360results about "Effective value measurements" patented technology

The invention discloses an automatic anchor point searching and processing method for grid-connected test data of a photovoltaic inverter, and belongs to the technical field of automatic test of a power system. According to the method, a three-phase voltage and current signal output by a power grid simulator and an inverter power instruction signal are aligned through a high-precision time synchronization device; wavelet transform multi-scale noise reduction and moving average filtering combined preprocessing is adopted to improve the signal-to-noise ratio; identifying a voltage zero crossing point candidate set, a drop starting point candidate set and a recovery termination point candidate set based on a self-adaptive dynamic threshold value; transient energy characteristic verification is introduced for a voltage drop starting point; effective anchor points are confirmed through time window association of power instruction step changes. According to the method, the problems of low efficiency of manual key event point identification, misjudgment caused by noise interference, grid event and inverter response time sequence correlation missing and the like are solved, and the automation degree of test data analysis, anchor point positioning precision and control response time sequence analysis reliability are remarkably improved.

The invention relates to the technical field of electrical performance testing, in particular to a water supply equipment electrical performance detection system based on artificial intelligence, which comprises an electrical parameter acquisition module, an energy efficiency analysis module, an insulation performance evaluation module and a comprehensive diagnosis module. According to the invention, a three-phase voltage and current root-mean-square value is dynamically calculated through a broadband current transformer and a sliding window integration method, a 50Hz fundamental component amplitude is extracted to separate power frequency and high frequency harmonic waves, a continuous period energy efficiency ratio standard deviation triggers an insulation detection threshold value, and a parameter fluctuation and insulation degradation response mechanism is established. Harmonic interference correction synchronous processing energy efficiency ratio and leakage current integration, the detection error being lower than 5%, temperature rise rate linear regression and bearing current threshold value cooperative determination, winding aging cross validation, fault misjudgment rate reduction to 26%, closed-loop detection fusion transient capture, dynamic threshold value triggering and multi-parameter diagnosis, early warning success rate reaching 92%, and positioning response being reduced to 3 seconds.

The invention relates to the technical field of equipment maintenance, in particular to a distribution box remote diagnosis and maintenance system which comprises a voltage deviation detection module, a node hot stacking identification module, a channel stability classification module, a contact aging trend evaluation module and a period adjustment trigger module. According to the method, peak value change of effective voltage in each channel period in the distribution box is collected and compared with a preset criterion so as to accurately identify an abnormal discharge unit and accurately position a potential risk channel, and the change rate of equivalent series capacitance, contact conductance and contact resistance of a node is continuously sampled in a non-power-on state so as to accurately identify the potential risk channel. According to the method, multi-parameter same-trend change characteristics are determined, the contact aging process is accurately evaluated by integrating the parameter trend, the node trend and the maintenance plan period remaining time are subjected to cross comparison, the maintenance task advance opportunity is automatically judged, the maintenance plan is actively adjusted, the node fault missing detection risk is effectively reduced, and the maintenance timeliness and accuracy are remarkably improved.

The invention discloses an arc fault detection method and device based on voltage time difference variation, and belongs to the technical field of low-voltage power distribution network fault protection, and the method comprises the steps: enabling an arc fault point to be equivalent to an arc voltage source, and employing an arc voltage change rate and an arc voltage effective value, establishing detection feature description of a fault waveform generated by the arc voltage source, wherein the fault waveform presents a square-wave-like waveform; sampling adjacent cyclic wave voltages of a load side monitoring point, performing feature identification on the tail end voltage difference between adjacent cyclic waves based on detection features, and identifying a first fault waveform; and after the first fault waveform occurs, performing continuous identification counting on the arc faults, realizing identification of the continuous arc faults by using the difference between the non-fault waveform before the fault occurs and the waveform to be identified, and confirming the occurrence of the arc faults. The detection method is good in reliability, clear in physical significance, high in detection sensitivity, not affected by line parameters, capable of achieving detection only through a single monitoring point and lower in cost.

The invention provides an electric leakage detection alarm method and system for a distribution box. The method comprises the steps of collecting zero-sequence current signals of all branches; dividing a fundamental wave region, a low-frequency harmonic region and a high-frequency harmonic region, and calculating the energy ratio of each frequency band; identifying higher harmonic interference based on the high-frequency energy ratio; a load type is determined through an equipment identification module, and a zero-sequence current tolerance interval is generated in combination with a preset model; according to the invention, the zero-sequence current tolerance model associated with the equipment type is constructed, the equipment identification module and the model generation module are combined, and the dynamic zero-sequence current tolerance interval is generated according to the information of the equipment type, the rated parameter, the grounding mode and the operation cycle, and is used as an important basis for judging whether the electric leakage behavior belongs to a normal working condition or not. When the actual detection value is in the tolerance interval, even if the zero-sequence current level is high, the system can correctly identify the state as a non-fault state, so that the problem of false alarm or alarm dead zone is avoided.

The invention discloses a water pump motor fault detection method and system, and belongs to the technical field of detection, and the method comprises the steps: building an electrical operation state model based on current, voltage and three-phase balance degree, and outputting an electrical state coefficient; predicting a resistance degradation trend by using the historical winding / insulation resistance data set, and generating a resistance prediction coefficient; combining the electrical state, the amplitude under the load and the flow of the water pump to construct a vibration-flow matching coefficient; fusing the resistance prediction coefficient, the noise index and the temperature index, and outputting a fault evaluation coefficient through a fault evaluation model; and when the fault evaluation coefficient exceeds a threshold value, shutdown is triggered. The system correspondingly comprises an electrical analysis module, a resistance prediction module, a state evaluation module and a fault decision module. According to the invention, early fault accurate detection is realized by fusing multiple parameters, and the reliability of the water pump motor is improved.

The invention discloses a distributed grounding line selection method and system based on phase current abrupt change, and the method comprises the steps: obtaining three-phase current of a line, and calculating a phase current abrupt change real-time value, a phase current abrupt change derivative and a phase current abrupt change effective value in the three-phase current; judging whether the phase current break variable derivative and the phase current break variable effective value meet a preset phase current break variable starting condition or not in a continuous first time period; if the preset phase current abrupt change starting condition is met, whether the phase current abrupt change line selection action in a continuous second time period meets a preset phase current abrupt change line selection action condition or not is judged; and if a preset phase current break variable line selection action condition is met, determining that the line has a single-phase earth fault and the fault phase in the line is the phase with the maximum current break variable in the three phases. And a single-phase earth fault line can be quickly positioned.

The invention discloses a porcelain insulator zero value detection method based on voltage distribution and a related device. The method comprises the following steps: acquiring voltage effective value data of each insulator to be detected; drawing a curve according to the acquired voltage data of each insulator to be detected by taking the serial number of the insulator as a horizontal coordinate and taking the effective value of the voltage as a vertical coordinate; and analyzing whether a zero-value insulator exists in the to-be-detected insulator string according to the waveform trend of the curve. The step-down circuit with the core device being the capacitor is arranged in front of the input end of the voltage detection device, and the capacitor is connected to the porcelain insulator to be detected in parallel, so that the input voltage is effectively reduced, and the voltage detection device is protected from being damaged by overhigh voltage; the effective value of the measured voltage is obtained, the actual effect of the measured voltage can be reflected more accurately, the calculation process is simplified, and the efficiency is improved.

The invention discloses a bus voltage multi-dimensional real-time monitoring and analyzing method, system, equipment and medium, and belongs to the technical field of power system monitoring and fault prediction.The method comprises the steps that high-frequency synchronous sampling is conducted on bus voltage signals, discrete time sequence voltage signals are obtained and preprocessed, preprocessed voltage signals are obtained, and the discrete time sequence voltage signals are obtained; the method comprises the following steps: synchronously extracting multi-dimensional characteristic parameters of voltage, obtaining a characteristic parameter set, calculating a health degree index comprehensively representing a voltage state by utilizing a dynamic weighted fusion algorithm based on the characteristic parameter set, calculating an abnormal degree of a current value according to a historical data sequence of the health degree index, and performing fault grade judgment according to the abnormal degree. And performing trend extrapolation based on the health degree index and the historical data sequence of the key parameters in the characteristic parameter set, and generating predictive maintenance suggestions. According to the method, the crossing from passive alarm to predictive maintenance is realized, and the intelligent level and the operation and maintenance reliability of state monitoring of the power system are remarkably improved.

The present disclosure relates to apparatus and methods for determining a transfer function of a current measurement arrangement (118), or a change in a transfer function of the current measurement arrangement. In one aspect, an apparatus is disclosed comprising: a signal source (112) configured to apply a reference signal to a first current transducer (110) such that a first transducer output signal from the first current transducer comprises: a current measurement signal indicative of the first current passing through a first conductor (104); and a reference signal component resulting from the reference signal; and signal processing circuitry (116)configured to determine the transfer function of the current measurement arrangement by: extracting the reference signal component from the first transducer output signal; and determining the transfer function of the current measurement arrangement based on the transducer output signal.

The invention discloses an electric energy quality comprehensive monitoring method and system based on real-time waveform analysis. The method comprises the following steps: S1, acquiring an analog voltage signal acquired by a mutual inductor; s2, preprocessing to obtain a voltage waveform data segment; s3, performing multi-dimensional feature extraction to obtain a voltage waveform multi-dimensional feature vector; s4, extracting a voltage RMS effective value, a total harmonic distortion rate and wavelet packet energy; s5, inputting the voltage RMS effective value, the total harmonic distortion rate and the wavelet packet energy into a grading event pre-detection model to obtain an event feature subset coding vector; and S6, enabling the event feature subset coding vector to pass through an intelligent event fine classification model to obtain an electric energy event accurate classification result. According to the electric energy quality comprehensive monitoring method and system based on real-time waveform analysis disclosed by the invention, the accuracy and efficiency of electric energy quality event monitoring are greatly improved.

A power distribution monitoring system (100) is provided that can include a number of features. The system can include a plurality of monitoring devices configured to attach to conductor(s) on a power grid distribution network. In some embodiments, a monitoring device is disposed on each conductor of a three-phase network and utilizes a complex platform of software and hardware to detect faults and disturbances that can be analyzed to determine or predict the risk of wildfires.

The present invention relates to the field of artificial intelligence technology, and discloses a power situation perception prediction method and prediction system for a distribution network, including: calculating multidimensional power data of each node in the distribution network according to electrical data; extracting multidimensional power features corresponding to the multidimensional power data, and analyzing the power operation state of the distribution network through the multidimensional power features; using a time series model to perceive the power time series, and obtaining a situation prediction value of the distribution network; updating the power time series within a moving time window, determining the power situation triggering condition of the distribution network according to the updated power time series, and updating the model parameters in the time series model according to the power situation triggering condition; optimizing the situation prediction value using the updated time series model, analyzing the power situation perception of the distribution network using the situation optimization value, and obtaining a power situation perception prediction result. The present invention can improve the accuracy of the power situation perception prediction of the distribution network.

The invention relates to the technical field of power equipment on-line monitoring and fault diagnosis, and discloses a converter transformer bushing end screen voltage abnormity detection device and early warning method.The method comprises the steps that voltage data are collected through a wireless intelligent sensor, soft synchronization and self-adaptive windowing are achieved through a commutation notch feature locking mechanism, and a preprocessing signal is output; topological correlation clustering is executed to construct a virtual health reference, a dynamic residual sequence is extracted through time domain difference, and system side and equipment side features are decoupled; constructing a variational mode decomposition model, and calculating a characteristic entropy value of the intrinsic mode function; and comparing the entropy value with a threshold value, triggering an active impedance disturbance verification mechanism, controlling a sensor to access a load and comparing an actual voltage drop rate with a theoretical voltage drop rate, and determining an insulation degradation or poor contact fault. High-precision synchronization can be achieved without a hardware clock, and the problems that weak fault features are difficult to extract and virtual connection and insulation faults are difficult to distinguish in a high-impedance loop are effectively solved.

The invention relates to the technical field of equipment anomaly detection, in particular to a method for monitoring operation state anomaly of highway electric equipment. Comprising the following steps: collecting bus voltage and current effective value waveform data and voltage and current effective value waveform data of each feeder line; performing data detection on the voltage and the current of each node, and obtaining a power curve of each feeder line; de-noising the load data; detecting power change caused by load switching, and combining load curves in the same operation working state; solving the change of the mean value of the power curve in the same working state, and segmenting the power curve according to the change of the mean value; obtaining a probability density function curve of the power under the normal operation condition of the equipment; and measuring the difference degree between the feeder load power curve and the probability distribution under the normal operation condition of the equipment in the same operation state, and judging the operation state of the electric equipment, so that the accuracy of monitoring the abnormal operation state of the electric equipment is improved.

The invention provides a distribution line short-circuit fault processing device using voltage and current time sequence information. A distribution line short-circuit fault processing device utilizing voltage and current time sequence information is applied to a distribution line, a plurality of measuring points are arranged on the distribution line, each measuring point is provided with a circuit breaker, and the distribution line short-circuit fault processing device utilizing the voltage and current time sequence information is arranged on the measuring points. The distribution line short-circuit fault processing device using the voltage and current time sequence information comprises a calculation module, a first fault detection module, a first control module, a second fault detection module, a second control module, a third fault detection module, a fourth fault detection module, a fifth fault detection module and a third control module. According to the distribution line short-circuit fault processing device based on the voltage and current time sequence information, the requirements of rapid power supply recovery of an instantaneous fault and accurate isolation of a permanent fault can be met.

Disclosed in the present invention are a feeder automation test method and apparatus, a device, and a storage medium. The method comprises: calculating a voltage effective value and a current effective value of each node in a distribution network framework under different fault handling section conditions of a feeder automation system; sending the voltage effective values and the current effective values to a corresponding tester, such that after receiving the voltage effective values and the current effective values, the tester converts the voltage effective values into an analog voltage waveform, converts the current effective values into an analog current waveform, outputs the analog voltage waveform and the analog current waveform to a corresponding field power distribution terminal, and returns switch position change information of the field power distribution terminal; and comparing the switch position change information with preset standard feeder automation action logic in a corresponding fault handling section condition and then, on the basis of a comparison result, obtaining a feeder automation test result. The present invention can improve the reliability of feeder automation tests.

The invention relates to the technical field of industrial monitoring and intelligent fault diagnosis. The invention provides a fault monitoring method and system for electrical elements of a mixing station. The method comprises the following steps: collecting operation signals of electrical elements of the mixing station; performing signal anti-interference processing based on the operation signal to obtain a preprocessed signal; according to the pre-processing signal, fault characteristic parameters of electrical elements of the mixing station are extracted, and the fault characteristic parameters comprise voltage reduction starting conversion logic characteristics of a contactor and overload transient characteristics of a motor; based on the fault characteristic parameters, fault trend analysis is carried out, and element performance degradation trend and potential fault risk are identified; and according to a result of the fault trend analysis, generating a multi-stage early warning signal for triggering preventive maintenance operation. The problems of failure of fault feature extraction, signal distortion and lack of potential risk early warning caused by insufficient pertinence, weak anti-interference capability and low intelligent degree of an existing mixing station electrical element monitoring technology are solved.

The invention provides an uninterruptible power supply automatic switching device test method and system based on visual control, and the method comprises the steps: connecting a voltage collection end of test equipment to a secondary output terminal of a voltage transformer at a power supply side of an automatic switching device; and meanwhile, a secondary current signal of the current transformer is obtained and input to the test equipment, and a current output end is pre-connected to a protection side current input terminal. In the testing process, actual voltage and current are monitored in real time through a graphical user interface, and the testing equipment is controlled to synchronously output analog voltage and current. The method comprises the following steps: presetting an automatic test sequence and parameters, automatically applying test working conditions to the spare power automatic switching device by test equipment according to the parameters after starting, synchronously acquiring test data, and finally calculating performance indexes based on the test data and generating a test report. According to the method, the spare power automatic switching device can be comprehensively, accurately and safely tested under the condition that power supply is not interrupted.

The invention provides a bearing fault diagnosis method based on ISCV-VIT, and the method comprises the steps: firstly collecting a current signal when a variable frequency driver of a motor needs to operate according to the variable frequency driver, and processing the collected current signal through an ISCV method; the input current is diagnosed according to the visual converter model; the method comprises the following steps: firstly, carrying out data segmentation on a time domain signal processed by ISCV, then adding the data into an image patch sequence in a linear mode through a trained linear projection layer and position embedding, then inputting a new image color block sequence into a converter encoder, and splitting the input into a plurality of heads by a multi-head attention layer; the outputs of all the magnetic heads are connected and transmitted through the MLP magnetic head, and finally, the output initial diagnosis result is subjected to a soft voting method to obtain a final diagnosis result.

The invention relates to the technical field of electrical variable measurement, in particular to a filter fault detection method and system, and the method comprises the following steps: synchronously collecting an input current signal flowing through a filter and voltage time domain waveforms at the two ends of the filter based on a sine input voltage signal applied to the filter; the ratio of the peak voltage to the peak current in the initial stage is calculated, and the waveform transient amplitude ratio is obtained; and based on the waveform transient amplitude comparison, segmenting and sorting continuously acquired time domain waveforms according to a preset time window to generate an instantaneous electrical parameter sequence. An input current signal and voltage waveforms at the two ends are synchronously collected on the basis of application of a sine input voltage signal, the ratio of peak voltage to peak current is extracted to obtain waveform transient amplitude comparison, the sensitivity of waveform characteristics is improved, continuously collected time domain waveforms are divided through the waveform transient amplitude comparison, an instantaneous electrical parameter sequence is formed, and the accuracy of the waveform characteristics is improved. And the signal segmentation is more reliable.

The invention discloses a tree line touch fault early-stage leakage current prediction method, device, equipment and medium, and belongs to the technical field of distribution line grounding fault detection.The method comprises the steps that a multi-factor coupled tree body temperature rise time domain model is established, and the tree body temperature rise time domain model is a mathematical model describing tree body temperature rise changing along with time; the considered multiple factors comprise the tree size, the moisture content and the environment temperature; establishing a plurality of equivalent fault resistance-tree temperature models, wherein the equivalent fault resistance-tree temperature models are mathematical models for describing the change of equivalent fault resistance values along with the tree temperature; respectively calculating the prediction error of each equivalent fault resistance-tree temperature model, and selecting the equivalent fault resistance-tree temperature model with the minimum prediction error as the optimal equivalent fault resistance-tree temperature model; and calculating the equivalent fault resistance by using the optimal equivalent fault resistance-tree temperature model, and predicting the effective value of the leakage current according to the calculated equivalent fault resistance and fault phase voltage.

The invention belongs to the technical field of electronic information, and relates to an online low-voltage load monitoring and abnormal tripping positioning method and a related device. According to the method, electrical parameters of all monitoring points are collected in real time, key parameters are calculated after analog-to-digital conversion and filtering denoising, and the key parameters are compared with a set threshold value to judge whether the monitoring points are in an abnormal state or not; once an abnormal state is found, an early warning is generated and uploaded to a remote platform; and continuously monitoring the state of the main switch or the total current at the same time, and when tripping occurs, backtracking an abnormal record within a preset time period before tripping, and positioning the last or the most serious abnormal monitoring point as an abnormal source. The system comprises a data acquisition module, an analog-to-digital conversion module, a preprocessing module, a calculation module, a judgment module, an early warning module, a trip monitoring module and a positioning module. According to the invention, early warning before a fault and rapid positioning after tripping are realized, and the intelligent level, the operation and maintenance efficiency and the power supply reliability of the power distribution network are improved.

The invention relates to a high-precision residual current CT disconnection detection and multi-channel synthesis method. The method comprises the following steps: reading an input value of a dial switch; confirming a multi-channel synthesis mode; confirming the number of actually used channels; sampling precision detection; the main control unit reads 16-channel voltage data in real time and records the 16-channel voltage data; carrying out broken line detection if the line is broken; performing multi-channel synthesis; performing effective value calculation to obtain a synthesized channel voltage effective value; performing effective value conversion; and storing the actual current value of the synthesis channel in a Flash storage area. The invention also discloses a high-precision residual current CT broken line detection and multi-channel synthesis system. The residual current sampling precision is improved, the current sampling precision is within the range of 0.5%, the broken line false alarm condition is reduced, accurate residual current data are provided for subsequent vector synthesis and data processing, and the residual current monitoring accuracy is improved; the device has a broken line monitoring function, can diagnose short line faults in time, has broken line detection-free time aiming at broken line false alarm, and has a broken line state recovery function to collect residual current again when a channel returns to normal.

A method (1100) of calibrating a power measuring function (516; 716; 946) of a wireless power device (510; 710; 930) is presented. An alternating electric signal is fed (1110) through a wireless power transmitter coil (520; 720; 920) to drive the wireless power transmitter coil at an operating point. Voltage measurements and current measurements are performed (1120) upon said alternating electric signal or upon a current signal resulting therefrom in the wireless power device. A series of voltage values and a series of current values are produced (1130) from the voltage measurements and current measurements. A power value is calculated (1140) from the produced series of voltage values and series of current values. The method then assesses (1150) whether the calculated power value meets a specification. If not, the method introduces (1160) a compensatory change in either of the produced series of voltage values and series of current values to account for a phase shift between the voltage measurements and current measurements at said operating point, and stores (1170) the compensatory change for the wireless power device (510; 710; 940). This enables the power measuring function (516; 716; 946) of the wireless power device (510; 710; 940) to produce wireless power measurement results at said operating point which are consistent with said specification.

The invention discloses a wind power system permanent magnet synchronous motor turn-to-turn short circuit fault diagnosis method considering wind speed fluctuation. The method comprises the following steps: firstly, selecting a current space vector effective value as a diagnosis variable, and constructing a permanent magnet synchronous motor digital twinborn model by establishing a non-electrical quantity expression of a stator current space vector; the model outputs a calculated value of a stator current space vector effective value; and then a self-adaptive threshold value based on the wind speed change rate is designed based on analysis of a residual error between a measured value of a current space vector effective value of the permanent magnet synchronous motor and a model calculation value. And finally, the permanent magnet synchronous motor is monitored in real time in combination with a digital twin model and an adaptive threshold value, a fault phase is determined through a phase current effective value, and the severity is estimated by comparing a current space vector measurement value with a calculation value.

The invention relates to a method for identifying a single-phase earth fault of a power distribution network based on a phase current break variable characteristic, which comprises the following steps of: acquiring a three-phase current signal according to a set theoretical sampling frequency, calculating an effective value of the three-phase current signal, and completing three-phase current power-on judgment when specific conditions are met at the same time; carrying out frequency tracking sampling frequency real-time sampling monitoring on the zero-sequence current, extracting a zero-sequence current break variable difference current curve, and carrying out fault starting condition judgment on the difference current curve; extracting three-phase current fault component waveforms from a fault starting point, and then performing low-pass filtering processing on the waveforms to obtain effective frequency band characteristic waveforms and power frequency component characteristic waveforms; and calculating the fault characteristic quantity, and executing different single-phase grounding fault positioning algorithms according to different types of neutral point grounding systems. According to the method, the single-phase grounding fault of the power distribution network is identified by adopting the technical principle of definite physical rules through phase current and zero sequence current signals.

The invention discloses a method for supporting high-frequency AC / DC component acquisition in core grounding current monitoring, which belongs to the technical field of transformers and comprises the steps of system initialization and communication establishment, continuous sample acquisition, period preprocessing and frequency spectrum and DC component calculation. The technical problem of accurately collecting and analyzing the high-frequency harmonic component and the direct-current component of the grounding current of the iron core at the same time is solved, the dual-channel sampling and digital signal processing technology is combined, on the basis of calculating the total current and the power frequency component, multi-dimensional monitoring and intelligent analysis of the running state of the transformer are achieved, and the fault diagnosis accuracy of the transformer is improved. According to the invention, various industrial scenes can be covered, missing detection of potential faults is avoided, and the fault early warning capability and the operation state judgment precision are improved.

The invention provides a signal processing method and system, electronic equipment and a storage medium, and relates to the technical field of computers. The method comprises the steps of obtaining at least one to-be-processed signal; performing analog-to-digital conversion on each path of to-be-processed signal to obtain a digital signal sequence; storing each path of digital signal sequence into a corresponding first shift register, and determining a first average value of the first half of data in the first shift register and a second average value of the second half of data in the first shift register; on the basis of the first average value and the second average value, smoothing each path of digital signal sequence to obtain a smoothed digital signal; accumulating the square value of each path of smoothed digital signal to obtain an accumulated digital signal; calculating a third average value of each path of accumulated digital signals based on the shift operation; and performing squaring operation on the third average value based on a successive approximation correction method to obtain a root-mean-square value of each path of to-be-processed signal. Therefore, the accuracy and efficiency of signal processing can be improved.

The invention discloses a series fault arc identification method suitable for a low-voltage alternating-current power distribution system, which is different from a traditional fault arc detection method and comprises the following steps of: judging whether an arc fault occurs in a line or the line is in a normal state by using zero-sequence current as a detection signal; according to the method, the selected characteristic quantities accurately describe four stages of arc starting, arc burning, arc extinguishing and zero stopping of the fault arc, and a good fault arc detection effect is achieved for a low-voltage alternating-current power distribution system with complex scenes including multiple loads, multiple arc generation modes, multiple line topologies and the like.