8384 results about "Instrument transformer" patented technology

The invention discloses an electric energy metering box fault prediction method and system based on big data analysis, relates to the technical field of smart power grids, and solves the problems of progressive aging missing detection and instantaneous interference misjudgment caused by dependence on single parameter threshold alarm and fault positioning misalignment caused by multi-source data isolated analysis in the prior art. According to the scheme, electrical, environment and equipment state parameters are collected in real time through a multi-dimensional sensing network; the error drift of the mutual inductor is dynamically predicted based on an LSTM-Kalman filtering model, and core breakdown early warning is realized in combination with wavelet transform; outputting a corrected resistance value and a fault mark by using a BP neural network; predicting the life of the piezoresistor by adopting a gradient boosting decision tree and fusing lightning overvoltage characteristics; the transient interference is suppressed through the combination of a Transform self-attention mechanism and dynamic time warping; according to the method, the aging detection precision and the complex environment adaptability are remarkably improved, the misjudgment rate is reduced, and the multi-fault associated positioning and active defense capability is realized.

The invention discloses an intelligent control system for a current transformer, and particularly relates to the technical field of power system monitoring, which comprises a fluctuation identification unit, a redundancy acquisition unit, an error fitting unit, a protection delay unit and a fault response unit, realizes real-time identification and classification of current fluctuation, and has standby path high-speed sampling and fusion signal construction capabilities. The fluctuation trend is judged through error regression, a protection strategy is dynamically set, response is delayed to avoid misoperation, finally, a high-level protection instruction is triggered and a fault event is output when offset overruns or alignment fails, and the data accuracy and the system response stability in the power supply switching process are guaranteed; according to the method, accurate identification of current fluctuation is realized through multi-dimensional feature extraction, data reliability is enhanced by using redundant sampling and error fitting, and by combining delay control and a hierarchical response mechanism, the risk of misoperation is effectively reduced, the fault judgment accuracy and the system protection stability are improved, and the method is suitable for a complex power supply switching scene.

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 current transformer fault early warning method, and relates to the field of fault prediction. The fault early warning method comprises the steps of collecting current transformer operation state information, preprocessing collected operation state information data, constructing a current transformer fault early warning model, and training and testing the current transformer fault early warning model. The current transformer fault early warning model is composed of a long-term trend analysis module, a conditional enhancement modeling module, a bidirectional LSTM module fusing an attention mechanism and a convolutional layer, and a self-adjusting fusion module. The long-term trend analysis module is used for modeling a long-term trend in the time sequence; the conditional enhancement modeling module is used for modeling seasonal components in the time sequence; a bidirectional LSTM module fusing an attention mechanism and a convolutional layer captures short-term and long-term dependency relationships in a time sequence; and the self-adjusting fusion module automatically adjusts the contribution degree of each model output to a final prediction result. The method can accurately predict the future fault condition of the current transformer.

A power distribution utility panel is provided with a first panel area configured to be accessed only by personnel of a utility, the first panel area including a current transformer, a second panel area including at least one remote controllable device for connecting and disconnecting power to / from one or more loads, and a third panel area including at least one power converter assembly, a controller and a power meter configured to monitor power from a power source, the at least one power converter assembly being configured to route power from the power source to an electric vehicle charger and / or an energy storage system.

The invention provides a high-voltage cable partial discharge identification and positioning method, and relates to the technical field of high-voltage cable diagnosis, and the method comprises the steps: collecting partial discharge pulse signals through high-frequency current transformers disposed at two ends of a high-voltage cable; carrying out noise reduction processing on the acquired partial discharge pulse signal by using an adaptive multi-scale wavelet decomposition and reconstruction method to obtain a partial discharge characteristic signal after noise reduction; inputting the partial discharge characteristic signal into a pre-trained lightweight residual attention network for identification and classification, and outputting a discharge type discrimination result, discharge intensity and characteristic parameters; and based on the discharge type discrimination result, the discharge intensity and the characteristic parameters, a self-correction double-end positioning algorithm is adopted to position the discharge source, and the position of the discharge source is calculated. According to the invention, the technical problems of unsatisfactory signal noise reduction effect, low discharge type identification accuracy, unstable positioning precision and the like in the prior art can be solved, so that high-precision identification and positioning of partial discharge of the high-voltage cable are realized.

The invention discloses an intelligent diagnosis system of a power distribution network fault self-judgment switch device, and relates to the technical field of power system automation and intelligent power grids, and the intelligent diagnosis system comprises an intelligent diagnosis system interconnection hub which is in communication connection with a power parameter monitoring module, an intelligent fault detection module and a visual decision support module; the electric power parameter monitoring module monitors the state of a power distribution network in real time through a mutual inductor, voltage, current, power factors and harmonic data are collected through an intelligent electric meter, the intelligent fault detection module achieves fault recognition, trend prediction and anomaly detection through an LSTM neural network, and the decision support module provides a graphical interface and automatically generates a fault response strategy. According to the method, autonomous judgment and quick response of the power distribution network fault are achieved, the accuracy and efficiency of fault detection are remarkably improved, the false alarm rate and the missing report rate are reduced, meanwhile, the decision support module of the graphical interface simplifies the fault processing flow, and the stability and safety of power grid operation are improved.

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 relates to the technical field of monitoring or controlling a charging station, in particular to a charging pile safety monitoring method and system, and the method comprises the following steps: step 1, monitoring: step 1.1, electric leakage monitoring: installing a high-sensitivity electric leakage sensor in a charging pile and a charging gun line, continuously monitoring the electric leakage current in real time, and monitoring the electric leakage current in real time; the monitoring frequency is that data are collected once every 10 milliseconds; step 1.2, overload and short circuit monitoring: real-time current change of a charging circuit is monitored by using a current transformer, and the acquisition frequency is once every 5 milliseconds; step 1.3, monitoring the temperature; according to the scheme, through monitoring of electric leakage, overload and short circuit, temperature, smog and flame, charging gun safety, vision and the like in combination with intelligent analysis, the operation state and the surrounding environment condition of the charging pile can be comprehensively, timely and accurately mastered, electrical faults, temperature anomalies and potential safety hazards can be rapidly detected and judged, and the safety and reliability of the charging pile are improved. And all-around real-time monitoring of the potential safety hazard of the charging pile is realized.

The invention provides an oil-paper insulation space charge measurement numerical simulation method considering a composite electric field working condition, and relates to the technical field of oil-paper insulation space charge measurement simulation, and the method comprises the steps: obtaining the actual operation environment parameters of a high-voltage transformer, and carrying out the multi-physical field coupling calculation of a fluid field, an electrostatic field and a temperature field of the high-voltage transformer; establishing a bipolar carrier transmission model, collecting structure parameters and attributes of oil paper insulation, and setting material parameters; setting boundary conditions of each physical field, and establishing a corresponding charge transport reaction equation; initializing an oil paper insulation system to configure related parameters of a solver, and calculating a charge transport reaction equation through the solver to obtain a simulation result; perfecting the simulation result to obtain a space charge measurement numerical simulation result of oil paper insulation; according to the invention, the limitation of field test conditions is overcome, the technical problem of low detection resolution of measurement equipment is solved, and the real-time performance of accurate observation of charge dynamic response is ensured.

The invention discloses a control circuit of an electronic load, the electronic load and a power supply test system. The circuit comprises an MCU; the signal output end of the MCU is connected with the input end of the DAC module; the closed-loop control circuit comprises a first error amplifier, a mutual inductor, an MOS (Metal Oxide Semiconductor) tube, a current sampling resistor and a power supply end VBUS; a mutual inductor is arranged between a first error amplifier and an MOS tube of the closed-loop control circuit, a power supply end VBUS is connected with a drain electrode of the MOS tube through a primary side of the mutual inductor, a first secondary side of the mutual inductor feeds back an input signal of the first error amplifier, and a second secondary side of the mutual inductor feeds back a driving signal of the first error amplifier to the MOS tube. According to the invention, the dynamic response speed when the electronic load pulls the high-frequency current can be improved, and the test requirements of high precision and high dynamic response are met.

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 relates to the technical field of intelligent early warning, and discloses an aviation case electrical safety intelligent early warning method, device and equipment and a storage medium. The method comprises the following steps: carrying out voltage, current, temperature and vibration parameter acquisition on a wiring row position, an input wiring terminal position and a zero sequence current transformer installation position of the aviation intelligent distribution box to obtain an electrical parameter data set; executing dynamic adjustment of an electrical safety detection threshold to obtain an aviation environment adaptability threshold parameter; performing feature extraction on the electrical parameter data set to obtain electrical parameter abnormal features; performing electrical fault mode matching and positioning analysis on the electrical parameter abnormal characteristics to obtain fault type, position and severity information; and generating a target early warning response strategy of the aviation intelligent distribution box in combination with the flight stage characteristics of the aircraft. According to the invention, a complete electrical safety protection system is constructed, the false alarm rate and the missing report rate are significantly reduced, and the safety protection capability of the aviation intelligent distribution box electrical system is improved.

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

The invention provides a resonance elimination device and method for suppressing ferromagnetic resonance in a power system, and relates to the technical field of power system safety prevention and control. The resonance elimination device for suppressing the ferromagnetic resonance in the power system comprises a resonance elimination module used for consuming energy generated by the ferromagnetic resonance; an acquisition module; the detection module is used for detecting excitation inrush current between the neutral point of the voltage transformer and the high-voltage damping resistor in real time; the calculation module is used for calculating the rising edge slope of the magnetizing inrush current and calculating the offset voltage of the neutral point to the ground; the judgment module is used for continuously judging the relationship between the rising edge slope of the excitation inrush current detected in real time and each threshold value and the relationship between the numerical value of the neutral point to ground offset voltage detected in real time and each threshold value, and judging whether the system has a single-phase ground fault or not; and the control module controls the input of the harmonic elimination module. The resonance elimination device can accurately and quickly eliminate ferromagnetic resonance and effectively improve the resonance elimination efficiency of the ferromagnetic resonance.

The invention provides a field data verification device based on a money-free clamp buckle type single-phase electric energy meter, and the device comprises a host which is used for starting a measurement process through the contact of a probe with a signal contact of the electric energy meter, receiving current data transmitted by a wireless clamp-shaped current transformer, and carrying out the filtering, calibration and error analysis of the measurement data; and the wireless split core type current transformer is used for being clamped on a current loop of the measured electric energy meter, starting to measure current data and sending the current data to the host in a wireless mode. According to the invention, a wireless communication technology, a field data processing algorithm and a verification function are integrated, and field real-time data acquisition, processing, analysis and verification can be realized, so that the efficiency and accuracy of verification work are 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 relates to the technical field of electrical variable testing, in particular to a high-precision performance testing processing method and system for a low-impedance voltage transformer. The method comprises the following steps: constructing a controllable test excitation signal, and synchronously collecting a corresponding primary side voltage and a secondary side voltage of a mutual inductor; space electromagnetism elimination is carried out according to the primary side voltage and the secondary side voltage of the mutual inductor, and frequency domain characteristic decomposition and signal instantaneous offset calculation are carried out at the same time, so that a mutual inductor signal characteristic matrix is constructed; acquiring environment parameters corresponding to the low-impedance voltage transformer; constructing a neural network model based on Bayesian optimization, and predicting and outputting a performance parameter set corresponding to frequency response and load characteristics; and comparing the performance parameter set with a preset standard threshold value, feeding back, generating a calibration compensation coefficient, testing and evaluating, and generating a high-precision performance test report corresponding to the low-impedance voltage transformer. According to the invention, high-precision performance testing of the low-impedance voltage transformer can be realized.

The invention relates to the technical field of electric energy metering, in particular to an insulation performance evaluation system and method for an insulation voltage transformer, and the system comprises an insulation monitoring and sensing optimization module, a central storage unit, a data processing and abnormity analysis module, and an equipment performance evaluation module. The insulation monitoring and sensing optimization module builds an intelligent sensor network and a data acquisition and processing terminal, and realizes real-time monitoring of the insulation voltage transformer; the data processing and anomaly analysis module extracts key features and analyzes the key features in real time by using a local anomaly factor algorithm, so that the abnormal change of the insulation performance can be found in time; and the equipment performance evaluation module calculates a comprehensive gain value index to carry out detailed performance evaluation on equipment with problems, so that operation and maintenance personnel can know the state of the equipment and formulate a reasonable maintenance, replacement or optimization strategy. The method is used for solving the technical problems of incomplete monitoring and insufficient evaluation of the insulation performance of the insulation voltage transformer.

The invention provides a mutual inductor fault diagnosis method based on multi-sensor data fusion and transfer learning, and the method comprises the following steps: S1, installing a plurality of high-precision sensors on the secondary side of a voltage transformer to be subjected to fault diagnosis based on the voltage transformer to be subjected to fault diagnosis; s2, on the basis of the step S1, performing data acquisition and processing on data acquired by various high-precision sensors through a DHDAS dynamic signal acquisition instrument; and S3, based on the step S2, carrying out fault diagnosis on the voltage transformer through a PC (Personal Computer) carrying acquisition analysis software on the DHDAS dynamic signal acquisition instrument. According to the method, multi-mode signals such as voltage, current and temperature are synchronously collected, time-frequency domain features are extracted through continuous wavelet transform, the dynamic characteristics of interlayer short circuit faults can be more comprehensively represented, meanwhile, by combining transfer learning and a deep neural network, the intelligent diagnosis model can remarkably improve the classification performance under the condition that sample data is small, and the classification efficiency is improved. And the limitation of a single-mode signal diagnosis method is effectively overcome.

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 an error prediction method and system for an electronic voltage transformer, and belongs to the technical field of electric appliance measurement, and the method comprises the following steps: collecting historical operation data of the electronic voltage transformer, including temperature, humidity, load voltage, secondary voltage and a historical ratio error value; a time sequence convolutional neural network TCN is selected as a basis, an error prediction model is constructed in combination with a linear attention mechanism, and offline learning is performed by using historical data. Operating data is collected in real time, the relative entropy of the operating data and historical data is calculated, and a distribution threshold value is set; and when the relative entropy exceeds a threshold value, updating model parameters online by using real-time data. According to the method, the data distribution change is detected through the relative entropy, and the prediction precision of the model in a dynamic environment is ensured. The relative entropy serves as an index for measuring probability distribution differences, data distribution mutation can be effectively recognized, online learning can be triggered, the model can be dynamically adjusted, and errors of the electronic voltage transformer can be predicted more accurately.

The invention discloses a method and a system for measuring an error caused by wavelength drift of an optical fiber current transformer. The method comprises the following steps: constructing a first mathematical model of a half-wave voltage size and a wavelength size, and a second mathematical model of a Verdet constant and the wavelength size; according to the first mathematical model and the second mathematical model, constructing a third mathematical model of the Verdet constant and the half-wave voltage; and constructing a fourth mathematical model of the output optical signal and the half-wave voltage, and determining the total influence of the wavelength drift on the output optical signal according to the fourth mathematical model. The error of wavelength drift can be effectively compensated, and the measurement performance of the optical fiber current transformer is improved.

The invention discloses a power distribution network scene low-voltage electric quantity internet-of-things monitoring device and method, and the device comprises a sensing layer, a network layer and an application layer, the sensing layer comprises a plurality of electric quantity collection terminal nodes, and each electric quantity collection terminal node comprises a current transformer, a voltage transformer, a metering chip, a first Bluetooth Mesh communication module and a first power module. And the metering chip converts analog signals acquired by the current transformer and the voltage transformer into digital signals and calculates to obtain voltage, current, power, electric quantity, frequency and other electric quantity parameters. According to the invention, automatic acquisition, wireless transmission, remote monitoring, intelligent analysis and visual display of the electric quantity data of the low-voltage side of the power distribution network can be realized; and meanwhile, an early warning effect can be achieved, early warning can be given out for possible faults of the line, the manual field patrol intensity is reduced, and an Internet of Things solution which is low in cost, high in efficiency, easy to deploy and wide in coverage is provided for low-voltage electric quantity monitoring of the power distribution network.

The invention provides an electric energy metering detection data quality evaluation method and system, and relates to the field of data processing. Data abnormity generated by a current transformer aiming at gradual change characteristics caused by contact oxidation is firstly eliminated through improved wavelet transform and feature extraction; the abnormal rate of the processed data is calculated according to a support vector machine model, the conditions of noise interference and abnormal fluctuation in actual current data are considered when a support vector machine is designed, and the contact resistance is slowly increased due to contact oxidation of the secondary winding of the current transformer; therefore, the problems that the gradual change abnormity is difficult to find in time and the electric charge metering deviation is easily caused by the existing fixed threshold value evaluation method are solved.

The invention relates to the technical field of circuit breakers, and discloses a magnetic control type pole-mounted circuit breaker, which comprises an arc extinguish chamber, a mechanism box, a current transformer and an isolating switch, and is characterized in that the arc extinguish chamber comprises a ceramic airtight shell fixedly mounted on the upper side of the mechanism box, and a fixed contact is fixedly mounted in the ceramic airtight shell; a moving contact is slidably installed in the ceramic airtight shell, a corrugated pipe is fixedly installed in the ceramic airtight shell, the moving contact is fixedly connected with the corrugated pipe, and a sliding rod is slidably installed in the mechanism box. The magnetic control driving mechanism is arranged in the mechanism box to drive the sliding rod to horizontally move left and right, the moving contact is driven to move up and down through the transmission effect of the transmission plate, the moving contact and the fixed contact are kept in a contact or separation state, opening and closing actions of the arc extinguish chamber are achieved, the design structure is simple, a buckle structure for restraining the position of the moving contact is simplified, and the working efficiency is improved. The device has the advantages of low failure rate and sensitive opening and closing actions.

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 relates to the technical field of current measurement, and discloses an open-close type current transformer which comprises a lower shell, one side of the top of the lower shell is rotatably connected with an upper shell, semicircular iron cores are embedded in the lower shell and the upper shell, a copper wire is wound on the iron core located in the lower shell, two ends of the copper wire are fixedly connected with butt joints, and the butt joints are fixedly connected with the upper shell. The butt joint is embedded in the outer wall of one side of the lower shell, the side, close to the butt joint, of the lower shell is rotationally connected with a mounting plate, butt joint rods are fixedly connected to the sides, close to the butt joint, of the two ends of the mounting plate, two limiting holes are formed in the mounting plate, and two limiting seats are fixedly connected to the side, close to the mounting plate, of the lower shell. Each limiting seat is aligned with the corresponding limiting hole in the same side, mounting grooves are formed in the tops and the bottoms of the limiting seats, limiting blocks are slidably connected into the mounting grooves, and the problem that due to the fact that the positive electrode and the negative electrode are reversely connected, wiring copper wires need to be detached, and then winding work needs to be conducted by replacing the positions, and operation is troublesome can be solved.