748results about "Electric winding testing" patented technology

The present invention relates to the technical field of secondary device monitoring. Disclosed are an online monitoring method for an operating state of a secondary current loop neutral line, and a system. The method comprises: by using a high-precision sensor for collection and a composite filtering algorithm for processing, obtaining a secondary current fundamental component of each neutral line of a transformer substation which is not influenced by harmonic waves and transient states, and uploading the secondary current fundamental component to a protection information master station; retrieving originally configured access protection information master station information to obtain three-phase secondary current loop information of each bay of the transformer substation, summarizing secondary current information of all monitoring ranges, and performing grouping and classification marking on said information by transformer substation, bay and winding; and using the collection information for operation analysis, automatically identifying and confirming an operating state of the line, and on the basis of the operating state, calculating the outlier deviation linearity and the continuous dynamic trend deviation degree of each winding of each bay. The present invention solves the problem that intermittent faults in secondary current loop neutral lines are concealed and are not easily found, realizes comprehensive monitoring for the whole system, and can quickly and accurately position a specific winding and issue an abnormal early warning.

The invention relates to the field of motor health management and predictive maintenance, in particular to a motor stator winding insulation state evaluation method and system based on a digital model. Comprising the following steps: S1, collecting high frequency of a motor stator winding, and generating multi-physical-quantity real-time data; s2, calculating a dynamic capacitance reference value according to real-time data of multiple physical quantities; s3, performing subtraction operation on the high-frequency equivalent capacitance measurement value and the dynamic capacitance reference value, and extracting an insulation degradation residual signal; s4, constructing a self-adaptive dynamic detection threshold according to multi-physical-quantity real-time data; s5, judging whether the absolute value of the insulation degradation residual signal is greater than a self-adaptive dynamic detection threshold or not: if so, judging that an insulation degradation event occurs; if not, judging that the operation state is a normal operation state; and S6, in response to the insulation degradation event, updating the insulation degradation index, and generating insulation state evaluation based on the updated insulation degradation index. According to the invention, false alarm under severe load fluctuation is avoided, and the accuracy and reliability of evaluation are significantly improved.

The invention discloses a power transformer winding insulation state monitoring method, a power transformer winding insulation state monitoring device, power transformer winding insulation state monitoring equipment and a medium, and relates to the technical field of power system equipment state monitoring. And an improved particle swarm optimization algorithm is adopted to inversely calculate the insulation parameters of a plurality of windings of the transformer to the ground, so that the insulation state of each winding can be accurately evaluated. Compared with a traditional monitoring method, the method has the advantages that rich information contained in the common-mode leakage current can be fully utilized, the insulation degradation conditions of different windings can be accurately distinguished, more accurate insulation state evaluation is provided, and the safe operation level of the transformer is effectively improved. Moreover, multi-stage evaluation is carried out on the insulation state through a fuzzy comprehensive evaluation method, the insulation state can be comprehensively reflected, different severity degrees of the insulation state can be distinguished, the current state can be evaluated, the degradation trend can be predicted through dynamic indexes, and a scientific basis is provided for operation and maintenance decision making.

The invention discloses a stator winding grounding fault arc extinction method and system based on grounding transition resistance. The method comprises the following steps: S1, acquiring fundamental voltage of a neutral point and a machine end after normal operation and a grounding fault in real time; s2, calculating a fault phase potential EA1, and calculating a phase angle delta between the fault phase potential EA1 and the neutral point ground voltage UN1; s3, constructing a generator stator winding grounding fundamental wave fault analysis positioning equation, and substituting the measurement and calculation amount to complete fundamental wave fault positioning; s4, if multiple solutions occur in fundamental wave fault positioning, introducing a low-frequency injection quantity check criterion, and screening out a unique correct transition resistance value; and S5, carrying out arc extinction on the fault point of the neutral point of the generator in a high-resistance grounding mode. According to the method, the accuracy and reliability of fault positioning are remarkably improved, the possibility of misjudgment is eliminated, and an accurate compensation basis is provided for arc extinction.

The invention discloses a transformer winding monitoring and diagnosis data acquisition method, system and device and a medium, and belongs to the technical field of power equipment state monitoring, and the method comprises the steps: constructing a multi-scale wavelet transform and improved adaptive Kalman filtering fusion architecture, the multi-scale wavelet transform and improved adaptive Kalman filtering fusion architecture is used for acquiring a monitoring signal of a transformer winding; performing frequency division processing on the monitoring signal by using the multi-scale wavelet transform, and determining each scale coefficient; adjusting a noise covariance matrix based on improved adaptive Kalman filtering, and carrying out filtering processing on each scale coefficient to determine a filtering result; and reconstructing the filtering result into a reconstructed signal, and performing signal quality evaluation on the reconstructed signal to determine the signal quality of the transformer winding. Through multi-scale decomposition and adaptive filtering, the limitation of a traditional method under non-stationary signal processing and strong noise interference is solved, and the retention degree and the signal-to-noise ratio of signal features are improved.

The invention belongs to the technical field of power equipment maintenance, and particularly relates to a transformer winding fault diagnosis method, a terminal and a storage medium, and the method comprises the steps: obtaining frequency response curves of a transformer winding in a normal state and an abnormal state through a frequency sweep test, the head end of the primary side winding is connected with a sweep frequency signal and the tail end is suspended; determining the number of units of an equivalent network according to the number of the frequency response curve characteristic frequencies of the windings in the normal state, and reconstructing a normal winding equivalent network composed of a plurality of RLC units; according to the method, the high-precision equivalent network is constructed, the frequency response residual error analysis is performed, and the Pearson's correlation coefficient is combined to screen the high-correlation element, so that the specific position of the winding deformation or fault can be accurately positioned, the fault type is distinguished, and the limitation that the traditional frequency response method can only judge the overall deformation degree is thoroughly solved.

The invention provides a transformer winding state detection method based on temperature characteristics. The method comprises the following steps: (1) collecting operation data; (2) preprocessing the operation data; (3) taking the normalized transformer load current, the normalized active power, the normalized top oil temperature, the normalized ambient temperature and the normalized oil flow speed as input data, taking the normalized winding hot-spot temperature as output data, and constructing a data set; (4) establishing a VSN-TKAN-GRN deep learning network parallel computing model of the transformer winding hot-spot temperature considering the multi-head attention mechanism; (5) predicting the hot-spot temperature of the transformer winding based on a VSN-TKAN-GRN deep learning network parallel computing model; and (6) calculating the average relative error percentage of the transformer winding hot-spot temperature prediction result and the actual measurement result, and judging the winding state according to the change of the average relative error percentage. According to the method, the state of the transformer winding in operation can be efficiently and accurately judged, so that effective transformer operation and maintenance measures can be taken in time, and large faults are avoided.

The invention discloses a column type distribution transformer winding abnormity detection system and detection method. The detection system comprises a frequency response detection instrument, a signal coupling assembly, an impedance matching module and a data processing module. The frequency response detection instrument is used for outputting a frequency sweep excitation signal and collecting a winding response signal; the signal coupling assembly is used for isolating power frequency voltage and filtering low-frequency interference; the impedance matching module is used for adjusting output impedance and input impedance to realize matching with electrical characteristics of different windings; and the data processing module is used for constructing an equivalent detection loop model, completing frequency response simulation calculation and carrying out frequency domain analysis and anomaly identification on an actually measured response curve. According to the invention, electrified state diagnosis of distribution transformer winding structure abnormity (such as deformation and loosening) can be realized.

The invention discloses a diesel generator turn-to-turn short circuit fault protection method and system based on multi-parameter characteristics, and relates to the technical field of intelligent fault diagnosis of power equipment, and the method comprises the steps: carrying out the feature extraction of operation state monitoring data, carrying out the integration according to a time sequence, and generating a real-time feature sequence set; performing spatio-temporal feature coding and fusion on the real-time feature sequence set to generate a multi-dimensional spatio-temporal feature map; mapping the comprehensive matching score set into fault confidence according to a linear relation, obtaining a fault confidence sequence, judging a fault level in combination with a characteristic amplitude overrun condition, and generating a fault diagnosis result set; and executing hierarchical response based on the fault diagnosis result set, generating a hierarchical protection action execution record, and generating a short-circuit fault protection report in combination with the fault diagnosis result set. According to the method, quantitative similarity analysis of real-time features and standard modes is realized, the fault probability is accurately evaluated through a multi-parameter weighted fusion mechanism, and the reliability and interpretability of a diagnosis result are improved.

An insulation inspection system includes: a set of input terminals; a brush; a circuit connected to the set of input terminals, the brush, and a part being inspected, where the circuit includes at least one pair of resistors and a capacitor; and a control module configured to detect when a short circuit exists between a conductive element of the part and one or more conductive bristles due to insulative material missing on the part and as a result the one or more conductive bristles of the brush contacting the conductive element of the part.

The invention discloses a remote fault diagnosis method for a generator excitation system, and belongs to the technical field of generator excitation systems. The diagnosis method is realized based on a diagnosis system, the diagnosis system comprises a generator excitation system, the generator excitation system can maintain the stability of generator terminal voltage, adjust reactive power distribution, improve the stability of a power system, improve the dynamic performance of the power system and the like, and the generator excitation system is connected with a data acquisition device. The data acquisition device is connected with a monitoring center and a data transmission module. According to the remote fault diagnosis method for the generator excitation system, the structure is reasonable, various operation parameters of the excitation system can be monitored in real time, the advanced data analysis technology is utilized, the fault is deeply analyzed, operation and maintenance personnel are helped to give an early warning in advance and make a quick response, the reliability of power generation equipment can be greatly improved, the downtime is shortened, and the remote fault diagnosis method is worthy of popularization.

The invention provides a power distribution network zero sequence mutual inductor wiring polarity on-line proofreading method and system. The method comprises the following steps that 1, an active inverter is directly connected between a phase line of a power distribution network or a neutral point of a grounding transformer and the ground, or is connected between the phase line of the power distribution network or the neutral point of the grounding transformer and the ground through a boosting transformer; step 2, performing closed-loop control on the active inverter to inject zero-sequence current into the power distribution network; 3, in the injection process, judging whether the wiring polarity of the zero-sequence mutual inductor is wrong or not; 4, if only one of the zero-sequence voltage transformer and the zero-sequence current transformer has a wiring polarity error, correcting by modifying a software flag bit; and step 5, each power distribution terminal and the accessory device thereof complete online calibration of the wiring polarity of the zero sequence mutual inductor. By applying the technical scheme, the problem that the grounding fault section positioning research and judgment result is wrong due to the wiring polarity error of the zero-sequence mutual inductor of the power distribution terminal and the accessory device thereof can be avoided, and the method has good engineering application value.

The invention belongs to the field of high-voltage switch fault diagnosis, and discloses a high-voltage switch coil fault assessment method and related equipment, and the method comprises the steps: obtaining a real-time operation coil current curve, and enabling the real-time operation coil current curve to be aligned with a preset standard coil current curve through a dynamic time warping method; the problem of large discrete type of a coil current curve caused by complex and changeable field operation environments is effectively solved; according to the method, key features, namely a deconstructed sequence feature set, of an aligned curve are further extracted through time sequence deconstruction, the deconstructed sequence feature set is input into a pre-trained coil fault assessment model, and therefore the fault type and the fault degree of the high-voltage switch coil can be accurately assessed. By adopting the method, the accuracy and the stability of fault diagnosis are improved, the practicability and the adaptability of the method are enhanced, and the method can be better applied to a complex field operation environment.

The invention discloses a motor fault diagnosis method and system based on color image fusion symmetric point mode, and the method comprises the steps: converting a vibration signal and an electromagnetic signal of a motor into symmetric point mode images, and generating a color signal image fusing feature information; respectively abstracting the color signal images fused with the feature information into nodes and edges in a high-dimensional semantic space so as to construct graph structure data; and performing diagnosis classification on the graph structure data of the vibration signals and the electromagnetic signals by using respective capsule graph network models, and fusing diagnosis classification results of the vibration signals and the electromagnetic signals through a voting mechanism to obtain a final diagnosis classification result. According to the method, multi-channel time domain signals are converted into image expressions with dense information and consistent geometry, and unified feature modeling is carried out on the images based on a depth map structure network with topology perception capability, so that motor fault diagnosis with high diagnosis precision and strong robustness is realized.

To process measurements acquired using measurement instrumentation (41, 42), a processing system (50) is operative to perform a physics informed data-driven processing technique to determine at least one parameter related to an asset (20) of an electric power system (10). The processing system (50) is operative to perform a preprocessing (70) of measurements to generate input data, with the preprocessing (70) comprising identifying a subset of measurement locations for which the measurements are reliable for inputting to the data-driven processing technique and using measurements obtained at the identified subset for generating the input data. The processing system (50) is operative to estimate local heat loss, using the data-driven processing technique.

The invention relates to the technical field of fault testing, in particular to a dry-type air-core reactor turn-to-turn short circuit monitoring method based on a magnetic field difference method. According to the method, regularization constraint is introduced in an initial baseline stage to construct a reference electromagnetic coupling matrix, a heat accumulation index is recursively analyzed based on three-phase current energy, a thermally-induced magnetic field drift model is fitted in combination with magnetic field residual errors, and combined with combined constraint of the reference electromagnetic coupling matrix and the thermal drift model, a three-phase electromagnetic coupling model is established. The normal thermally induced magnetic field drift component is dynamically stripped in real-time monitoring; and under the constraint of a reference electromagnetic coupling matrix, fitting and optimizing a current vector through weighted least square state estimation, and integrating magnetic field and current two-dimensional deviation to obtain a structure consistency deviation index for fault monitoring. According to the invention, monitoring is carried out in consideration of a linear electromagnetic transfer rule and nonlinear thermal drift compensation, a complex magnetic field environment and a variable load operation condition of the dry-type air-core reactor are adapted, and continuous and reliable monitoring guarantee is provided for long-term stable operation of equipment.

The invention discloses a permanent magnet motor turn-to-turn short circuit fault diagnosis method considering complex working condition influence, belongs to the technical field of permanent magnet motor fault diagnosis, and aims to solve the problems that a turn-to-turn short circuit diagnosis result of a permanent magnet synchronous motor for an electric vehicle is easily influenced by working conditions and slight faults are difficult to diagnose under complex operation working conditions. The method comprises the following steps: step 1, high-frequency signal injection and information acquisition; injecting the high-frequency rotating voltage signal into a motor control system under a natural coordinate system, and collecting each phase of high-frequency current and each phase of high-frequency voltage of the motor through a band-pass filter; 2, subtracting the high-frequency voltage from the healthy voltage under the condition that the high-frequency signal is injected, and calculating to obtain a high-frequency voltage residual error of each phase; 3, according to the high-frequency voltage residual error of each phase, obtaining two fault characteristic quantities, namely the standard deviation of the high-frequency voltage residual error and the absolute average value of the high-frequency voltage residual error of each phase; and 4, judging whether a turn-to-turn short circuit fault occurs or not according to the fault characteristic quantity, and judging a fault phase.

The invention discloses a high-precision transformer fault detection method and system, relates to the technical field of transformer detection, is used for solving the problems of insensitive fault characterization and delayed diagnosis under a light load condition, and judges whether to enter a load judgment mechanism or not by acquiring input side access voltage information and counting low-load accumulated duration. When entering a load discrimination mechanism, detecting the start-stop behavior of a load branch and the temperature rise trend of a winding, calculating a light load index, identifying a light load state, carrying out region division on an iron core, collecting magnetic flux density data, and calculating iron loss balance characteristics aiming at iron loss deviation which is easy to occur under a light load condition; the insulation degradation coefficient is calculated by fusing the oil temperature peak value and the dielectric loss factor, and the abnormal index is generated with the iron loss balance characteristic, so that the early warning of the early hidden fault of the transformer can be realized in a light load scene in which the traditional temperature rise and current indexes are insensitive, and the operation reliability and maintenance efficiency of the transformer in a power distribution system are improved.

The embodiment of the invention discloses a waveform identification and correction method and system for winding deformation diagnosis, and relates to the technical field of transformer winding monitoring, and the method comprises the steps: synchronously collecting voltage and current signals, and carrying out the preprocessing; performing waveform disturbance type identification on the preprocessed signal, and dividing the disturbance type into harmonic dominant disturbance, voltage sag disturbance or compound disturbance, and harmonic dominant disturbance, voltage sag disturbance or compound disturbance; dynamically selecting a corresponding waveform processing path according to a waveform disturbance type identification result; processing the signal by adopting the selected waveform processing path so as to correct and reconstruct the signal and obtain compensated voltage and current waveform data; by constructing a disturbance identification and path adaptive processing mechanism, the problems of processing lag and compensation distortion of a general algorithm during dynamic signal disturbance are solved, the identification precision is improved, and real-time error correction is realized.

To process measurements acquired using measurement instrumentation (41, 42), a processing system (50) is operative to perform a data-driven processing technique to determine at least one parameter related to an asset (20) of an electric power system (10) and at least one uncertainty measure.

This invention provides a method for detecting quench in a superconducting coil using leakage current, comprising the following steps: Step 1: Determine a first detection connection point on the main superconducting tape adjacent to a first current connection point, wherein the first detection connection point and the first current connection point are equipotential points; Step 2: Determine a second detection connection point on the sampling superconducting tape, wherein the second detection connection point and the second current connection point are equipotential points; Step 3: Connect a leakage current sampling circuit to the first and second detection connection points. If the leakage current sampling circuit detects leakage current, it is determined that quench exists in the main superconducting tape. This invention uses a leakage current sampling circuit to solve the problem of difficulty in sampling the quench voltage of superconducting magnets.

The invention provides a method for suppressing internal misfire caused by turn-to-turn short circuit of a dry-type air-core reactor, and belongs to the technical field of dry-type air-core reactors. A turn-to-turn short circuit fault detection device combining differential protection and infrared thermal image detection is established to form a three-dimensional turn-to-turn short circuit feature vector, a four-dimensional internal misfire minimum ignition vector is obtained, and a fire development prediction model is established based on an Arrhenius equation. A double-layer game model for minimizing the upper-layer fire loss and minimizing the lower-layer fire extinguishing cost is constructed to optimize five-dimensional suppression vector parameters, and coordinated actions of suppression equipment such as power-off protection, forced ventilation, temperature suppression and inert gas release are controlled in real time through a suppression vector parameter adjustment function. The technical problem of fire suppression measure starting lag or excessive response caused by difficulty in accurately predicting the opportunity and degree of development of the turn-to-turn short circuit fault of the dry-type air-core reactor into the internal fire disaster is solved.

The invention relates to a current transformer with an open circuit protection function and a protection method thereof, and belongs to the technical field of transformers, the current transformer comprises a transformer body and a protection box arranged at the front end of the transformer body, and the protection box comprises an indication mechanism used for indicating an open circuit fault of the transformer body; the box body is fixedly connected with the mutual inductor body, and a wire outlet groove is formed in the box body and used for secondary wiring; the binding posts are arranged in the box body and are connected with the secondary coil of the mutual inductor body; the protection mechanism is arranged on one side of the binding post; and the alarm mechanism is connected with the protection mechanism and is used for sending open-circuit fault alarm information. According to the device, the binding posts are short-circuited quickly through the protection mechanism, abnormal operation of the transformer caused by open circuit is prevented, continuous operation of a system is ensured, and the reliability and stability of the current transformer are improved.

The invention discloses a motor winding fault monitoring method and system, and relates to the technical field of winding fault monitoring. According to the motor winding fault monitoring method, three-phase current waveform signal data and running state data of a set motor are obtained; based on a pre-trained current waveform identification model, in combination with three-phase current waveform signal data of the set motor, a winding fault induction characteristic value of the set motor is analyzed; based on the running state data of the set motor, the winding comprehensive disturbance risk characteristic value of the set motor is analyzed, and the winding fault risk assessment characteristic value of the set motor is analyzed in combination with the winding fault induction characteristic value. Therefore, the dynamic change rule of the current waveform in the time sequence is effectively described, the identification depth and the time response speed of fault causes are improved, and the accuracy of fault risk assessment is enhanced.

The invention relates to the technical field of transformer internal defect diagnosis, in particular to a distribution transformer internal defect diagnosis method and device based on virtual differential current. Comprising the following steps: synchronously acquiring data; calculating an actually measured differential current; establishing a differential current model; according to a differential current model, calculating a deviation value between the actually measured differential current of each phase and a model prediction value, and taking the deviation value as the virtual differential current; carrying out filtering processing on the virtual differential current; and judging defects. According to the method, a differential current model associated with winding impedance and excitation branch parameters is constructed based on operation data when the transformer has no defects, so that the model is bound with physical topological characteristics of the transformer, and virtual differential current (deviation between a measured value and a model predicted value) can reflect actual state change of the winding in the transformer; and the physical relevance and reliability of defect diagnosis are enhanced.

The invention provides an adjustable linear motor winding coil clamping test bench, which comprises a bottom plate, slide rails and an electric cylinder which are installed on the bottom plate, a slide block which is slidably installed on the slide rails, and an adjusting assembly which is arranged on the slide block, a permanent magnet array is arranged between the two slide rails, and a winding coil is arranged above the permanent magnet array; the open framework design that the framework is sleeved outside the winding coil can be compatible with coils with different sizes; the two moving plates synchronously move oppositely / reversely by rotating the two-way lead screw to adapt to clamping of coils with different widths, stress balance is ensured, the handle lead screw is movably connected with the supporting block and is in threaded fit with the frame, the overall height of the frame is finely adjusted by rotating the handle, and adjustment of air gaps between the coils and the permanent magnet array is achieved.

The invention discloses a five-phase motor weak turn-to-turn short circuit fault diagnosis method based on high-frequency voltage injection, and belongs to the technical field of motors, and the method comprises the following steps: S1, deducing a mathematical model of a five-phase permanent magnet synchronous motor weak turn-to-turn short circuit fault; s2, deducing high-frequency response characteristics when a turn-to-turn short circuit fault occurs in the five-phase permanent magnet synchronous motor after the high-frequency voltage signal is injected; s3, obtaining a value of a high-frequency response feature after the high-frequency voltage signal is injected, and calculating a value of a fault feature; and S4, judging whether a turn-to-turn short circuit fault and a fault phase occur or not according to the value of the fault feature. According to the five-phase motor weak turn-to-turn short circuit fault diagnosis method based on high-frequency voltage injection, whether the five-phase motor has a short circuit fault or not can be effectively identified, the fault phase can be accurately found out, and safe operation of the motor can be guaranteed.

The embodiment of the invention relates to the technical field of transformer fault detection, and discloses a transformer winding fault detection method and system based on frequency response and a medium, and the method comprises the steps: determining the equivalent inductance and equivalent capacitance of a transformer winding; and calculating a first-order grounding coefficient of driving point admittance by using the peak frequency and the valley frequency when the neutral point is grounded, and calculating a first-order open-circuit coefficient by using the peak frequency and the valley frequency when the neutral point is open-circuit. A first difference function is constructed through the equivalent inductance, the scaling rate and the first-order grounding coefficient, and a second difference function is constructed through the equivalent capacitance and the first-order open circuit coefficient. And fault detection of the transformer winding is carried out according to a comparison condition between fluctuation of the first difference function and the second difference function and a preset threshold value, and early sensitive detection is realized.

The invention provides a far and near field multi-axis sensing array coupled converter transformer monitoring method and system. The system comprises a near field four-axis sensing array, a far field four-axis sensing array, a signal-to-noise improving unit, an original point processing unit, an AD conversion unit and a background display control seat unit. Acquiring near-field and far-field noise signals without excitation, and coupling the near-field noise signals; taking the far-field noise signal as input, taking the coupled near-field noise signal as output, and training a deep network model; acquiring a to-be-detected signal and a field noise signal under excitation, and coupling the to-be-detected signal; taking the field noise signal as the input of the trained deep network model to obtain a reconstructed coupling noise signal; the method comprises the following steps: obtaining a denoised signal to be detected and a denoised coupling signal by using a coupling noise signal, carrying out signal processing to obtain a corresponding analog signal, converting the analog signal into a corresponding digital signal, and carrying out visual monitoring. The fault recognition rate and the operation and maintenance efficiency are remarkably improved.

The invention belongs to the technical field of safety protection of large generators, and particularly discloses a slot potential-based ground fault arc extinction and TVS fault identification method and system. The fundamental wave slot potential and the third harmonic slot potential of each slot conductor are calculated by obtaining the fundamental wave and third harmonic voltage of the neutral point and the generator end of the generator. And furthermore, the real fault position is determined through matching with the ground fault potential, so that fault positioning at any position in a full winding range is realized, the limitation of a traditional method is broken through, and the coverage range of fault positioning is remarkably expanded. According to the invention, through the voltage and current low-frequency components of the neutral point of the generator, the grounding transition resistance during a grounding fault and the grounding transition resistance during stabilization after arc extinction are respectively calculated, and the fault property is judged by comparing the transition resistances in different states, so that an instantaneous fault and a permanent fault can be accurately distinguished; simple and effective fault identification is provided, engineering realization is easy, and fault properties can be rapidly and accurately judged.