3973 results about "Instrument transformer" patented technology

The invention relates to the technical field of control systems, in particular to a control system and a control method of an intelligent permanent magnet vacuum circuit breaker, and the system comprises a multi-source signal synchronous acquisition module, an operation mechanism box body of the permanent magnet vacuum circuit breaker and acceleration sensors arranged at preset positions around a permanent magnet operation mechanism, a voltage transformer and a current transformer are connected to a line interface, and a unified sampling frequency and a trigger condition are set. According to the method, vibration, voltage and current signals are synchronously collected at key parts of the permanent magnet vacuum circuit breaker, timestamps are applied, a data basis of multi-source information strong association is constructed, and the direct time sequence relation between the electrical transient state and the mechanical response can be revealed. Segmented windowing and frequency spectrum transformation are carried out on collected vibration signals, a time frequency energy distribution diagram is generated, and instantaneous frequency components and energy evolution details generated by non-stationary events such as impact and friction in the opening and closing process are captured.

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 discloses a primary and secondary fusion pole-mounted intelligent circuit breaker. The primary and secondary fusion pole-mounted intelligent circuit breaker comprises a fault detection module, a protection action module, a reclosing module and an information reporting module, the fault detection module collects multi-dimensional electrical quantity through a current transformer and a voltage transformer, and judges a fault and identifies the type in combination with a dynamic normal range and a duration threshold. The protection action module calculates the fault distance based on the correction impedance, judges whether to act or not by combining the current flow direction and the protection range, and selects a protection level according to the fault severity; the reclosing module dynamically sets an observation time window, distinguishes instantaneous or permanent faults through a retest verification mechanism, and adaptively adjusts a reclosing strategy; and the information reporting module uploads fault related information. According to the method, the problems of high misjudgment rate, poor protection selectivity, rigid reclosing logic and the like of a traditional circuit breaker are solved, and the accuracy, quickness and self-healing capability of power distribution network fault processing are remarkably improved.

The invention discloses a current transformer real-time state diagnosis system based on Internet of Things, which relates to the technical field of electrical equipment state diagnosis and comprises a reference construction module, a disturbance excitation module, a modeling identification module, a driving unwrapping module, a self-adaptive setting module and a closed-loop control module, in the operation process of a secondary winding loop of the current transformer, a nanosecond time synchronization reference is established, a phase reference baseline is locked, current vector trajectories are continuously collected based on the time synchronization reference and the phase reference baseline, and a discrete phase residual image is constructed. According to the method, through high-precision time synchronization, phase disturbance excitation, sparse modeling identification, driving unwrapping and self-adaptive setting control, hysteresis oscillation of the secondary circuit of the current transformer is accurately identified and suppressed, the fault diagnosis accuracy and the system stability are remarkably improved, and the limitation of a traditional method in the aspects of identification sensitivity and response capability is broken through.

The invention provides a fault detection method, device and equipment for a direct current transformer with variable magnetic flux density, and the method comprises the steps: obtaining a magnetic field recovery curve family through gradient pulse excitation, and extracting a characteristic spectrum which reflects the fatigue degree of an iron core; separating fast and slow recovery components by using a time scale decomposition technology, calculating a scale coupling factor and establishing a dynamic health reference; a hysteresis critical point is positioned by adopting a bidirectional approximation test, and a fault precursor is identified from hysteresis width parameters; extracting an intersection point position through curve family cross analysis, constructing an angle field, calculating an angle sequence, and quantifying a fault development speed; designing a self-adaptive excitation scheme based on the development speed, and identifying a fault resonance mode from the chaotic transition features; a multi-resolution space fault distribution diagram is generated through phase space trajectory deviation degree analysis; spatial distribution and time sequence evolution information are fused to calculate a comprehensive fault index, four-stage classification diagnosis is realized, and a complete mutual inductor fault detection technical scheme from early warning to accurate positioning is formed.

The invention relates to the technical field of power system measurement, and discloses a current transformer error dynamic monitoring method and system.The current transformer error dynamic monitoring method comprises the steps that current transformer time sequence data and a system event log are obtained; constructing a time sequence causal graph to represent the time correlation between the event and the error change; identifying potential causal links by applying a counter causal model; designing a multi-world simulation engine to generate an anti-fact scene; quantifying a causal effect by comparing actual observation with an anti-fact simulation result; establishing a monitoring mechanism to track key trigger events in real time; generating a dynamic causal interpretation report and adjusting a compensation strategy; according to the method, the limitation of traditional correlation analysis is broken through, the causal relationship and the correlation can be accurately distinguished, the real triggering factor of the error change of the current transformer can be accurately identified, the false alarm rate and the missing report rate are reduced, and the accurate dynamic monitoring of the error of the current transformer is realized.

The invention relates to the technical field of voltage control, in particular to a synchronous main shift gear automatic compensation voltage control system, which comprises an area load information acquisition module, a voltage instantaneous value and a current instantaneous value are periodically read through a voltage transformer and a current transformer which are deployed on a key feeder line or a user side in a specified area, and the voltage instantaneous value and the current instantaneous value are acquired; and calculating to obtain an active power value and a reactive power value, adding a synchronous timestamp and a node position code to each collected value, transmitting and collecting the coded voltage value, active power value, reactive power value and timestamp information, organizing and storing according to a regional and time sequence, and establishing a regional load real-time measurement data set. According to the method, real-time capturing and structured processing of the system call number, the parameter and the return value are carried out on the L4T kernel event triggered by the target process PID, a serialized system call track is obtained, and an execution process recording path mainly driven by process behaviors is formed.

The invention belongs to the technical field of simulation analysis, and particularly relates to a medium-high voltage switch cabinet internal humidity inversion calculation method based on simulation analysis, which comprises the following steps: establishing a geometric model of a switch cabinet, importing the geometric model into finite element simulation software to obtain a simulation analysis model, adding each physical field and computational domain and boundary conditions thereof, and calculating the internal humidity of a medium-high voltage switch cabinet. All the physical fields are coupled, and mesh generation is carried out; performing numerical solution on the simulation analysis model by using a transient solver to obtain a temperature and humidity distribution condition in the switch cabinet; the simulation analysis model is optimized, a simulation data set is constructed, and a PINN is trained; based on the environment temperature and humidity and the operation current collected in the actual operation of the switch cabinet, the trained PINN is used for prediction, and the steady-state relative humidity of the current transformer is obtained. According to the invention, based on the limited boundary monitoring data, efficient and accurate reconstruction of the humidity field of the key area in the switch cabinet is realized, and a feasible path is provided for equipment state sensing and condensation risk early warning.

The invention discloses a method for detecting abnormal metering performance of an intelligent electric energy meter, which belongs to the technical field of electric energy metering equipment and comprises the following steps of: 1, establishing a reference response curved surface of parasitic parameters of a voltage sampling resistor and a current transformer in the electric energy meter relative to temperature and humidity; step 2, during the operation period of the electric energy meter, acquiring the real-time measurement value of the parasitic parameter in situ; and step 3, matching the real-time measurement value with the reference response curved surface. According to the method, an active matching model library can be constructed by fusing an underlying physical model of a component and a mapping rule set for a complex environment with sudden change of plateau outdoor temperature and humidity, the internal mechanism that parasitic parameters change along with temperature and humidity is explained from the physical essence level, and the limitation of a pure data statistical method is made up; the dynamic error judgment threshold value can adapt to environmental stress changes in real time, and the accuracy of metering performance anomaly detection and the complex environment adaptability are effectively improved.

The invention provides an intelligent monitoring and early warning method based on multi-source information fusion, and belongs to the technical field of intelligent diagnosis and early warning, and the method comprises the steps: synchronously collecting the multi-modal data of a voltage transformer, the multi-modal data comprising voltage / current waveform, partial discharge signal, temperature and vibration data; preprocessing the multi-modal data, wherein a preprocessing method comprises waveform segmentation, spectrogram generation and scalar normalization; constructing a dynamic weight distribution mechanism: calculating a weight matrix based on the relevance between the time sequence features and the spatial features, and dynamically adjusting scalar weights by combining the physical coupling relationship between the temperature and the vibration to generate feature fusion weights; iteratively updating the weight matrix according to the real-time prediction error; fusing the time sequence features, the spatial features and the scalar features through the dynamic weight distribution mechanism to generate a comprehensive feature vector; and synchronously outputting a fault type classification result and an equipment health score based on the comprehensive feature vector, and calculating a real-time prediction error.

The invention relates to the technical field of voltage transformers, in particular to a voltage transformer real-time monitoring system based on broadband and edge calculation, which comprises the steps of collecting multiple paths of voltage transformer data, extracting peak values and zero cross points, comparing jump rising edge time differences, unifying time sequences, extracting extreme values and slope identification disturbance sections, and monitoring the voltage transformers in real time. Measuring amplitude continuous change to judge the offset trend, analyzing trend direction classification waveform fragments, and combining the three indexes to generate an operation state label. According to the method, a unified time sequence is constructed by comparing cross-channel jump rising edge time differences, multi-channel jump process alignment is achieved, the synchronous anomaly recognition capability is improved, the number of extreme values and the slope direction are extracted to recognize a disturbance dense section, continuous anomaly is judged by combining statistics of overrun, and the fluctuation trend is judged by tracking the deviation trend between extreme values. And based on the three-index combination classification operation state, the anomaly identification precision is improved.

The invention discloses a fault diagnosis method and system for a metering error of a voltage transformer, and relates to the technical field of power equipment fault diagnosis, and the method comprises the steps: obtaining the historical electric quantity data of a secondary side under the normal operation of the voltage transformer, and carrying out the noise reduction and normalization preprocessing; establishing an initial principal component analysis model according to the preprocessed historical electric quantity data, and calculating to obtain a statistic control threshold value; updating a mean vector and a covariance matrix of the model by adopting a dynamic strategy based on real-time acquired new electric quantity data of the secondary side of the voltage transformer; and calculating a new statistic according to the updated mean vector and the covariance matrix, comparing the new statistic with a statistic control threshold value, and if the new statistic is greater than the statistic control threshold value, determining a metering error fault. According to the invention, the model parameters can be updated according to the real-time change data output by the voltage transformer, the adaptability to different metering error ranges of the voltage transformer is improved, and the detection precision is improved.

The utility model belongs to the technical field of medium-voltage power distribution systems, and discloses an isolating switch device and a switch cabinet, the isolating switch device comprises an insulating rod, a conductive block, a conductive sheet and an operating mechanism, the conductive block is sleeved on the insulating rod, the conductive sheet is fixedly connected with the conductive block, and the operating mechanism drives the conductive sheet and the conductive block to rotate through the insulating rod. Therefore, the conducting strip is selectively connected or disconnected with the circuit breaker connector bar, and the conducting block is electrically connected with the voltage transformer in the rotating process. An isolating switch device is additionally arranged between a circuit breaker and a voltage transformer in a switch cabinet, an operating mechanism is utilized to drive a conducting strip and a conducting block to rotate through an insulating rod, the conducting block and the voltage transformer keep electrical connection in the rotating process, the position of the conducting strip is changed in the rotating process, and then the conducting strip is selectively connected with or disconnected from a circuit breaker connector bar. The structure is simplified, the number of elements is reduced, flexible operation can be achieved, and the stability and reliability of the disconnecting switch device can be guaranteed.

The invention belongs to the technical field of mutual inductor verification, and particularly relates to a data processing method for testing a current mutual inductor, so as to solve the technical problem that an existing verification method cannot truly reflect the comprehensive error of the mutual inductor, and the method comprises the following steps: S1, obtaining the current waveform data of a tested current mutual inductor; s2, deducting the exponential decay aperiodic component from the original current waveform data to obtain corrected current waveform data; s3, reconstructing to obtain de-noised current waveform data; s4, acquiring fundamental waves of the primary side current and the secondary side current and setting amplitude and phase angles of subharmonics; s5, calculating an initial ratio error and an initial angle error of the current transformer; s6, generating a ratio error compensation vector and an angular difference compensation vector; and S7, respectively carrying out vector summation on the initial ratio error and the initial angle error with the ratio error compensation vector and the angle error compensation vector to obtain the final ratio error and the final angle error of the current transformer. And the test accuracy and reliability of the ratio difference and the angle difference of the current transformer are improved.

The invention relates to the technical field of power system relay protection, and discloses a relay protection device mutual inductor adjustment system and method, and the system comprises a system connection initialization module, a data collection reference data generation module, a power frequency background signal offset module, a pilot frequency current injection error calibration module, and a calibration result verification output module. The method comprises the following steps: initializing sampling frequency of a to-be-calibrated mutual inductor and calibration source output precision of a calibration system, collecting amplitude and phase data of real-time power frequency current of the mutual inductor, generating offset current with equal amplitude and opposite directions through power electronic compensation based on reference data, optimizing offset current parameters through a closed-loop adjustment algorithm, and adjusting the offset current parameters through a closed-loop adjustment algorithm. Power frequency background signal offset is completed, pilot frequency calibration parameters are set, a difference value between a mutual inductor pilot frequency output signal and a calibration source standard signal is extracted by adopting a zero pointing technology, an optimal calibration coefficient is automatically calculated, verification of a calibration result is completed, and accuracy and reliability of the calibration result are ensured.

A method, apparatus and system for state evaluation of metrological characteristics of a capacitor voltage transformer, relating to the technical field of voltage measurement. The method comprises the following steps: acquiring operation data of a capacitor voltage transformer, establishing a metrological performance evaluation model, and obtaining a statistical control threshold (S1); collecting in real time the operation data of the capacitor voltage transformer, and calculating a statistic of the operation data by means of the metrological performance evaluation model (S2); comparing the statistic of the operation data with the statistical control threshold to determine whether a fault occurs in the capacitor voltage transformer (S3); and detecting a change trend of a primary signal and a secondary signal of the tested capacitor voltage transformer to determine whether metrological characteristics are abnormal (S4). In the method, the concept of time is introduced, by providing a timestamp, the influence of newly obtained data on the metrological performance evaluation model is greater, and by means of real-time update, the metrological performance evaluation model can be updated, so that when in a stable state, the detection time is reduced, and the model calculation is reduced.

The invention provides a mutual inductor loop resistance dynamic compensation correction method and device, and relates to the technical field of circuit testing, and the method comprises the steps: constructing a structural feature tensor and an environmental interference tensor according to the structural parameter information and environmental parameters of a primary winding and a secondary winding; training a dynamic compensation model based on the structural feature tensor, the environmental interference tensor and historical loop resistance test data; injecting a set direct current into the primary winding, obtaining an initial voltage signal sequence at two ends of the primary winding, and constructing a test state tensor in combination with the current loop current and the real-time environment parameters; inputting the test state tensor into the dynamic compensation model, and outputting a non-target resistance compensation value at the current moment; and based on the non-target resistance compensation value, correcting an initial loop resistance value obtained by calculating the initial voltage signal sequence to obtain a compensation resistance value of the target mutual inductor loop. According to the invention, the accuracy of mutual inductance loop resistance testing can be improved.

The invention relates to the technical field of wireless communication, and particularly discloses a high-voltage transformer remote metering monitoring system based on 5G network slicing, which senses network performance in real time by constructing a multi-dimensional network state matrix, performs path rehearsal and resource allocation calculation by using a digital twinning technology, and realizes remote metering monitoring of a high-voltage transformer. Generating a candidate transmission path set with optimal time delay consistency and a corresponding wireless resource block allocation scheme; calculating a path resource allocation factor and combining with network load prediction to generate an optimal resource scheduling strategy; and finally, converting the strategy into a specific network control instruction, establishing a special transmission channel with deterministic service quality, and implementing real-time monitoring and maintenance.

The invention discloses an on-line qualitative detection method for partial discharge of power equipment, which comprises a detection system and detection steps, and also comprises the following steps: the detection system comprises a high-frequency partial discharge detector for detecting a high-frequency current transformer; the ultrahigh frequency detection system is used for detecting electromagnetic wave radiation which is generated by partial discharge and has extremely short duration time; the ultrasonic detection system is used for detecting sound waves and ultrasonic signals generated along with energy release when partial discharge occurs; a transient ground voltage method detection system is used for live-line detection of equipment such as a medium-voltage switch cabinet. According to the online qualitative detection method for the partial discharge of the power equipment, different detected equipment and different detection methods are adopted to perform online detection on the partial discharge of the equipment, so that the early partial discharge phenomenon of the power equipment can be found in time, the long-term discharge monitoring data of the power equipment can be stored, and the overall detection effect is improved.

The invention provides a current transformer dielectric loss anti-interference measurement method based on a variable frequency power supply, and relates to the technical field of power detection, and the method comprises the steps: constructing an excitation channel, collecting a background response signal, recognizing a main interference frequency through combining a frequency tracking algorithm, and dynamically constructing a frequency deviation parameter; generating a pair of non-power-frequency excitation frequency control variable-frequency power supplies to output sine wave excitation signals; excitation voltage and response current signals are synchronously collected to form sampling signals, notch frequency is set according to frequency deviation parameters, main interference is filtered out, and first processing signals are obtained; performing weighting processing by constructing a window function matched with the frequency band characteristic to generate a second processing signal; the complex amplitude and phase information at the target frequency is extracted, the complex impedance is calculated based on the complex current method, the dielectric loss value of the current transformer is finally output, and the anti-interference capability and precision of measurement are effectively improved. According to the invention, the interference in the dielectric loss measurement of the current transformer can be processed, so that the measurement precision is improved.

The invention discloses a voltage transformer metering error evaluation method, which relates to the technical field of voltage transformer metering and comprises the following steps of: constructing a synchronous acquisition system of multiple groups of voltage transformers in a transformer substation, acquiring original voltage data, constructing a virtual reference voltage generation model and outputting a reference voltage sequence; the method comprises the steps of establishing a virtual reference voltage model, calculating error statistical characteristics, marking the operating state grade of the voltage transformer, evaluating health scores according to the error characteristics, outputting a scoring result, receiving inspection feedback comparison differences, updating the model, generating an analysis chart, and uploading the analysis chart to a client display and linkage operation and maintenance system. On-line error evaluation is realized, multi-source data are fused, error features are dynamically extracted, an operation state is marked, a health scoring and early warning mechanism is established, a feedback closed loop is introduced to optimize model precision, an evaluation result is displayed in a chart form, operation and maintenance scheduling is assisted, and the real-time performance, the accuracy and the self-adaptive capability of evaluation are improved.

The invention relates to the technical field of power system fault monitoring, and discloses a measurement switch fault identification and early warning system, which comprises a signal acquisition unit, a feature analysis unit, a fault judgment unit and an early warning trigger unit. The signal acquisition unit acquires a potential fluctuation sequence and an exciting current pulse sequence through a contact voltage sensor and a coil current transformer; the feature analysis unit extracts time-frequency domain and statistical domain feature groups by means of wavelet transform and moment function analysis; the fault judgment unit generates a fault judgment vector by adopting kernel principal component analysis fusion features; and the early warning triggering unit triggers four-level early warning by using dynamically updated grading threshold values (including historical reference values and online dynamic values). According to the system, through multi-modal feature fusion, dynamic threshold adjustment and a grading early warning strategy, accurate identification and grading early warning of measurement switch faults are achieved, the fault identification accuracy and early warning timeliness are improved, and the system is suitable for the field of electric power and industrial automation.

The invention relates to a CVT error evaluation method and device, error evaluation equipment and a storage medium, and belongs to the technical field of mutual inductor error recognized.The CVT error evaluation method comprises the steps that a first data set is restored to a primary voltage level based on voltage proportionality coefficients of multiple CVTs to obtain a second data set, and a difference matrix is constructed based on the second data set; establishing a likelihood function based on the difference matrix, and converting the likelihood function into a posterior probability density function based on a Bayesian formula; extracting data corresponding to a preset number of CVTs from the second data set to construct a third data set, and determining a prior probability density based on the third data set; and based on a multi-chain MCMC algorithm fused with plant rhizome growth and a posterior probability density function, determining error values corresponding to a plurality of CVTs when the posterior probability density is maximum. According to the method, the accuracy of CVT error evaluation is effectively ensured, and meanwhile, the error evaluation efficiency is also improved.

The invention discloses a partial discharge signal denoising method based on STFT-SVD and Bayesian kurtosis threshold adaptive optimization, and the method comprises the steps: collecting an analog signal outputted by a high-frequency current transformer, carrying out the analog-to-digital conversion, obtaining a one-dimensional time domain signal sequence, carrying out the DC component removal and amplitude normalization of the signal, and obtaining a preprocessing time domain signal; performing short-time Fourier transform on the preprocessed time-domain signal to obtain a time-frequency spectrum, suppressing low-amplitude noise by adopting a soft mask method, and retaining main characteristics of partial discharge pulses; performing singular value decomposition on the time-frequency spectrum after soft masking, automatically selecting a principal component number according to a principal component, and adaptively reserving a main signal component to obtain a principal component spectrum; and performing inverse short-time Fourier transform on the principal component atlas to reconstruct a time domain signal, adaptively selecting a kurtosis threshold in combination with a Bayesian optimization algorithm, and outputting a denoised time domain signal.

The invention discloses a sensor clamping mechanism and a mutual inductor crimping fault detection device and method, and relates to the technical field of mutual inductor detection. In a project verification process of an existing voltage-withstanding table and an error table, abnormal conditions such as inclination of a mutual inductor body, inaccurate tray positioning, abnormity of a magnetic switch, air leakage of an air cylinder air pipe and the like occur, so that a terminal stud of a test table cannot be in contact with a secondary side terminal of a mutual inductor to be tested; and detection interruption or false detection of a corresponding mutual inductor exists, so that the verification efficiency is reduced. According to the frame body, the measuring rod, the elastic piece and the sensor, the sensor can detect the relative displacement between the measuring rod and the frame body, if the relative displacement is within a normal range, the terminal stud is in successful crimping contact, and if the relative displacement exceeds the normal displacement range, the terminal stud has a crimping fault. Therefore, the system judges that the wiring terminal of the to-be-detected mutual inductor is failed in crimping with the wiring end, automatically identifies the crimping fault of the wiring end, and improves the operation efficiency of an assembly line.

The invention discloses a current transformer oil level monitoring system based on ultrasonic echo detection, which relates to the technical field of electric power monitoring and comprises the following steps: acquiring original echo time sequence data; calculating the distance between the transmitting end and the top of the metal expander by combining the propagation velocity of the ultrasonic waves in the air; and when the oil level height value is lower than a set threshold value, an alarm signal is triggered. According to the invention, the problems of easy clamping stagnation, complex installation, large temperature drift and environmental interference and the like of the traditional float-type, pressure-type and window observation methods are effectively overcome, remote uploading and local acousto-optic prompt are supported, and intelligent inspection and fault pre-warning identification under unattended operation are realized; and the operation safety, the monitoring reliability and the operation and maintenance intelligent level of the oil-immersed current transformer are remarkably improved.

The invention relates to the technical field of power data analysis, in particular to a line loss abnormity associated mutual inductor insulation fault positioning method. Collecting multi-source operation data of a target station area, and obtaining a datum line loss rate sequence, a residual component sequence and an auxiliary feature vector based on the multi-source operation data; according to the reference line loss rate sequence, obtaining a comprehensive sensitivity vector representing the influence degree of the mutual inductor on the line loss; obtaining a preliminary diagnosis result according to the comprehensive sensitivity vector, the residual component sequence and the real-time load rate; performing spatial logic verification according to the preliminary diagnosis result and the electrical topological graph of the transformer area to obtain a fault positioning list; generating a correction amount according to the fault positioning list and the corresponding comprehensive sensitivity vector, and correcting the line loss rate according to the correction amount; and meanwhile, feedback optimization is performed on the machine learning model according to complete data of the diagnosis. According to the invention, accurate and efficient diagnosis and correction of the line loss abnormity of the target station area can be realized.

The invention provides a fault early warning method and system for power transmission, transformation and distribution equipment, and relates to the technical field of power transmission, transformation and distribution equipment, and the method comprises the steps: carrying out the real-time monitoring of a transformer through a sensing module, and obtaining a real-time gas concentration-generation rate, a real-time temperature rise monitoring value, and a real-time integrated monitoring parameter; the method comprises the following steps: periodically sampling a current transformer and a voltage transformer of a power distribution network in a power system to obtain a current-voltage three-phase data sequence; state analysis is carried out, and a fault early warning instruction is triggered; performing feature backtracking on the sensing module to generate a transformer feature backtracking result; performing trend feature identification on the current-voltage three-phase data sequence to generate current-voltage three-phase data trend features; and performing fault early warning analysis to obtain a fault early warning result. According to the invention, the technical problem of low fault early warning accuracy of the transformer and the power distribution equipment in the prior art can be solved, and the technical effect of improving the early warning accuracy is achieved.

The invention provides an electronic current transformer operation data calculation system, and relates to the technical field of data processing, and the system comprises a data processing module which is used for carrying out the sliding time window scanning of an equipment dependence adjacency matrix, calculating the local reachable density under a dynamic neighbor topological distance through a local outlier factor algorithm, if it is detected that the harmonic total distortion rate gradient enters a statistical hypothesis test rejection domain or the winding temperature rise rate exceeds a material thermal aging critical threshold, extracting a multi-dimensional abnormal feature vector set; the risk quantitative index generation module is used for generating a risk quantitative index group from the multi-dimensional abnormal feature vector set through a pre-trained fault propagation probability model; and the processing instruction set generation module is used for establishing a multi-objective optimization function based on the risk quantification index group, performing non-dominated sorting evolution on a processing instruction chromosome by adopting an NSGA-II genetic algorithm, screening a dynamic optimization instruction sequence matched with a real-time load fluctuation coefficient through a Pareto frontier solution set, and generating a structured processing instruction set. The operation reliability of the power system is improved.

The utility model relates to the field of resonance eliminators, and discloses a protection element and a current limiting type resonance eliminator, the protection element comprises at least two groups of protection units, the two adjacent groups of protection units are connected in series, and each protection unit comprises a protection module; the current-limiting resonance eliminator based on the current-sensitive resistor made of the current-sensitive material is connected in series between the PT neutral point and the ground. Under the normal operation condition, the current-limiting resonance eliminator is in a low-resistance state, and system parameters and PT performance are not affected; when excitation energy is generated due to a system fault, the current-limiting resonance eliminator suddenly changes into a high resistance state, quickly absorbs resonance energy, destroys resonance parameters, suppresses PT excitation current below 200mA, and ensures that a voltage transformer is unsaturated and a PT fuse is not fused; and a built-in current sensor is connected, so that the running state of the current-limiting resonance eliminator can be monitored in real time.