1168 results about "Current wave" patented technology

The invention discloses an integrated energy system operation management method based on load prediction, and belongs to the technical field of energy system management, and the method specifically comprises the steps: collecting operation parameters of energy use equipment, the parameters comprising current waveform characteristics, surface temperature distribution and medium flow change; analyzing a time sequence change rule of the operation parameters, and extracting characteristic indexes related to equipment aging; establishing an energy consumption prediction correction model according to the characteristic indexes, and dynamically adjusting a theoretical energy consumption calculation value of the energy use equipment; inputting the corrected theoretical energy consumption calculation value into an energy distribution optimization model to generate a load distribution instruction of the energy network; after executing the load distribution instruction, comparing the deviation between the actual energy consumption and the correction theoretical value, and updating the parameter weight of the energy consumption prediction correction model; according to the invention, continuous and stable operation and optimal management of the integrated energy system in the equipment aging process are realized.

The invention discloses an intelligent monitoring and early warning system for the safety state of an electrical cabinet, and belongs to the technical field of electrical variable measurement, and the system comprises a data collection module which is used for obtaining multi-source sensing data of the electrical cabinet, and the multi-source sensing data comprises a current waveform parameter, an infrared temperature distribution parameter and a mechanical vibration spectrum parameter; the health feature evaluation module is used for generating a health state feature vector of the electrical cabinet by using the multi-source sensing data; the instruction generation module is used for outputting an early warning decision instruction according to a matching result of the health state feature vector and a preset fault propagation rule base; and the safety protection module is used for executing a safety protection action when the early warning decision instruction meets a preset execution condition. A multi-source sensing data fusion analysis technology is adopted to construct an electrothermal mechanical composite feature vector, a fault propagation rule base is coupled to realize cross-domain conduction path modeling, composite hidden dangers such as contact deterioration and the like can be accurately identified in a fault incubation period, and graded active safety protection measures are triggered.

The invention relates to the technical field of industrial automatic detection, in particular to an intelligent electromagnetic valve fault detection method and system based on multi-parameter analysis, and the method comprises the following steps: S1, synchronously collecting the dynamic current waveform, vibration spectrum information and environment temperature data; s2, extracting a current characteristic value and vibration energy distribution, and calculating a temperature drift amount; s3, the current characteristic value, the vibration energy distribution and the temperature drift amount are input into a multi-parameter incidence matrix, and a coupling deviation coefficient representing the coupling relation between parameters is generated; s4, calculating a comprehensive health index of the electromagnetic valve based on the coupling deviation coefficient; and S5, matching the comprehensive health index with a preset fault feature library, and outputting a corresponding fault type and a positioning result. According to the method, by fusing the multi-source characteristic parameters and introducing the health index evaluation mechanism, accurate recognition and positioning of the electromagnetic valve faults are achieved, and the detection accuracy and the response efficiency are improved.

The invention relates to the technical field of intelligent power grids, and provides an intelligent operation centralized control center intelligent scheduling interaction method and system, and the method comprises the steps: generating a heat distribution gradient through environment noise filtering, reflecting the temperature field change of equipment, obtaining a voltage amplitude envelope through fundamental wave and harmonic wave separation, and monitoring the power quality; a current fluctuation coefficient is extracted by combining segmented deviation analysis to evaluate a line load state, and frequency fluctuation parameters are captured by using time domain statistics to track system stability. By constructing a dynamic association map, heterogeneous data such as thermodynamics, electrical quantity, load characteristics and synchronous states are mapped to power grid topological nodes, and a cross-dimension association relationship is established to realize whole-network state coupling analysis. An overload risk, a voltage out-of-limit probability and a system instability threshold are quantified through a hierarchical evaluation mechanism, a multi-target optimization constraint condition is formed, and finally a scheduling strategy considering equipment safety, economy and power supply reliability is generated. When the power system operates, intelligent scheduling is carried out according to the operation state of the power grid.

The invention relates to the technical field of electrical equipment monitoring, in particular to a power distribution equipment state intelligent diagnosis system and method, and the system comprises a current fluctuation detection module, a voltage stability evaluation module, a heat effect diffusion analysis module, a fault point positioning module and an equipment state evaluation module. According to the invention, through extracting current change characteristics of key nodes and judging continuity of fluctuation differences, rapid identification of current anomalies can be realized, a voltage distortion region and a distribution range thereof can be positioned in combination with phase deviation and symmetry change of voltage waveforms, and the current anomalies can be identified based on a temperature gradient path and jump point screening. A hot spot diffusion trend and a thermal disturbance boundary can be described, morphological analysis and coordinate labeling are performed on the basis of multiple fault areas, multi-point concurrent positioning is realized, association between thermal disturbance and connection defects is identified in combination with temperature difference and current path change characteristics, fault diffusion trends and state disturbance blocks can be accurately presented, and the accuracy of fault diagnosis is improved. And the power distribution state identification and intervention efficiency is improved.

The invention relates to the technical field of circuit breakers, in particular to a circuit breaker fault diagnosis method and system for switching an alternating current filter in an extra-high voltage converter station, and the method comprises the following steps: S1, synchronously collecting multiple parameters: synchronously collecting vibration acceleration signals, opening and closing coil current waveforms, arc light intensity and environment temperature and humidity parameters; s2, time sequence feature extraction: performing time-frequency domain decomposition on the vibration acceleration signal to obtain a mechanical action time sequence spectrum; s3, operation mode classification: determining the operation mode of the circuit breaker; s4, three-dimensional fault matrix construction: generating a three-dimensional fault matrix including spatial distribution characteristics; s5, dynamic threshold analysis: generating a diagnosis threshold interval dynamically adjusted along with the environmental parameters; and S6, comprehensive diagnosis output: outputting a mechanical jam grade, a contact ablation degree and an insulation deterioration early warning signal. According to the invention, the mechanical, electromagnetic and insulation characteristics of the circuit breaker can be reflected more comprehensively, and reliable guarantee is provided for safe and stable operation of a high-voltage power grid.

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

The invention 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 earth leakage protection monitoring, and discloses an earth leakage circuit breaker remote monitoring system integrated with the Internet of Things. An electric leakage characteristic modeling module of the system obtains real-time monitoring data, extracts current waveform characteristic parameters, identifies an abnormal waveform mode and a first occurrence time sequence, and generates an original electric leakage characteristic template; the network path generation module performs topological sorting on the monitoring nodes based on the template, establishes an equipment connection path and constructs an Internet of Things topological path; a path anomaly analysis module extracts a node sequence and screens abnormal transmission paths to obtain an abnormal path set; the risk level judgment module collects terminal node risk tags and obtains a risk level tag group through matching; and the topological structure output module counts associated nodes, divides abnormal paths, establishes a mapping relation and generates a remote monitoring topological table. The system improves the accuracy and efficiency of electric leakage monitoring, and is suitable for a complex power network environment.

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

The invention discloses a switch loop data extraction method, device and equipment based on phase locking, and the method comprises the steps: carrying out the interval change analysis of operation data in a ring main unit, and recognizing a communication abnormal node through a phase locking technology; associating a mechanical vibration source based on the communication abnormal nodes, detecting a vibration conduction path, extracting current fluctuation characteristics, and determining position deviation; the operation current intensity is adjusted in combination with fluctuation characteristic parameters, and accurate off-position control is achieved through reverse braking force; constructing a dynamic threshold reference based on frequency domain analysis, and generating a complete operation record according to the dynamic threshold reference and the accurate parking data; performing typed grouping and transmission optimization on the data, and controlling data switching by adopting a gradually migrated beat sequence; and finally, through signal reconstruction and data fusion technologies, a switch loop data set with continuous time sequence and complete space is generated. The method can effectively cope with communication interference, mechanical vibration and other complex environmental factors, and improves the integrity and accuracy of data acquisition.

The invention discloses a pulsed eddy current detection method and system for a thermal power pipeline with a coating layer, and relates to the technical field of pulsed eddy current nondestructive detection.The pulsed eddy current detection method comprises the steps that pulsed eddy current detection simulation and experiment are conducted under the condition of a three-dimensional simulation model and a test piece, and excitation current waveform, amplitude and frequency parameters are determined; an induced voltage signal is collected, peak values, time points and attenuation characteristics are extracted, the corresponding relation between the wall thickness, the coating layer thickness and the welding seam structure and detection signals is constructed, a parameterized database is constructed, and temperature correction is completed; and optimizing a sensor structure and a signal acquisition scheme according to a parameterized database, obtaining detection data in a pipeline operation state, completing two-dimensional imaging of wall thickness distribution and welding seam positioning, and forming detection information covering a straight pipe, an elbow and a welding seam area. According to the method, wall thickness detection and welding seam positioning of the thermal power pipeline under the conditions of a thick wall and a thick coating layer are achieved through the full-process design of test piece modeling, simulation experiment and imaging collection.

The invention belongs to the technical field of electrical safety, and particularly relates to a human body electric shock protection method and system based on multi-parameter fusion, multi-dimensional characteristic parameters are formed by extracting a high-frequency harmonic component, a voltage abrupt change slope and a magnetic field intensity fluctuation value of a residual current waveform, and the weight is dynamically adjusted according to the instantaneous change rate of each characteristic, so that the human body electric shock protection is realized. Generating a weighted feature vector; and a comprehensive criterion value is calculated in combination with a preset rule base and is compared with a dynamic threshold value, so that whether the circuit breaker is triggered to act or not is determined. According to the method, through fusion analysis of a plurality of physical characteristics, the identification capability of the system in a complex electromagnetic environment is improved, the probability of misoperation caused by external interference is effectively reduced, the action accuracy and stability of the circuit breaker are improved, and the power utilization safety and the power supply continuity are guaranteed.

The invention relates to the technical field of power supply system management, and discloses a centralized management method and management system for a power supply system. The method comprises the following steps: monitoring a current fluctuation sequence and voltage offset data of each node of a power supply network in a continuous operation period, and collecting an equipment state log text and load change time sequence information; identifying a time point of abnormal sudden change of current fluctuation, and extracting a characteristic parameter set of a power supply quality reduction event in combination with a voltage offset data change amplitude; matching a historical abnormal event library, positioning key operation record fragments strongly related to load change in the log, and generating a mapping relation table of equipment operation behaviors and power supply quality fluctuation through semantic analysis and time sequence alignment; and correcting the parameters of the load prediction model, outputting and executing a power supply priority dynamic adjustment strategy, and triggering automatic calibration of equipment operation parameters. According to the method, comprehensive control of the power supply system is realized, abnormity can be identified and processed in time, association between operation and quality is clear, and stability and flexibility of operation of the power supply system are improved.

The invention relates to the technical field of data processing, in particular to a motor performance monitoring data processing system which comprises a signal registration module, a rhythm judgment module, a trend lag module, an effect recognition module and a label scheduling module. According to the method, the waveband gravity center is established by identifying extreme points, trend comparison is performed, a gravity center alignment structure between different channels is constructed, the time period rhythm stability is judged based on the sampling interval change trend, abnormal paragraphs are marked, and the response lag time period is positioned in combination with the rotation speed slope change and the current fluctuation behavior. And detecting the sequence and direction relationship of a plurality of parameter fluctuation frames, identifying the dense segments which alternately act to construct a label labeling index, and adjusting the state output sequence according to the occurrence frequency of different labels in a continuous time period, thereby realizing the identification and dynamic sorting scheduling of the response structure relationship among different time sequence behaviors. And the time sequence consistency identification capability and the parameter linkage structure expression capability of the monitoring data in the continuous abnormal state are improved.

The invention discloses a distributed photovoltaic access power distribution network relay protection analysis method and system, and belongs to the technical field of photovoltaic grid connection, and the method specifically comprises the steps: injecting a dynamic resonance detection signal at the AC side of a current converter of a photovoltaic grid-connected system, and enabling the frequency to be matched with the natural resonance frequency of a target section; analyzing the energy focusing effect of the dynamic resonance detection signal in the power distribution network, and generating a resonance energy distribution map; when the energy density of a certain section in the resonance energy distribution map exceeds a preset threshold value, the photovoltaic output current waveform is adjusted to be a discontinuous waveform containing periodic intermittent cutoff; based on the reflection delay difference of the waveform in the fault section, constructing a space-time mapping model of a fault point, and analyzing and determining a fault position; according to an output result of the space-time mapping model, controlling a photovoltaic side circuit breaker and a power grid side relay to execute a selective tripping action based on waveform phase synchronization; according to the invention, the sensitivity and reliability of distributed photovoltaic access power distribution network relay protection are improved.

The invention discloses a high aspect ratio micropore pulse abrupt change current copper filling method and system, and belongs to the technical field of printed circuit board manufacturing, and the method comprises the steps: obtaining micropore structure parameters, and generating a gradient pulse abrupt change current waveform; monitoring a deposition thickness parameter of the orifice of the micropore in real time, and when the deposition thickness parameter exceeds a preset thickness threshold value, activating the reverse peak clipping pulse group; generating a resonant composite sound field in the electroplating bath; detecting the concentration distribution of the additive in the micropores in real time, and generating a dynamic adjusting instruction according to the concentration distribution of the additive; the independent injection rate of the accelerator and the inhibitor is controlled according to the dynamic adjusting instruction; and based on the gradient pulse abrupt change current waveform, the resonant type composite sound field and the dynamic adjusting instruction, the copper filling process is executed till the target deposition parameters are achieved. According to the method, a multi-field coupling mechanism of gradient pulse dynamic peak clipping, composite sound field synergistic mass transfer and additive concentration real-time regulation and control is adopted, and defect-free high-reliability copper filling can be achieved.

The invention discloses a digital calibration system and method for dynamic response parameters of a surge protection circuit, relates to the technical field of power electronic protection and test calibration, and is used for solving the problem that an existing surge protection circuit calibration method cannot reflect device degradation and dynamic response mismatch. Surge event voltage and current waveforms are collected through a synchronous trigger mechanism, non-stationary signal features are extracted through combined time-frequency analysis, and a voltage-current phase trajectory diagram is constructed to generate a response feature matrix; performing phase-space reconstruction on the matrix, calculating Kolmogorov entropy quantification system stability, and establishing a material degradation transfer function in combination with an energy absorption sequence to generate a grain boundary degradation index; key parameters are screened through L1 regularization regression, and a quantitative relation between a grain boundary degradation index and a protection threshold value is established to realize adaptive threshold value calculation; and executing strategy switching from calibration to predictive maintenance according to the degradation trend and threshold fluctuation change, and outputting a maintenance signal to complete dynamic accurate calibration and reliable operation of the surge protection circuit.

The invention belongs to the technical field of circuit monitoring, and particularly relates to an AI fault identification method and system for an electric power circuit, and the method comprises the steps: constructing a cross-modal data flow with a space-time mark through the synchronous collection of a thermal imaging sequence and a three-phase current waveform, extracting the characteristics of a multi-physical field through combining the characteristics of a wire material, and carrying out the recognition of an AI fault. And establishing a thermal-electric coupling relationship by using space-time alignment convolution, further analyzing and calculating correlation strength between temperature anomaly and current fluctuation through a sliding window, constructing a dynamic threshold model, generating a fault probability thermodynamic diagram, and finally outputting a graded early warning signal. Compared with the prior art, the method has the advantages that deep fusion analysis of thermal imaging and electrical signals is realized, the recognition precision and response speed of potential fault points are improved, the abnormal state of the wire joint can be found and accurately positioned earlier, the misjudgment rate is effectively reduced, and the safety and stability of power grid operation are improved.

The invention relates to the technical field of electric power intelligent judgment, in particular to an AI-based intelligent electric energy meter fault diagnosis system, which comprises an operation data acquisition module, a jump correlation judgment module, an operation deviation judgment module, a current waveform diagnosis module and an abnormity alarm module. According to the invention, through synchronous acquisition of the current data and the operation data of the refrigeration storage, whether the current jump is related to the gating action is judged, and the refrigeration performance abnormity of the refrigeration storage and the fault type of the intelligent electric meter are effectively identified by further combining multiple cross validation of baseline energy consumption and temperature change; an ideal current waveform is constructed through an AI algorithm and is compared with an actually measured waveform, so that intelligent judgment and classification of fault types are realized; meanwhile, the diagnosis result is linked with the operation and maintenance system, the response efficiency is improved, and the method is particularly suitable for scenes with high requirements on the stability of the electric meter, such as cold chain storage, and has good practical value and popularization prospect.

The invention relates to the field of pump set control, in particular to a multi-modal pump set dynamic optimization control method and system, and the method comprises the steps: collecting the current waveform, pressure pulsation spectrum and flow time sequence data of each unit of a pump set through a distributed sensor array, and carrying out the time-frequency domain fusion processing to generate an operation state tensor; and inputting a multi-modal identification neural network, and outputting a dominant modal identifier and a modal confidence vector. And according to the modal confidence, activating a basic optimization strategy library or executing cross-modal strategy collaboration, and generating an optimization instruction. And dynamically selecting an instruction conversion path to obtain a frequency converter parameter set, loading the frequency converter parameter set to a programmable logic controller, and driving an execution mechanism to converge a moving track. The method can effectively cope with changes of multi-mode operation states and complex working conditions, and dynamic optimization of the pump set is achieved.

The invention discloses a self-sensing monitoring method, system and equipment based on a lightning arrester, and relates to the technical field of power equipment monitoring. The self-sensing monitoring method, system and equipment based on the lightning arrester comprises the following steps: S1, collecting lightning stroke data in real time through multi-sensing fusion, and performing data cleaning and standardization processing on the lightning stroke data; s2, adopting a three-mode sensing and three-source power supply cooperation mechanism to realize state-driven adaptive sensing and energy path switching; s3, automatically scheduling a communication path according to a communication type and link quality, dynamically analyzing and compensating transmitting power, and completing authentication encryption and multi-hop secure transmission; s4, lightning stroke characteristics are extracted, an equipment life prediction model is constructed, residual life prediction is realized, and equipment health grade division and operation strategy adjustment are carried out according to the residual life prediction model; and S5, calculating an electric leakage deviation value by reconstructing a current waveform, triggering graded early warning and linking a communication power and energy supply strategy. The problem that the operation of a power system is affected due to large leakage current monitoring errors is solved.

The invention discloses a cable partial discharge detection method and system, and the method comprises the steps: installing sampling sensor groups on a detected cable at a preset interval, and each group at least comprises a current sensor and an ultrasonic sensor; synchronously sampling and preprocessing the high-frequency current signal and the ultrasonic signal; extracting current waveform characteristics and a first time stamp of arrival of the first pulse, and extracting sound wave pulses in the ultrasonic signals and a second time stamp of arrival of the sound wave pulses; and calculating a time difference, if the time difference is smaller than a preset threshold value and the waveform amplitude similarity is within a preset range, determining that no failure partial discharge exists, otherwise, positioning a failure position. According to the method, the acoustoelectric signals are acquired cooperatively through multiple sensors, interference is eliminated in combination with time difference and waveform similarity criteria, the detection reliability and the positioning precision are effectively improved, and the method is suitable for cable insulation state monitoring and fault early warning.

The invention provides a power load prediction method and device, and belongs to the technical field of power load prediction.The method comprises the steps that current waveform data are obtained, and fundamental wave and harmonic components in the current waveform data are extracted; carrying out waveform spatial form geometric analysis to obtain a real-time load characteristic sequence, and then carrying out segmentation processing; the current effective value sequence of each time window is converted into a time-frequency domain energy distribution vector, and then a three-level feature library is constructed; constructing a three-dimensional tensor model through equipment start-stop event identification, inputting the three-dimensional tensor model into a multi-target optimizer to evolve feature weights, and filtering abnormal samples to obtain a feature cluster; performing random masking processing on the time sequence data of the feature cluster to generate a mask sequence, inputting the mask sequence into an encoder to reconstruct masking data, comparing, learning and judging abnormal output correction data, and inputting the corrected data into a prediction network to generate a feedback signal flow; and analyzing the feedback signal flow to update the prediction network weight. Based on the method, the invention also provides power load prediction equipment. According to the invention, the precision of power load prediction is obviously improved.

The invention provides a vehicle battery health state assessment method and system based on a charging pile, and the method comprises the steps: collecting the electrical parameters in the connection process of the charging pile and a vehicle, marking a key event, carrying out the decomposition processing of a charging current waveform, obtaining a basic charging current component and a pulsation component caused by an equalization circuit, generating a basic charging current curve and a cell consistency index; current response characteristics in different charge state intervals are calculated based on the basic charging current curve, correction is carried out in combination with the power distribution state of the charging pile, and current response parameters of the battery are obtained; and combining the current response parameter and the cell consistency index with a historical charging record to form a time sequence feature, and performing comparative analysis on the time sequence feature and a preset reference mode to obtain a current health state index of the battery. According to the invention, the health state of the battery can be accurately evaluated in a multi-vehicle parallel charging environment, the consistency problem of the battery cells can be identified, and the evaluation service of the health state of the battery is provided for the electric vehicle.

The invention relates to the technical field of variable frequency speed regulation, in particular to an automatic water pump control strategy and energy efficiency optimization method and system.The method comprises the following steps of obtaining water pump outlet flow data, calculating flow acceleration, determining the pressure gradient direction, matching the hydraulic power trend, calculating frequency instruction deviation and setting the adjustable range; lagging and current rising mark inertia disturbance, power frequency limitation is set, a compensation value is generated, the frequency rate is dynamically adjusted in combination with all factors, and the frequency conversion adjusting priority is generated. According to the method, through matching of the flow acceleration and the pressure gradient, the sensing capacity for dynamic changes of fluid is improved, frequency adjustment of a frequency converter is optimized in combination with frequency deviation calculation, energy consumption increase caused by lag is reduced, and based on correlation analysis of the motor rotating speed change rate and current fluctuation, inertia disturbance accurate recognition is achieved; the voltage compensation timeliness is improved by combining bus voltage dynamic monitoring and a reverse compression strategy, the frequency of the frequency converter is dynamically adjusted by combining multiple parameters, and the response speed and the energy efficiency are improved.

The invention relates to the technical field of electrical safety early warning, and discloses an electrical fire early warning method and system. The method comprises the following steps: acquiring a multi-dimensional dynamic parameter set of an electrical circuit in real time, wherein the multi-dimensional dynamic parameter set comprises a current fluctuation sequence, temperature gradient distribution data and an insulating medium loss value; performing time-frequency domain joint decomposition processing on the dynamic parameter set, and extracting current harmonic distortion characteristics, a temperature field spatial evolution mode and a dielectric loss accumulation rate; generating a current anomaly index according to a harmonic distortion characteristic and a preset threshold deviation degree, calculating a thermal runaway risk level in combination with a temperature field spatial evolution mode, and determining an insulation degradation coefficient based on a dielectric loss accumulation rate; fusing the three to construct a comprehensive fire risk index; and when the index exceeds the dynamic warning threshold value, a grading early warning signal is triggered and a hidden danger positioning map is generated. According to the method, the electrical fire early warning effect is optimized through multi-dimensional parameter acquisition and fusion analysis.

The invention discloses a grid-connected inverter control method based on second-order linear active disturbance rejection, and particularly relates to the field of grid-connected inverter control. Voltage and frequency error signals between the output side of the inverter and the power grid are obtained, a pre-synchronization control model is constructed, and voltage amplitude and frequency synchronization is achieved; a second-order linear active-disturbance-rejection controller is introduced in the frequency synchronization control process, an extended state observer is adopted to estimate the output frequency, the frequency change rate and a disturbance term, and a state error feedback control law is combined to generate a frequency regulation control quantity, so that accurate frequency control is realized; after grid connection, a dual-channel LADRC power regulation controller is constructed, and decoupling tracking control is carried out on active power and reactive power; meanwhile, on the basis of fast Fourier transform processing as a stable grid-connected state criterion, the method has the advantages of being high in control precision, high in anti-interference capability, good in current waveform quality, high in adaptability and the like, and is suitable for various grid-connected application scenes.

The invention relates to the technical field of intelligent inspection control, and discloses a multi-dimensional intelligent inspection multi-device cooperative control method. The method comprises the following steps: synchronously acquiring a real-time operation parameter set of a plurality of monitored devices, wherein the real-time operation parameter set comprises a vibration spectrum, a temperature distribution map and a current waveform; performing multi-source heterogeneous data fusion processing on the real-time operation parameter set to generate a multi-dimensional feature vector; based on a preset collaborative optimization target, performing dynamic association analysis on the multi-dimensional feature vector to generate an equipment operation feature vector; and performing a matching decision according to the equipment operation feature vector and a preset cooperative constraint condition, and outputting a cooperative control instruction set. According to the method, through multi-dimensional data acquisition, fusion processing and dynamic association analysis, comprehensive perception and cooperative control of the multi-device operation state are realized, the coordination and reliability of device group operation are improved, and the method is suitable for multi-device cooperative operation and maintenance in a complex scene.

The invention provides a circuit breaker action coil current characteristic diagnosis and analysis system and method. Belongs to the technical field of power system automation and substation state monitoring. The method comprises the following steps: carrying out synchronous wave recording on current of a plurality of circuit breaker actuating coils on a direct current feeder screen side to generate multi-channel synchronous wave recording data; meanwhile, SOE message information is collected, a circuit breaker with specific action is automatically matched and positioned by utilizing a timestamp and action identification information in an SOE message, and action circuit breaker positioning data is generated; the current waveform data of the circuit breaker actuating coil are collected in real time, and a high-precision algorithm is used for feature extraction and analysis, so that abnormal fluctuation in current change can be accurately captured, such as overlarge starting current and unstable holding current, the risk of misoperation or rejection of operation of the circuit breaker caused by abnormal current characteristics is reduced, and the service life of the circuit breaker is prolonged. Electric power system accidents caused by equipment faults are avoided, and the operation reliability of the circuit breaker is improved.