve of the high-frequency notch circuit, f sc The second and third eigenvalues ​​are the smallest under the frequency component of f s1 and f s2 In turn, the second eigenvalue and the third eigenvalue belonging to different frequency points in the sampling time window extracted by statistical sampling can be used to determine whether the arc fault is in the downstream line or the upstream line. The average value is taken here to better reflect the amplitude-frequency response law and eliminate the influence of accidental interference. The specific calculation of the third mean and the fourth mean belonging to different frequencies is as follows:

[0097] K1 is β n ∈f s1 The number of

[0098] K2 is β n ∈f sc The number of

[0099] K3 is β n ∈f s2 The number of .

[0100] K4 is ε n ∈f s1 The number of

[0101] is n ∈f sc The number of

[0102] K6 is ε n ∈f s2 The number of .

[0103] Where AVG(β n ∈f s1) is the second eigenvalue belonging to f s1 The third mean at frequency, AVG(β n ∈f sc ) is the second eigenvalue belonging to frequency f sc The third mean value when AVG(β n ∈f s2 ) is the second eigenvalue belonging to f s2 The third mean at frequency; AVG(ε n ∈f s1 ) is the third eigenvalue belonging to f s1 The fourth mean at frequency; AVG(ε n ∈f sc ) is the third eigenvalue belonging to f sc The fourth mean at frequency; AVG(β n ∈f s2 ) is the third eigenvalue belonging to f s2 The fourth mean at frequency.

[0104] The mean can be obtained by a preset algorithm, where if η>η 0 or γ>γ 0 , it means that the high-frequency signal mean or amplitude is affected by the upstream notch network, and it is determined that the arc fault occurs in the upstream line. At this time, no further alarm and line disconnection processing is performed; otherwise, it is considered that the fault arc occurs in the subordinate line, and the arc fault flag of the subordinate line can be set to 1, that is, ArcFaultLoadSide=1, and an alarm action can be issued through the alarm unit connected to the controller. This solution infers the location of the fault arc by calculating the characteristics of the high and low frequency components of the current in the line. Only when the location is in the subordinate line of the monitoring point, the arc fault is judged, thereby reducing the probability of accidental disconnection of the subordinate branch (no fault arc) with normal power consumption, and improving the reliability of the arc detection product.

[0105] The embodiment of the present invention also proposes a fault arc detection and positioning device, which includes a fault arc detection and positioning circuit. The structure of the fault arc detection and positioning circuit can refer to the above embodiment and will not be repeated here. Alternatively, the fault arc detection and positioning device may include a high-frequency trap circuit, a sampling circuit and a controller. The controller includes a memory, a processor and a fault arc detection and positioning program stored in the memory and executed on the processor. When the fault arc detection and positioning program is executed, the fault arc detection and positioning method described in the above embodiment is implemented. As a matter of course, since the fault arc detection and positioning device of this embodiment adopts the technical solution of the above-mentioned fault arc detection and positioning circuit or the fault arc detection and positioning method, the fault arc detection and positioning device has all the above-mentioned beneficial effects.

[0106] It is worth mentioning that the sampling circuit in the fault arc detection and positioning device includes a high-frequency sensor for collecting the high-frequency differential mode noise signal, and the sampling end of the high-frequency sensor is connected to the first mains power line and the second mains power line which are opposite to each other and cross each other. The collection of high-frequency differential mode noise signals is achieved through the design of the sampling end and the mains power line, which can reduce the interference degree caused by the spatial electromagnetic coupling after the arc fault of the adjacent branch to a certain extent.

[0107] In addition, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. The computer-readable storage medium may be a memory in a controller, or may be at least one of a ROM (Read-Only Memory) / RAM (Random Access Memory), a magnetic disk, and an optical disk, and the computer-readable storage medium includes a number of instructions for enabling a terminal device having a processor (which may be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0108] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for detecting and locating an arc fault, characterized in that: The method comprises: Obtaining a low-frequency current signal and a high-frequency differential-mode noise signal collected by a mains power monitoring point, wherein a high-frequency trap circuit is provided on the mains power incoming line before the monitoring point; Determine whether there is a fault arc within the monitoring range corresponding to the monitoring point; When there is a fault arc within the monitoring range, determining whether the arc fault is an adjacent branch arc fault according to a first characteristic value obtained by sampling the low-frequency current signal and used to identify the degree of low-frequency current mutation, wherein the first characteristic value is a parameter describing the degree of low-frequency current waveform mutation; When the arc fault is not the adjacent branch arc fault, the fault line position is determined to be an upstream line or a subordinate line according to whether the second eigenvalue and the third eigenvalue obtained by sampling the high-frequency differential mode noise signal are disturbed by the high-frequency notch, wherein the second eigenvalue and the third eigenvalue are the mean and peak-to-peak values ​​of all sampling points in the calculation window; Wherein, the step of determining whether there is a fault arc within the monitoring range corresponding to the monitoring point includes: Determine in sequence whether the second eigenvalue and the third eigenvalue in each unit time in the signal sampling time window are both greater than the corresponding characteristic threshold; Wherein, each time it is judged that the second characteristic value and the third characteristic value in the same unit time are both greater than the corresponding characteristic threshold, the counter is incremented by 1; each time it is judged that the second characteristic value or the third characteristic value is not greater than the corresponding characteristic threshold, the counter is decremented by 1; During the judgment process, when the value of the counter is greater than a preset value, it is determined that a fault arc exists within the monitoring range; The step of determining whether the arc fault is an adjacent branch arc fault according to the first characteristic value obtained by sampling the low-frequency current signal and used to identify the degree of low-frequency current mutation comprises: According to the first characteristic value, it is determined whether the high-frequency mutation and the low-frequency mutation are synchronous; wherein, when the high-frequency mutation and the low-frequency mutation are not synchronous, it is determined that the arc fault is an adjacent branch arc fault.

2. The arc fault detection and location method according to claim 1, characterized in that: The step of determining whether the high-frequency mutation and the low-frequency mutation are synchronized according to the first characteristic value comprises: After all the second characteristic values ​​and the third characteristic values ​​within the signal sampling time window are determined, the time points corresponding to all the positive zero-crossing points of the counter are obtained; Obtain a first mean value of all first eigenvalues ​​corresponding to before the moment and a second mean value of all first eigenvalues ​​corresponding to after the moment; When the difference between the first mean and the second mean is greater than a preset mutation threshold, determining that the high-frequency mutation and the low-frequency mutation are synchronized; When the difference between the first mean and the second mean is smaller than a preset mutation threshold, it is determined that the high-frequency mutation and the low-frequency mutation are not synchronized.

3. The arc fault detection and location method according to any one of claims 1 to 2, characterized in that: The step of sampling the high-frequency differential mode noise signal to obtain a second eigenvalue and a third eigenvalue comprises: Mixing the high-frequency differential mode noise signal with a local oscillator frequency signal whose frequency changes periodically per unit time, and filtering the mixed signal; wherein the local oscillator frequencies that change periodically are the first local oscillator frequency, the second local oscillator frequency and the third local oscillator frequency in sequence; The high-frequency differential mode noise signal after mixing and filtering is sampled to obtain sampling data corresponding to multiple unit times in the signal sampling time window, and the sampling data corresponding to each unit time is calculated to obtain the second eigenvalue and the third eigenvalue.

4. The arc fault detection and location method according to claim 3, characterized in that: The step of determining whether the fault line is located in the upstream line or the subordinate line according to whether the second characteristic value and the third characteristic value obtained by sampling the high-frequency differential mode noise signal are disturbed by the high-frequency notch wave comprises: Matching the second eigenvalue and the third eigenvalue with the center frequency corresponding to each of the local oscillator frequencies in sequence, so as to group all the first eigenvalues ​​and the second eigenvalues ​​respectively according to the matched center frequencies; calculating a third mean for each group when each center frequency matches the second eigenvalue and a fourth mean for each group when each center frequency matches the second eigenvalue; The location of the fault arc is determined to be in the upstream line or the subordinate line according to a preset algorithm, the third mean value and the fourth mean value; the preset algorithm is: γ=|AVG(ε n ∈f s1 )-AVG(ε n ∈f sc )|+|AVG(ε n ∈f s2 )-AVG(ε n ∈f sc )|-|AVG(ε n ∈f s2 )-AVG(ε n ∈f s1 )| η=|AVG(β n ∈f s1 )-AVG(β n ∈f sc )|+|AVG(β n ∈f s2 )-AVG(β n ∈f sc )|-|AVG(β n ∈f s2 )-AVG(β n ∈f s1 )| Among them, β is the second eigenvalue, ε is the third eigenvalue, and f s1 is the center frequency corresponding to the first local oscillator frequency, f sc is the center frequency corresponding to the second local oscillator frequency, f s2 is the center frequency corresponding to the third local oscillator frequency, AVG(β∈f) is the third mean, and AVG(ε∈f) is the fourth mean; when η>η0 or γ>γ0, it is determined that the arc fault position is in the upstream line.

5. The arc fault detection and location method according to any one of claims 1 to 2, characterized in that: After all the steps, the method further comprises: When the arc fault is located in a subordinate line, an alarm action is performed, and the alarm action includes at least one of sending an audible and visual alarm signal, disconnecting the subordinate line, and reporting arc fault information.

6. A fault arc detection and positioning device, characterized in that: The device includes: a high-frequency trap circuit, a sampling circuit and a controller. The controller includes a memory, a processor and a fault arc detection and positioning program stored in the memory and executed on the processor. When the fault arc detection and positioning program is executed, the fault arc detection and positioning method according to any one of claims 1 to 5 is implemented.

7. The arc fault detection and positioning device according to claim 6, characterized in that: The sampling circuit comprises a high-frequency sensor for collecting the high-frequency differential mode noise signal, and a sampling end of the high-frequency sensor is connected to a first mains power line and a second mains power line which are opposite to each other and cross each other.

8. A computer-readable storage medium, wherein the computer-readable storage medium is stored in a memory and, when executed on a processor, implements the arc fault detection and location method according to any one of claims 1 to 5.

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