90 results about "Harmonic amplitude" patented technology

The invention provides a non-intrusive diagnosis method for typical rotor faults of a synchronous phase modifier, and the method comprises the steps: carrying out finite element modeling and fault working condition setting, carrying out simulation to obtain magnetic field distribution data under each working condition, carrying out the extraction and feature analysis of stray magnetic field signals, extracting time domain and frequency domain signals of a stray magnetic field under healthy and various fault working conditions, and carrying out the diagnosis of the typical rotor faults of the synchronous phase modifier. Fundamental wave, odd-even harmonic components and signal change trends are compared and analyzed, stray magnetic field characteristics corresponding to faults are extracted and recognized, diagnosis criterion establishment and fault recognition are carried out, diagnosis criteria and threshold values of rotor turn-to-turn short circuit, dynamic eccentricity and shaft-diameter composite eccentricity faults are established according to the stray magnetic field characteristics, and the fault diagnosis accuracy is improved. And when the specific harmonic amplitude or change characteristic of the stray magnetic field signal exceeds the criterion threshold, determining the rotor fault of the corresponding type and degree. Equipment dismounting or structure reconstruction is not needed, the detection system is simple in structure, internal fault characteristics of the phase modifier can be reflected in real time, and high sensitivity and practicability are achieved.

The invention discloses an LSTM (Long Short Term Memory)-based harmonic frequency coupling model optimization method for a network construction type converter, which considers the influence of a dead zone and establishes a converter model controlled by a virtual synchronous generator based on a harmonic state space method. In the power electronic modeling process, due to approximate simplification, switch neglecting and other nonlinear relations, the model is not accurate enough, meanwhile, in the harmonic state space model modeling process, system state variable parameters need to be considered, and the precision of the model affects harmonic transmission characteristics and coupling analysis, so that the modeling efficiency is greatly improved. Errors caused by power electronic modeling are reduced through an LSTM neural network algorithm, the harmonic amplitude estimation difference is reduced, state variable parameter values in a system model are accurately estimated, the model precision is further improved, and then the harmonic coupling condition under the dead zone influence is effectively and accurately analyzed.

The invention relates to the technical field of power distribution network fault detection, and discloses a power distribution network high-resistance grounding fault intelligent detection method, system and device and a medium, and the method comprises the steps: collecting a power distribution network line transient signal which comprises a transient zero-sequence voltage signal and a transient zero-sequence current signal; preprocessing the transient signal and extracting a multi-dimensional feature set for representing high-resistance grounding fault characteristics, wherein the multi-dimensional feature set comprises a transient energy feature, a wavelet entropy feature and a harmonic component feature; and inputting the extracted multi-dimensional feature set into a pre-trained machine learning model, and simultaneously outputting a judgment result of the high-resistance grounding fault and an estimated value of the grounding resistance through the machine learning model. According to the method, the transient energy, the multi-scale wavelet entropy, the odd harmonic amplitude and the phase, which are derived from different analysis domains and have complementary physical meanings, are deeply fused, so that the problem that a single feature is weak in characterization capability and easy to fail under the conditions of high noise and high resistance is effectively solved.

The application discloses a kind of water electrolysis hydrogen production rectifier transformer harmonic active inhibition optimization method, comprising the following steps: constructing rectifier circuit, rectifier circuit includes switch tube, the voltage vector and zero vector of switch tube output are combined, and combined output voltage vector is obtained;The harmonic amplitude is obtained by processing combined output voltage vector, Levy tangent flight strategy and confidence domain variation strategy are introduced in black-winged kite optimization algorithm to construct improved dynamic search algorithm, the total harmonic distortion is obtained by iterative calculation of harmonic amplitude by improved dynamic search algorithm, i.e. optimal switch tube combination, the switch tube of rectifier circuit is adjusted by optimal switch tube combination, and the total harmonic distortion of rectifier circuit is reduced.The optimal switch tube combination of rectifier circuit is iteratively calculated by improved dynamic search algorithm in the application, effectively reduces resource consumption, and processing speed is accelerated, and the efficiency and accuracy of electrolytic water hydrogen production rectifier are improved.

The invention discloses a modularized multi-level converter fault positioning method based on TimesNet and a harmonic theory. The method comprises the following steps: carrying out bridge arm voltage sampling on a modularized multi-level converter to obtain a bridge arm voltage signal; carrying out harmonic parameter estimation on the bridge arm voltage signal based on a pre-trained Times Net network to obtain a harmonic amplitude, a harmonic phase and a background noise level; carrying out self-adaptive correction on a preset basic amplitude threshold according to the background noise level to obtain a dynamic amplitude threshold; and when the harmonic amplitude is greater than the dynamic amplitude threshold, determining that the modular multilevel converter has a fault, and positioning the fault sub-module according to the harmonic phase. The method improves the fault positioning accuracy and reliability of the modular multilevel converter, and can be applied to the technical field of DC power transmission and transformation.

The invention discloses a metering equipment remote calibration method and device, a medium and equipment. The method comprises the following steps: calculating a loss index according to current characteristics of an extracted current signal in a monitoring period, and determining a phase offset of each harmonic based on the loss index; constructing an environment gain coefficient according to the environment temperature and the environment humidity in the environment management period; constructing a current correction coefficient according to the fundamental wave amplitude of the current signal in the monitoring period and the environment gain coefficient; and correcting each harmonic amplitude in the next monitoring period according to the current correction coefficient, and correcting each harmonic phase in the next monitoring period according to the phase offset of each harmonic to obtain a calibration current in the next monitoring period.

The application relates to a semiconductor package failure detection method based on high harmonic amplitude-phase demodulation, and relates to the technical field of semiconductor package detection. The application is used to solve the problems existing in the prior art semiconductor package defect detection method. The application applies a current excitation to a measured semiconductor package to make the semiconductor package generate heat, and collects a thermal image sequence of the semiconductor package; a same-frequency quadrature reference signal of each harmonic of the thermal image sequence is synthesized according to the current excitation; a demodulation phase is extracted by using the same-frequency quadrature reference signal; a dominant path is extracted according to a fourth-order demodulation phase; the dominant path is verified according to a fifth-order and sixth-order demodulation phase; if the dominant path is verified to be correct, it is determined that the measured semiconductor package has a failure state corresponding to the dominant path; otherwise, the thermal image sequence of the measured semiconductor package is collected again for detection. The application is suitable for the fields of semiconductor package manufacturing and testing, quality and reliability control, failure analysis and the like.

The invention relates to the technical field of power monitoring, in particular to an online monitoring method and system for a power control cabinet. The method comprises the following steps: acquiring a time domain signal, tracking a fundamental wave frequency, adjusting a sampling window, and performing Fourier transform to obtain a harmonic amplitude and a phase; harmonic waves are divided into harmonic wave correlation groups according to association rules, harmonic wave phase consistency coefficients are calculated to weight the total energy in the groups, and weighted harmonic wave energy is obtained; total inter-harmonic energy is calculated, and an inter-harmonic structure factor is obtained based on the spectral entropy. And acquiring a real-time load rate and a change rate, and calculating a synchronous change coefficient and a load factor. And summing the weighted harmonic energy and the corrected inter-harmonic energy to obtain total distortion energy, and obtaining a comprehensive distortion index according to the total distortion energy. According to the scheme, the structured inter-harmonics possibly caused by the early failure of the equipment can be found earlier, and the requirements of early warning and predictive maintenance are met.

The invention relates to the technical field of PWM (Pulse Width Modulation), and discloses a method for optimizing double random PWM, which comprises the following steps: randomizing a carrier frequency fc and a pulse position to obtain double random PWM, performing parameter setting on random distribution of the carrier frequency and the pulse position by adopting a Sigmoid function, improving a genetic algorithm by utilizing a particle swarm algorithm, and optimizing the double random PWM. Optimizing a minimum value fmin of a random number of a carrier frequency or a pulse position, a maximum value fmax of the random number of the carrier frequency or the pulse position and a curve transverse adjustment parameter sigma of random number Sigmoid distribution in the double random PWM by adopting an improved genetic particle swarm algorithm; according to the method, harmonic energy is dispersed from frequency and phase dimensions to a wider range through double random PWM, the switching frequency and the harmonic amplitude at the integral multiple of the switching frequency are reduced, random numbers are distributed in a Sigmoid mode, and the carrier frequency and the pulse position can more easily avoid a sensitive area by means of the nonlinear probability density characteristic that samples are more on the two sides and less in the middle, so that the switching efficiency is improved. And EMI peaks caused by extreme parameters in traditional uniform distribution are reduced.

The invention discloses a distributed coupling harmonic wave cooperative positioning platform based on federated learning, relates to the technical field of power grid harmonic wave analysis, and solves the technical problems that harmonic wave data is uploaded in a concentrated manner, data leakage risks exist, the spatial dependency relationship of harmonic wave propagation between dynamic analysis nodes of a power grid topological structure is ignored, and the harmonic wave cooperative positioning accuracy is influenced. The connection relation between the nodes in the power grid topological structure can be quantified through the adjacency matrix, the observability contribution degree of each detection node to the whole network state can be accurately calculated in combination with the harmonic propagation model, measurement distribution points are optimized, and the positioning precision is improved. Gradient parameters are encrypted through a Paillier algorithm and then uploaded to a server, the server directly completes aggregation operation in a ciphertext domain, a global model can be updated without decryption, and node groups influenced by the same harmonic source are identified by calculating Spearman rank correlation coefficients of inter-node harmonic amplitudes and quantifying time synchronization degrees of different node harmonic signals.

The invention discloses a malignant load identification method suitable for an electric energy meter and an acquisition terminal, the electric energy meter and the acquisition terminal, and belongs to the technical field of load identification. The method comprises the steps that a target malignant load set is established, current data of the target malignant load set are collected, and after frequency domain features are extracted, a reference frequency domain combination feature vector of each load is constructed; obtaining target working condition current data in actual operation, and constructing a to-be-identified frequency domain combination feature vector in the same mode; and judging whether a malignant load exists or not by calculating the cosine similarity of the included angle between the two vectors. The invention also discloses an electric energy meter and a use and acquisition terminal based on the method. According to the method, the amplitude of the harmonic waves and the phase information are synthesized to construct the combined feature vector and perform similarity matching, so that the limitation that the prior art only depends on the amplitude of the harmonic waves is overcome, finer and more reliable identification of the malignant load is realized, and the misjudgment rate is effectively reduced.

The invention discloses a fault detection method and system for a permanent magnet synchronous motor, and relates to the technical field of permanent magnet synchronous motor fault detection.The method comprises the steps that stator three-phase current during operation of the permanent magnet synchronous motor is collected in real time, and zero-sequence current is calculated; carrying out multi-band frequency spectrum analysis based on the zero sequence current, respectively detecting a third harmonic amplitude and a sixth harmonic amplitude by adopting a parallel dual-channel FFT (Fast Fourier Transform) processor, and calculating a harmonic amplitude ratio; correcting the third harmonic amplitude and the sixth harmonic amplitude through a preset compensation coefficient matrix, and recalculating the corrected harmonic amplitude ratio; and performing fault classification on the corrected harmonic amplitude ratio based on a preset threshold value in combination with a time accumulation counter, and outputting a final fault code after continuous three times of consistent detection, thereby completing fault detection of the permanent magnet synchronous motor. The fault type can be rapidly positioned, the fault diagnosis precision is improved, it is ensured that an alarm is given after real faults are accumulated to the confirmable level, and the diagnosis reliability and stability are improved.

The application discloses an electromagnetic detection optimized bipolar SHMPWM transmitting method, which comprises the following steps: S1, by analyzing the influence of the resistive and inductive load on the transmitting current waveform distortion and the transmitting spectrum energy loss, extending the current waveform based on the equal-area principle, compensating for the lost transmitting current spectrum energy, and calculating the current waveform extension time; S2, considering the inductive load and the dead zone effect, establishing a bipolar SHMPWM nonlinear equation set; S3, using the particle swarm algorithm to iteratively operate the bipolar SHMPWM nonlinear equation set, and obtaining the solving result of the switching angle of the half-cycle symmetric SHMPWM. The application adopts the optimized particle swarm algorithm to solve the equation set to obtain the switching angle, and realizes that the frequency domain information of the half-cycle symmetric SHMPWM frequency focusing waveform conforms to the specific harmonic amplitude set by the expectation.

The application discloses a permanent magnet synchronous motor position estimation method based on secondary harmonic tracking. When the permanent magnet synchronous motor is in zero speed and low speed state, a high-frequency sinusoidal pulse voltage signal is injected into the estimated d-axis of the motor. The secondary harmonic current response signal is extracted, and the amplitude thereof is obtained through heterodyne and low-pass filtering processing. The system is converged to the minimum point of the current secondary harmonic amplitude through the minimum value gradient tracking method, so that the effective detection of the zero speed and low speed position of the permanent magnet synchronous motor is realized. The application can realize the unique position convergence point in the whole error range, so as to improve the estimation performance and robustness of the system in the zero speed and low speed interval.

The application discloses a three-level inverter harmonic suppression method based on zero vector symmetrical reconstruction and spread spectrum composite modulation, and the method comprises the following steps: step 1, signal acquisition and voltage instruction acquisition; step 2, spread spectrum modulation parameter setting; step 3, basic vector action time calculation; step 4, zero vector symmetrical reconstruction of vector sequence; step 5, switch time calculation and register updating; and step 6, PWM signal generation and system closed loop operation. The application realizes full-band suppression of inverter output PWM harmonics by deeply fusing the zero vector symmetrical reconstruction technology and the spread spectrum modulation technology. The application can be applied to a permanent magnet synchronous motor driving system powered by a three-level voltage source inverter, can simultaneously suppress the PWM harmonic amplitude near the odd carrier frequency and the even carrier frequency, effectively reduces electromagnetic vibration and noise, and has extremely high application value in the field of high-power inverters and motor drives.

The embodiment of the application provides a kind of wide frequency signal dynamic generation method and system based on multiple clock sources, the method comprises: by field programmable gate array real-time monitoring target frequency, and based on the frequency band of target frequency belongs to automatically switched to corresponding target clock source;When the target clock source is switched, the phase difference corresponding to the new and old target clock source is corrected by phase compensation register, and the compensation value is loaded to the phase offset register of direct digital frequency synthesis chip;Based on direct digital frequency synthesis chip, generate the fundamental wave waveform of wide frequency signal, and superimpose multiple harmonic components by sub-accumulation method, and the amplitude of each harmonic is independently controlled by look-up table method;The output signal of power amplifier is extracted by analog-digital converter, and the error information of measured waveform and theoretical waveform is extracted and dynamically corrected phase offset register and harmonic amplitude look-up table coefficient, and output target wide frequency signal.The application realizes the unity of wide frequency coverage, high resolution and fast response.

The application relates to the technical field of power conversion device control, and discloses a power distribution network power conversion equipment harmonic suppression method and system. The method comprises the following steps: collecting harmonic amplitudes to construct a state vector and a coupling matrix, predicting the control harmonic and calculating a feedback influence quantity, superimposing an inhibition quantity and a compensation quantity to generate a double-layer instruction to adjust a switching parameter, outputting a pulse width modulation signal and monitoring a residual error to update the coupling matrix. The application improves the global optimization performance of harmonic suppression and the self-adaptive ability to power grid environment changes.

The present application provides a real-time optimization method, system and device for inverter output voltage harmonics, the method comprising: obtaining control parameters of an inverter; controlling the inverter to work according to the control parameters and obtaining N waveforms corresponding to N periods; decomposing the N waveforms to determine a to-be-processed waveform harmonic; when the amplitude of the to-be-processed waveform harmonic exceeds a harmonic threshold, a first optimization mode is used for optimization processing; when the amplitude of the to-be-processed waveform harmonic does not exceed the harmonic threshold, a second optimization mode is used for optimization processing. A method combining two harmonic reduction technologies is used, when the harmonic amplitude is small, the active filter function of the auxiliary inverter is used to reduce the harmonic, and the SHEPWM complex calculation is not used, when the harmonic amplitude is large, the SHEPWM technology is used to eliminate the harmonic, and the flexibility of inverter control is improved.

The utility model relates to the technical field of power harmonic signal analysis, in particular to a harmonic amplitude extraction circuit, which is characterized in that a phase-locked loop is used for carrying out frequency multiplication processing on fundamental waves to obtain frequency multiplication waveforms, a filter waveform is obtained in a band-pass filtering mode, and the harmonic amplitude is extracted through multiplication of the two waveforms. According to the method, the waveform containing the harmonic amplitude characteristics is extracted through the low-pass filter, and finally the harmonic amplitude is extracted through the low-pass filter, so that Fourier transform and computer program calculation are not needed in the process, the real-time performance and continuity are good, and the consumption of hardware resources is low. According to the embodiment of the invention, the analog circuit is formed by only depending on common electronic components such as the operational amplifier, the resistor, the capacitor and the triode, the signal is operated and filtered, the reliability is high, the replaceability is good, and the maintenance and the precision adjustment of the circuit are facilitated.

The invention discloses an open-circuit fault diagnosis method and equipment applied to an inverter power supply of a hybrid power device. The method comprises the following steps: acquiring an output voltage or an output current in a current state; obtaining a current state, and obtaining each harmonic amplitude and a total harmonic distortion rate of a normal state; obtaining each harmonic amplitude offset and the total harmonic distortion rate offset of the current state; respectively comparing each subharmonic amplitude offset and the total harmonic distortion rate offset of the current state with the judgment threshold of the corresponding subharmonic amplitude offset and the judgment threshold of the total harmonic distortion rate offset; and determining that the open-circuit fault exists in the current state if the same specific subharmonic amplitude offset of the current state is greater than the judgment threshold of the corresponding subharmonic amplitude offset, or the total harmonic distortion rate offset of the current state is greater than the judgment threshold of the total harmonic distortion rate offset. According to the invention, the open-circuit fault of the inverter power supply of the hybrid power device can be diagnosed.

The invention discloses a non-linear periodic error correction method for a displacement sensor and the displacement sensor, and the method comprises the steps: enabling an error collection range to be the actual displacement range of the displacement sensor in a plurality of repetition periods, calculating equal-interval displacement values according to a theoretical range, and collecting a plurality of corresponding error data; fourier transform is carried out on the error data, multiple groups of harmonic parameters are obtained, and each group comprises harmonic frequency, harmonic amplitude and harmonic phase; sorting the harmonic parameters according to the harmonic amplitudes, and selecting a plurality of groups of harmonic parameters corresponding to larger amplitudes to establish an error mathematical model; calculating an error value corresponding to any original displacement value based on the model; and correcting the original displacement value according to the error value to obtain a corrected target displacement value. According to the technical scheme, the nonlinear periodic error can be effectively compensated, the output precision of the displacement sensor is improved, and meanwhile, the dependence on the manufacturing process is reduced. The sensor can be widely applied to the technical field of sensors.

The application discloses a kind of low-loss proportional amplification fluxgate current sensor measurement methods, it is related to current measurement technical field, including, obtaining the observation set of synchronous demodulation by phase-locked;Based on the scheduling optimization function of prediction set construction, apply soft opening constraint, amplitude stability constraint, phase consistency constraint and saturation depth constraint, output corresponding control variable;According to control variable setting excitation signal parameter and executing excitation drive and compensation injection, extract the harmonic amplitude-phase response of current cycle in demodulation window position;Harmonic amplitude-phase response is converted into linear measurement output of current cycle, while updating observation set.The application implements proportional closed-loop conversion in I / Q rectangular coordinates, combines amplitude error and phase error into compensation current update amount, and combines calibration proportionality coefficient and output amplitude limiting, so that closed-loop converges amplitude-phase deviation in linear interval quickly, improves compensation current stability and response speed and reduces energy consumption.

The invention discloses a measurement method of a fluxgate current sensor with low loss and scale amplification, which relates to the technical field of current measurement and comprises the following steps of: acquiring an observed quantity set subjected to phase locking synchronous demodulation; constructing a scheduling optimization function based on the pre-measurement set, applying a soft opening constraint, an amplitude stability constraint, a phase consistency constraint and a saturation depth constraint, and outputting a corresponding control variable; excitation signal parameters are set according to the control variables, excitation driving and compensation injection are executed, and harmonic amplitude phase response of the current period is extracted in the position of the demodulation window; and converting the harmonic amplitude-phase response into linear measurement output of the current period, and updating the observed quantity set at the same time. Proportional closed-loop conversion is implemented in I / Q rectangular coordinates, amplitude errors and phase errors are synthesized into compensation current updating quantity, and a calibration proportionality coefficient and output amplitude limiting are combined, so that a closed loop quickly converges amplitude-phase deviation in a linear interval, the stability and response speed of compensation current are improved, and energy consumption is reduced.

This invention discloses a high-precision power reconstruction method and system for low-frequency sampling of electricity meters, belonging to the field of electricity meter sampling. The method includes: acquiring low-frequency sampled current and voltage sequences; obtaining coarse-grained power baseline and residual data by performing two-dimensional phase point pairing and feature vector mining, and reconstructing using Gaussian process regression; importing the current and voltage sequences into a hybrid differential model, and calculating transient power increments through state transition equation propagation analysis; for the residual data, extracting harmonic amplitude, phase, and frequency parameters, and obtaining the power contribution of each harmonic through line impedance mapping inversion; and superimposing the coarse-grained power baseline, transient power increments, and the power contributions of each harmonic to obtain a full-band power sequence. This application solves the technical problem that existing low-frequency sampling electricity meters are unable to capture rapid transient processes, resulting in insufficient full-band power metering accuracy.

The invention discloses a harmonic extraction method and device based on an improved orthogonal phase-locked loop, a terminal and a medium, and the method comprises the steps: collecting a three-phase voltage signal, and carrying out the preprocessing of the three-phase voltage signal; calculating the frequency fluctuation quantity according to the fundamental frequency tracked by the orthogonal signal generator; based on the damping coefficient, processing the preprocessed signal through an orthogonal signal generator to generate an orthogonal signal; carrying out notch suppression on the preprocessed signal and the orthogonal signal, and optimizing a damping coefficient; park transformation is carried out on the preprocessed signals and orthogonal signals, and fundamental wave parameters are output through a PI regulator; configuring a central angular frequency for each to-be-extracted harmonic component based on the fundamental wave parameter, and calculating a harmonic amplitude and a phase; through the improved orthogonal signal generator, the fundamental wave phase locking anti-interference performance is improved, the fundamental wave phase locking error is reduced, and extraction deviation caused by frequency fluctuation is avoided.

The invention relates to the technical field of data transmission, in particular to a data transmission method and system in a wireless communication network, and the method comprises the steps: recognizing a current load type according to load operation state data, extracting harmonic signals before and after a load type switching moment, and calculating the amplitude variation of each harmonic to obtain harmonic content change characteristic data; calculating a differential interference coefficient of each radio frequency communication frequency band according to the frequency spectrum coverage degree of each sub-harmonic to each radio frequency communication frequency band and the corresponding harmonic amplitude variation; calculating the differential interference coefficient of each radio frequency communication frequency band and the background noise intensity in the original signal data to obtain an actual interference intensity value of each radio frequency communication frequency band, and determining a gain adjustment amount of a radio frequency amplifier corresponding to each radio frequency communication frequency band; adjusting the gain parameter of each radio frequency amplifier according to the gain adjustment amount, and then performing data transmission; and the communication quality stability of the wireless communication network in a complex electromagnetic environment is improved.

The invention relates to the technical field of power systems, in particular to a harmonic source dynamic monitoring and responsibility distribution platform and method, and the platform comprises the following steps: a real-time monitoring module, a harmonic source positioning module, a responsibility distribution module, an alarm and event recording module and a data management and analysis module. According to the system, the time domain sampling density of high-frequency harmonics is remarkably improved, the sampling rate of 20 kHz enables the number of sampling points in a single period to be increased to 6.67 points from 1.67 points in the sampling process of 5 kHz, the problem of waveform distortion caused by time domain signal discretization is effectively solved, the actually measured harmonic amplitude error is converged to be within + / -5% from + / -30%, the phase error is reduced to be negligible, and the method has the advantages that the method is simple and easy to implement. The method can automatically detect and correct error frequency components in a frequency spectrum, and when 18kHz harmonic waves are aliasing to 2kHz due to undersampling, the algorithm matches with a harmonic wave prior model through amplitude correlation analysis, and redistributes energy to real frequency points, so that the identification accuracy of harmonic wave times is improved, and a real and reliable data basis is provided for subsequent analysis.

The application provides an intelligent identification method for load characteristics of electrical equipment, comprising the following steps: S1. collecting load signals of the electrical equipment during operation, including voltage and current signals, and recording a collection period of the load signals of the electrical equipment during operation; S2. processing and transforming the load signals by using Fourier series to obtain a direct current component value, a fundamental wave amplitude, a harmonic amplitude and a phase of the load signals; and S3. constructing a characteristic matrix based on the direct current component value, the fundamental wave amplitude, the harmonic amplitude and the phase of the load signals. Through the above method, the load characteristics of each electrical equipment in the distribution network can be accurately identified, accurate data support is provided for power supply of the distribution network, and accurate data support is provided for judgment of electrical equipment abnormalities and early warning analysis of electrical fires.

The invention relates to the technical field of electric energy meter monitoring, in particular to a power utilization data analysis method and system for an electric energy meter, and the method comprises the following steps: responding to an electric quantity sudden drop event, triggering an intelligent electric energy meter to collect current waveform data, and carrying out the fast Fourier transform of the collected current waveform data, and calculating amplitudes and phases of the fundamental wave and each harmonic wave, and establishing wave recording harmonic characteristic data. According to the method, through real-time response to an electric quantity sudden drop event, short-time high-frequency current waveform data is acquired, and frequency domain transformation is executed, the amplitude and phase of a fundamental wave and each harmonic wave can be positioned, then structured wave recording harmonic characteristic data is constructed, deep analysis of original current change is realized, and the accuracy of wave recording is improved. And meanwhile, the harmonic amplitude ratio is extracted and the phase angle is combined to construct the harmonic feature vector, so that the fine identification capability of the load feature is enhanced.

The invention discloses a power consumer portrait construction method based on two-dimensional feature fusion, and belongs to the technical field of power big data analysis and intelligent power grid management, and the method comprises the following steps: carrying out the optimization and screening of power consumption behavior features; iteratively optimizing the feature subset by using a sparrow search algorithm; dynamically extracting harmonic characteristics; fourier transform is carried out on wave recording data of 50Hz / 10k sampling point seconds, a current effective value and each harmonic amplitude are extracted, a correlation coefficient between the current effective value and a total harmonic distortion rate is calculated, main harmonic waves are counted in a classified mode according to power utilization scenes, and scene and harmonic wave mapping rules are established; constructing a user portrait; and generating a power consumption behavior tag based on the optimized power consumption behavior feature subset. According to the method, the problems that a traditional user portrait depends on a single power consumption behavior feature, the dimensionality is missing, the feature dimensionality is simplified, the correlation between a harmonic feature and a scene is ignored, the scene adaptability is poor, a feature redundancy processing mechanism is missing, and the dynamic scene adaptability is insufficient are solved.