428 results about "Waveform distortion" patented technology

The invention discloses an intelligent power distribution layered self-healing fault isolation and power supply recovery method, which is suitable for realizing rapid fault isolation and power supply recovery of a non-fault area when a power distribution system has a fault. According to the method, a hierarchical control framework is adopted, and intelligent switch equipment on the lower layer is responsible for collecting the current and voltage states of a line in real time and immediately completing local identification and fault section removal after a preset fault signal is detected; the fault information is then uploaded to a power distribution automation master station on the upper layer, the master station analyzes a recoverable power supply area in combination with the current network topology and generates a network reconstruction scheme, and a non-fault area is switched to a standby power supply path by controlling an interconnection switch; the system supports the backtracking analysis of historical data such as waveform distortion and partial discharge signals before a fault, identifies a potential abnormal trend, optimizes an operation strategy, and achieves a self-adaptive early warning function. The method has the advantages of being rapid in response, clear in structure and high in autonomy, and the reliability and continuity of the power distribution system can be remarkably improved.

The invention relates to the technical field of power system fault monitoring, and discloses a 10kV voltage transformer ground fault real-time monitoring method and system, and the system comprises a ground fault data collection module, a waveform distortion analysis module, a transient signal detection module and the like. Three-phase current, zero-sequence current and voltage waveform data are collected, a current harmonic component proportion, a zero-sequence current high-frequency transient energy value and the like are analyzed, a fault type is determined by combining a phase difference, and a fault position is positioned according to topological parameters and line impedance. And the temperature of the grounding down lead can be monitored, and the fault probability is evaluated and the threshold value is dynamically adjusted by machine learning. According to the invention, real-time accurate monitoring can be realized, fault types and positions can be accurately diagnosed, potential hidden dangers can be comprehensively monitored, the intelligence of a monitoring system is improved, the operation and maintenance cost and risks are effectively reduced, and safe and stable operation of the 10kV power distribution network is ensured.

The invention provides a multi-target tracking and interference cooperation method and system based on a millimeter wave radar. The method comprises the following steps: firstly, acquiring an original detection signal in real time by using a millimeter-wave radar carried by an unmanned aerial vehicle, establishing a track correlation sequence of each moving target, extracting interference waveform characteristics formed by signal coupling among a plurality of moving targets in the original detection signal, and then, according to a spatial distribution parameter of the interference waveform characteristics, determining a track correlation sequence of each moving target; correcting the space-time continuity judgment rule of the trajectory correlation sequence, and finally outputting an anti-interference cooperative tracking result based on the corrected space-time continuity judgment rule. According to the technical scheme provided by the invention, the industry pain point that waveform distortion interference of the millimeter wave radar in a dense target scene cannot be eradicated is solved, and the error correlation rate in a dense formation scene is also reduced.

The invention discloses a power transmission channel risk early warning evaluation method and system, and relates to the technical field of power transmission channel abnormal condition early warning, and the method comprises the steps: analyzing the current waveform distortion degree caused by a nonlinear load in a power transmission line through monitoring the voltage harmonic distortion rate, and evaluating the influence of harmonic waves on the insulation aging and heating loss of the line and equipment; the real-time gradient of the temperature of the wire is analyzed, abnormal heating conditions of different sections of the wire are judged, and the abnormal rising degree of the temperature of the wire and potential thermal damage accumulation caused by overload and poor contact factors are evaluated; by monitoring and analyzing multi-dimensional indexes such as the voltage harmonic distortion rate, the lead temperature real-time gradient, the sag dynamic deviation rate and the corona discharge intensity, the defect of a traditional monitoring means in the aspect of abnormal heating risk assessment is overcome.

The invention discloses a casting product appearance defect detection method and system based on machine vision, and particularly relates to the technical field of casting product defect detection. According to the method, casting materials of a production line are divided into different categories, the casting materials with abnormal absorptivity are identified, terahertz wave scanning is carried out on the casting materials, scattering images are obtained, and the stability of scattering point density distribution is evaluated; scanning by using a terahertz time-domain spectrometer, analyzing an amplitude fluctuation state of a time-domain signal and evaluating a waveform distortion degree; after comprehensive analysis, the quality of images captured by the imaging system is evaluated, the images are divided into different grades, defect detection is directly carried out on high-quality images, the quality images are centered, the accuracy of the images is analyzed, and the transmitting power and the scanning speed of terahertz imaging equipment are dynamically adjusted, so that the imaging quality is improved, and the accuracy and the efficiency of detection are remarkably improved; and the quality and safety of casting products are ensured, and the product quality problem and potential equipment faults caused by untimely defect detection are effectively avoided.

The invention relates to the technical field of electric power monitoring analysis, and discloses an intelligent analysis system for electric power monitoring data based on a mutual inductor. The system comprises a mutual inductor data acquisition and structuring module which acquires a current waveform, a voltage waveform and a harmonic component in real time, and generates a standardized monitoring data unit through preprocessing, field mapping and association identification establishment; the theoretical monitoring value calculation module constructs a dynamic calculation model according to historical power data, and an input standard data unit outputs a theoretical value; the rule conformity verification module is used for matching the equipment type with the operation rule and generating single compliance judgment; a multi-dimensional difference analysis module compares a theoretical value with a measured value from time domain deviation, frequency domain deviation and waveform distortion, and generates an equipment-level difference coefficient matrix; the association network construction module is used for constructing a multi-monitoring-point association map according to the equipment identifier and the position information; and the anomaly positioning and strategy generation module combines the map, compliance judgment and a difference matrix, calculates a risk score, generates an anomaly probability distribution map, positions anomaly and matches a monitoring strategy.

The invention belongs to the technical field of semiconductor testing, and discloses a novel automatic detection system and method for the electrostatic protection performance of a power device. A distributed parasitic parameter network model is constructed by acquiring packaging structure parameters of a to-be-tested power device and physical layout data of a test fixture, key parasitic parameter distribution is identified in combination with a time domain reflection measurement technology, a waveform distortion coefficient is calculated, and a spatio-temporal evolution model of electrostatic pulse propagation is constructed. Based on the model, a compensatory predistortion waveform is generated to counteract the parasitic effect of a transmission path, a device port response signal is collected in real time, an energy dissipation characteristic spectrum is extracted through wavelet packet decomposition, and quantitative evaluation of the electrostatic protection performance is achieved. According to the invention, the test precision and repeatability are improved, and the method is suitable for electrostatic protection tests of various novel power devices, especially high-frequency wide-band gap devices.

The invention discloses a modular reclosing circuit breaker protection system based on intelligent electrical cloud coordination, particularly relates to the technical field of intelligent power distribution network relay protection, and is used for solving the problems that fault diagnosis is delayed and a protection strategy cannot be generated in a fault clearing time window due to resource competition in a cloud coordination protection system. A dynamic preemption priority is generated based on power grid topology vulnerability and associated circuit breaker collaborative requirements by monitoring the load state of cloud computing node resources in real time; credibility attenuation control is carried out in combination with a fault current waveform distortion rate; when the resource preemption necessity exceeds a threshold value, freezing a periodic task thread and releasing computing resources, and opening up a high-priority communication channel at the same time; sending a fault recording compression instruction to a target circuit breaker terminal to obtain an edge preprocessing feature vector; and protection strategy optimization is executed in the released resources to generate reclosing parameters, and the reclosing parameters are issued and executed through a high-priority channel, so that quick response of a fault diagnosis task is realized.

The invention discloses an electric energy metering method under power grid waveform distortion, and particularly relates to the technical field of electric energy metering. The problems of false triggering of an energy compensation mechanism, metering deviation and electricity price settlement risks caused by zero-sequence current or false phase drift easily generated in a multipoint grounding or grounding fault power system in the prior art are solved. According to the anomaly identification and control method integrating zero-sequence current frequency domain characteristic analysis and three-phase phase deviation trend consistency judgment, the false phase deviation state is accurately identified through synchronous sampling, frequency domain analysis and trend consistency evaluation of three-phase voltage, three-phase current and neutral line current, and the false phase deviation state is accurately identified. The error compensation behavior is shielded in real time, the fundamental wave power metering mode is switched to, the electric energy metering accuracy is guaranteed through an error backtracking correction mechanism after recovery, and the anti-interference capability and metering reliability of the electric meter under complex working conditions are effectively improved.

The invention relates to a weak current cable fault positioning method and system, and the method comprises the steps: preliminarily locking a fault region through monitoring the axial stress change in real time, injecting a low-frequency pulse signal in a target section, analyzing the reflection waveform characteristics, and extracting the waveform distortion characteristics in a reflection signal; dynamically adjusting the output impedance based on the amplitude attenuation and time delay relationship, and if the dynamically adjusted output impedance cannot enable the output impedance of the injected low-frequency pulse signal to be synchronous with the impedance change trend of the cable, marking as an impedance mismatch point; after an impedance mismatch point is identified, other interferences are eliminated through multi-band signal attenuation difference analysis, and the position of a fault point is determined; the system is used for implementing the method. According to the method and system, stress monitoring and electric signal detection are combined, the detection range is remarkably shortened, the positioning precision and the detection accuracy are improved, and the method and system are suitable for weak current cable fault diagnosis in a complex environment.

The invention relates to the technical field of power distribution networks, and discloses a power distribution network fault self-recovery method and system based on machine learning, and the method comprises the steps: collecting the multi-source fault feature data of a power distribution network in real time, including the voltage and current waveform distortion feature, the load sudden change feature and the equipment temperature anomaly feature; and inputting the multi-source fault feature data into a multi-stage classification model for processing, and by setting a pseudo fault filtering module, establishing a typical interference feature library and setting dynamic filtering thresholds for different working conditions during real-time fault detection of the power distribution network, so that the recognition accuracy of various interference signals is ensured, and the fault detection accuracy of the power distribution network is improved. Meanwhile, similarity comparison is carried out on real-time collected data and pseudo fault features, whether the problems of signal distortion and noise pollution occur at the fault positioning position of the power distribution network or not can be detected in real time, the accuracy of fault type recognition is ensured, the misjudgment risk is reduced, and when strategy adaptation is abnormal, the matching degree of the self-healing strategy and the actual state of the power grid is ensured.

The invention discloses a harmonic control method and system of a frequency converter. The method comprises the following steps: acquiring an output voltage signal and a bus voltage signal of the frequency converter in a current time period; performing spectral analysis on the output voltage signal, and constructing a first frequency distribution characteristic curve; correcting the first frequency distribution characteristic curve according to the bus voltage signal to obtain a second frequency distribution characteristic curve; if the output frequency signal of the frequency converter generates frequency drift, tracking the frequency drift of the output frequency signal to obtain a frequency drift rule; performing voltage waveform distortion analysis on the output voltage signal to obtain a total harmonic distortion rate; performing parameter optimization on the filter according to the total harmonic distortion rate and the frequency drift rule, so that the third frequency distribution characteristic of the filter is matched with the second frequency distribution characteristic; in the next time period, the optimized filter is adopted to carry out frequency converter harmonic suppression; the harmonic suppression effect of the frequency converter can be effectively improved, and the power supply quality of a power grid is improved.

The invention provides an abnormal blood sampling inspection data evaluation processing method and system of a blood sampling system. Wherein the diffusion track dynamic state of an anticoagulant-blood contact surface in a blood sampling tube is tracked in real time, dielectric response waveform distortion characteristics on the two sides are synchronously collected through a capacitance sensor array, and diffusion form parameters are generated; curvature sudden change is analyzed to trigger an acoustic fluid device to modulate audio frequency and flow velocity, and a composite disturbance field is formed; performing capacitance axial scanning on the disturbed mixed fluid, extracting phase angle offset and gradient abrupt change point coordinates, and constructing a dielectric anomaly three-dimensional map; matching a standard dielectric model, positioning a coordinate set of a concentration gradient imbalance area and a coordinate set of an eddy current attenuation area, and generating an anticoagulant abnormal index and a mixed defect matrix in combination with phase angle offset difference; and establishing a data anomaly degree evaluation function based on the anomaly index and the defect matrix, dynamically associating a clinical error threshold, and outputting a test evaluation result. According to the invention, anticoagulant diffusion can be monitored in real time, and the mixing quality error can be accurately evaluated.

The invention discloses an alternating current power grid fault current waveform recording method, and relates to the technical field of power grid fault detection, when power grid waveform distortion or a high-resistance fault symptom is monitored, denoising and wavelet enhancement are performed on multi-source wave recording and simulation data through a data acquisition and preprocessing module, and an initial data set with multi-label high-order features is generated; the multi-task learning module corrects data distribution deviation in combination with domain adaptation and adaptive weighted loss, integrates physical priori such as arc discharge, and recognizes composite faults such as harmonic distortion, short circuit and grounding; through cross validation and noise simulation evaluation, the model verifies robustness through high-order calculus measurement, characteristic attention distribution can be verified in a visual mode, incremental training is automatically triggered when real-time recording reaches a threshold value, a comparison memory mechanism is applied, new fault information is adaptively absorbed, and a multi-label diagnosis closed loop is formed. And the accuracy and continuous optimization capability of multi-scene fault identification of the smart power grid are effectively improved.

The invention relates to the technical field of intelligent decision making, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses an equipment adaptive control method and device, equipment and a medium, and the method comprises the following steps: obtaining a multi-modal signal of an equipment detection target, and constructing a dynamic reference system according to the multi-modal signal; performing space-time alignment optimization on the multi-modal signal according to the dynamic reference system to obtain a space-time alignment signal, and performing dynamic calibration on the space-time alignment signal to obtain a calibration signal; performing transient waveform distortion feature extraction on the calibration signal to obtain a signal distortion feature; performing feature space mapping on the signal distortion features to obtain a feature mapping result; and generating an equipment early warning grade parameter according to the feature mapping result and a preset safety boundary distance, and dynamically adjusting a preset equipment control parameter according to the equipment early warning grade parameter. By analyzing the multi-mode signal, the dynamic adjustment of the equipment control parameters is realized, and the equipment detection precision is improved.

The invention relates to a multi-modal fusion pipeline damage positioning method, which comprises the following steps of: uniformly arranging piezoelectric transducer arrays along the circumferential direction of a pipeline, generating non-frequency dispersion L (0, 2) and T (0, 1) guided waves respectively excited by 70kHz sine pulses as excitation signals, and unidirectionally spreading the excitation signals along the pipeline; the method comprises the following steps: acquiring reflection echoes at a to-be-measured section of a pipeline, and performing matched filtering, omega-k domain filtering and circumferential modal decomposition on the reflection echoes to obtain two modal components in an L (0, 2) mode and a T (0, 1) mode; performing back propagation and focusing imaging on each modal component to obtain imaging results under two modals L (0, 2) and T (0, 1); and fusing the imaging results in the two modals to obtain a multi-modal fusion pipeline damage image. Compared with the prior art, the method has the advantages that the problem that sensitivity of different defect types is difficult to consider due to single-mode optimization and the problems of signal waveform distortion and energy dispersion existing in multi-mode signals are solved.

The invention relates to the technical field of water level online measurement, and discloses a water level measurement method and system based on ultrasonic waves. According to the invention, a variable time-sharing amplification circuit with a dynamic range is adopted, and the amplification times of echoes with different distances are automatically changed, so that the amplitude of an echo signal is kept to be more than five times of that of noise, and the influence of the noise on the measurement precision is effectively avoided; the method comprises the following steps of: receiving an echo signal, carrying out digital shaping on the echo signal according to a standard echo waveform near an echo peak value, and taking time corresponding to a waveform vertex after shaping as echo time, so that the influence of the measurement accuracy of echo waveform distortion is eliminated through the technology; meanwhile, the method that optimization is carried out after continuous three times of measurement is adopted, and the accidental phenomena of no echo and measurement value jumping can be effectively eliminated.

The invention relates to a wireless power transmission system parameter identification method based on a time domain differential model, and belongs to the technical field of wireless power transmission system control. The method comprises the following steps: establishing a parameterized time domain dynamic physical model; collecting system dynamic response data; constructing an optimization target based on a time domain residual error; and performing optimal parameter estimation based on iterative optimization. According to the method, a time domain dynamic physical model of a wireless power transmission system is constructed, and unknown parameters are solved through an iterative optimization algorithm with a minimum waveform matching error as a target. According to the algorithm, in an iteration process, a physical model is called to carry out forward differential equation solution, a time domain residual error between a model solution current and a real measurement current is used to drive a parameter estimation value to converge, and finally high-precision and high-robustness wireless power transmission system parameter identification under any working frequency is realized. The problem that in the prior art, due to static stiffness and sensitivity to waveform distortion of a theoretical model, the identification precision is insufficient is effectively solved.

The invention discloses a power transformation cabinet temperature and humidity remote monitoring and alarming method and system, and relates to the technical field of power transformation cabinet temperature and humidity monitoring and alarming, and the method comprises the following steps: a temperature and humidity monitoring system carries out the continuous monitoring of the temperature and humidity in a power transformation cabinet at a preset sensitivity, and monitors the temperature and humidity fluctuation; and any abnormal condition exceeding a safety range can be found and alarmed in time. By introducing the deep learning model to predict the load change trend, the response capability of the temperature and humidity monitoring system is remarkably improved. A traditional system depends on a fixed alarm threshold value and cannot deal with load fluctuation and rapid change in time, and a deep learning model intelligently predicts a load aggravation trend and generates an abnormal fluctuation index based on parameters such as real-time current waveform distortion and load response time. When the load is abnormal, the system automatically adjusts the alarm sensitivity, quickly captures the temperature and humidity change and triggers the alarm, thereby avoiding the temperature and humidity abnormity problem caused by the load fluctuation, and ensuring the safe operation of the equipment.

The invention relates to the technical field of power system court management, and particularly discloses a court identification and user binding method based on a special transformer acquisition terminal, which comprises the following steps: separating harmonic interference generated by start and stop of an electric welding machine through a kurtosis index and time-frequency energy entropy fusion detection method, and extracting a fundamental voltage and a pure power signal; constructing a dynamic time bending model containing phase consistency and gradient feature constraint based on the fundamental wave voltage, and calculating voltage track similarity to judge electrical coupling; for the users with electrical coupling, dynamic weight power cross-correlation analysis is fused to generate a comprehensive decision value, and a space-time diagram neural network is utilized to update a transformer area topology structure online in combination with a historical topology change event, so that the dynamic determination of the transformer area to which the users belong is realized; through multi-dimensional feature fusion and anti-interference algorithm design, the problems of phase deviation and waveform distortion caused by electric welding machine harmonic waves are reduced, and the transformer area identification accuracy and real-time performance are improved.

The invention relates to the field of crystal detection, and discloses a multifunctional comprehensive scintillation crystal and semiconductor material energy spectrum test system, which comprises a crystal adaptation module for judging the type and size of a placed crystal through an optical identification and parameter matching mechanism, and a signal acquisition module for amplifying, filtering and digitally processing an acquired signal, the signal correction module is used for correcting waveform distortion and baseline drift through a dynamic gain adjustment algorithm of a low-noise pre-amplifier and a multi-channel pulse analyzer; the data analysis module is used for generating an energy spectrum curve according to input signals and calculating energy resolution, counting rate, light attenuation time or carrier mobility, and the environment calibration module is used for dynamically evaluating shading degree, environment light, temperature and electromagnetic interference through an optical sensor and a temperature and humidity detector in the camera obscura and outputting updated calibration parameters. The method has the advantages of improving the detection efficiency, precision and consistency.

A system and computer-implemented method for data communication using a Physical Information Neural Network (PINN) is provided. At a transmitter, the method is configured to obtain source data to be transmitted, encode the source data into a codeword based on a Forward Error Correction (FEC) code, map the codeword to amplitude symbols, modify the mapped amplitude symbols to pre-equalized symbols including pre-distorted channel impairment symbols based on a predetermined physical model, and transmit the modified pre-equalized symbols to a receiver. And transmitting the digital data of the pre-balanced symbols as channel data through a channel. At a receiver, the method is configured to receive and demodulate channel data from a channel to produce an initial estimate of bits of the received channel data, mitigate channel noise and waveform distortion in the channel data based on the initial estimate, channel data composed of shaped non-uniform symbols is converted into a de-shaped bit sequence as a uniform data sequence, the de-shaped bit sequence is decoded to correct a residual error in the converted channel data, and the corrected channel data is stored in a data sink.

The invention relates to an electric power facility intelligent lock management and control method based on multi-dimensional right limit data processing, and the method comprises the steps: obtaining a curve of magnetic induction signal intensity and waveform changing with time during the operation of an intelligent lock, and carrying out the preliminary filtering processing of data through the analysis of waveform distortion and intensity attenuation characteristics, and obtaining a change trend sequence; the waveform distortion degree increment and the signal strength reduction rate caused by wear of the intelligent lock body are extracted through the change trend sequence, and the grading index of the wear degree of the intelligent lock body is determined; the lock cylinder gap change is combined with historical door body matching state data, the dynamic mapping relation between the magnetic induction signal intensity and the gap change is calculated, and the magnetic induction threshold value range is dynamically adjusted; and whether the intensity of the magnetic induction signal meets the target locking judgment standard or not is judged in real time, the lock control parameters are dynamically updated when the lock body runs, and optimized lock control state data are obtained.

The invention belongs to the technical field of data transmission, and particularly relates to a medical monitoring data transmission method, a monitoring method and an application method.The data transmission link is subjected to standardized conversion, and the method comprises the steps that connection modes of different devices are adapted through a physical interface or a wireless communication protocol, and a communication link is established; key parameters in the data flow are analyzed in real time through a lightweight neural network model to obtain an analysis result, potential semantic features of the data flow are automatically identified through multi-modal signal analysis to obtain an identification result, and a temporary analysis rule is dynamically generated based on the analysis result and the identification result; and the disassembled independent parameters are recombined according to a unified standard format. According to the method, equipment hardware does not need to be transformed, continuous data transmission of various equipment is ensured by automatically establishing a standardized data stream transmission channel, the workload of manually configuring analysis rules can be reduced through implementation, the risk of wrong analysis caused by waveform distortion can be reduced through multi-modal signal analysis, and finally, the private format difference of the equipment is eliminated.

The invention discloses an intelligent diagnosis system for power utilization abnormal information acquisition, particularly relates to the technical field of power system monitoring, and is used for solving the problems of waveform distortion and broadening caused by transmission line distribution parameters in the long-distance wired transmission process of an existing system. The system collects abnormal characteristic waveform data through a distributed intelligent terminal, selects a characteristic harmonic component in the power frequency voltage of a power line to construct an inherent test signal, extracts the envelope form similarity of a response signal and the test signal through envelope analysis as a first distortion evaluation index, and obtains a second distortion evaluation index after statistical significance judgment. Performing instantaneous frequency stability analysis on the signal with significant distortion to obtain a second distortion evaluation index, and finally generating a corresponding waveform compensation parameter based on double indexes to realize real-time compensation correction; the integrity of the abnormal characteristic waveform in the transmission process is effectively maintained, and the accuracy and reliability of power consumption abnormity diagnosis are remarkably improved.

The invention discloses a totem-pole circuit control method, a totem-pole circuit and electronic equipment. The totem-pole circuit control method comprises the following steps: acquiring an output voltage in a switch sub-circuit; obtaining periodic turn-on time and a second counting comparison value by using the output voltage; obtaining an input voltage in the energy storage sub-circuit, a minimum value of a preset negative current and a counting period set value; obtaining a maximum value of energy storage current in the energy storage sub-circuit in response to the condition that the periodic turn-on time is greater than the preset turn-on time; obtaining a first counting comparison value by using the counting period set value, the second counting comparison value, the maximum value and the minimum value; generating a first control signal by using the counting period set value, the second counting comparison value and the first counting comparison value; and adjusting the switching state of the switching sub-circuit by using the first control signal so as to adjust the energy storage current and the output voltage. According to the control method of the totem pole circuit, the conversion efficiency can be effectively improved, and the waveform distortion rate is reduced.

The invention relates to the technical field of relay protection testers, in particular to a verification method for a transient waveform of a relay protection tester. A microcomputer platform inputs a simulation current waveform I1 to a protection device through a switch and a protection tester, the microcomputer platform also inputs the simulation current waveform I1 to a verification alarm system, and the protection device receives a waveform output by the protection tester and then outputs a recovery current waveform I2 to the verification alarm system. The simulation current waveform I1 and the protection device recovery current waveform I2 are sequentially subjected to time axis alignment and preprocessing, then the waveform distortion coefficient mu, the attenuation rate difference upsilon and the higher harmonic content difference wj are calculated, and finally the mu, the upsilon and the wj are comprehensively evaluated to obtain an evaluation matrix R. According to the invention, the real-time simulation current waveform collected by the tester and the current waveform collected by the protection device are compared and corrected to form a closed-loop detection system, and the comprehensive evaluation matrix R is adopted in the waveform calibration method, so that misleading of a single evaluation standard to waveform correction is avoided.

The invention provides a power distribution network fault detection method and system based on distortion center point recognition, and the method comprises the steps: building a nonlinear fault waveform simplified mathematical model through a piecewise function, carrying out the fitting of a nonlinear fault waveform of a power distribution network based on the model, and obtaining a fitted nonlinear fault waveform curve function; solving the fitted non-linear fault waveform curve function through Fourier transform to obtain a characteristic interval in which the phase difference between the fundamental wave and the third harmonic of the non-linear fault waveform at the distortion center point has regular distribution; processing an input fault signal to be recognized based on a similarity principle, and recognizing a nonlinear fault waveform distortion center point; processing a nonlinear fault waveform distortion center point to obtain a fundamental wave and third harmonic phase difference; designing a fault detection criterion based on the fundamental wave and third harmonic phase difference; and when the continuous set times in the set duration meet the fault detection criterion, determining that the distribution network fault with the nonlinear waveform characteristic occurs.

The invention provides a solution for integrating a fault arc detection function into an existing intelligent electric energy meter, and aims at solving the problems that an independent fault arc detection device is low in popularization degree, complex in installation, high in cost, poor in compatibility and the like. The intelligent electric meter comprises a data acquisition module, an electric energy metering module, a fault arc detection sub-module, an A / D conversion module, a storage module, a communication and remote control module, a clock module, a display module, a key module, a power supply module and a main processor module. The data acquisition module acquires voltage and current signals through a voltage transformer and a current transformer, converts the voltage and current signals into digital signals, and extracts high-frequency characteristics and waveform distortion parameters. And the communication and remote control module realizes closed-loop control of fault alarm, user interaction and algorithm optimization. All the modules are coordinated to work through the main processor, and according to a real-time detection result, the following operations are automatically triggered: pushing alarm information; controlling a circuit breaker to cut off a power supply according to a preset threshold; and dynamic upgrading of the fault detection algorithm is completed based on an updating instruction issued by the remote management platform.

The invention discloses a composite voltage generation device and a cable insulation performance evaluation system and method, and relates to the technical field of high-voltage insulation testing. The composite voltage generating device comprises a synchronous controller, a direct current source, an impact source, an IGBT active protection unit and a magnetic isolation coupler, and by means of the excellent characteristics of the IGBT and the magnetic isolation coupler, the superposition time sequence accuracy of direct current and impact voltage is improved, and waveform distortion is reduced. The IGBT active protection unit comprises a first IGBT and a second IGBT, and direct-current voltage polarity switching can be realized through selective conduction of the IGBTs; the RC circuit is connected in parallel between the collector electrode of the first IGBT and the emitter electrode of the second IGBT, reverse current flowing back to the direct current source direction can be discharged through the RC circuit, the risk of energy flowing back is reduced, meanwhile, the magnetic isolation coupler can completely block direct current, and an impact source is protected against the influence of direct current voltage; according to the invention, the authenticity and reliability of cable insulation performance evaluation can be effectively improved.