65 results about "Harmonic amplitude" patented technology

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 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 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 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 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 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 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.

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 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 relates to the technical field of power conversion device control, and discloses a harmonic suppression method and system for power conversion equipment of a power distribution network. The method comprises the steps of collecting harmonic amplitude to construct a state vector and a coupling matrix, predicting control harmonic and calculating feedback influence quantity, superposing suppression quantity and compensation quantity to generate a double-layer instruction to adjust switch parameters, outputting a pulse width modulation signal and monitoring residual error to update the coupling matrix. According to the invention, the global optimization performance of harmonic suppression and the adaptive capacity to the power grid environment change are improved.

The invention discloses a multi-source data fusion power grid equipment digital twin modeling method and system. The method comprises the steps of S1, collecting original sensing data, sensing node working load power, power grid harmonic frequency, harmonic amplitude proportions of all orders and equipment equivalent load power of power grid equipment; s2, calculating a dynamic error factor of sensing node aging, and correcting the original sensing data by adopting the factor; s3, calculating a nondimensionalized harmonic accumulation interference coefficient, and correcting the data after aging correction by adopting the coefficient; and S4, calculating a temperature rise space-time coupling correction amount based on the coupling effect of the harmonic accumulation interference coefficient and the equivalent load power, introducing a reference temperature to construct a dimensionless temperature ratio to correct harmonic corrected data, obtaining real fusion data, and inputting the real fusion data into a twin model to iterate and update parameters. According to the method, the problem of model precision drift is solved through correction logic of progressive linkage, and the stability and accuracy of twin modeling are improved.

The application relates to a cable insulation safety evaluation method and system based on harmonic data preprocessing, and the method comprises the following steps: collecting voltage or current data of a cable to be detected; according to the periodic characteristics of harmonics, harmonic data is updated after reaching a preset fixed time each time, the process of the harmonic data updating comprises the following steps: extracting harmonics of the voltage or current data through a wave trap, and compensating the harmonic phase by using a repetitive predictive controller to obtain extracted harmonics; multiplying the extracted harmonics by an amplitude gain module to compensate the harmonic amplitude and obtain optimized harmonics; subtracting the optimized harmonics from the original voltage or current data to obtain fault data; performing traveling wave decoupling on the fault data, and judging the fault type and fault distance of the cable according to the traveling wave signal obtained through decoupling. Compared with the prior art, the application realizes rapid evaluation of cable insulation safety and rapid and accurate positioning when the insulation is damaged.

The application discloses a cascaded H-bridge inverter SHEPWM method based on an NR-ACA algorithm, which comprises the following steps: expanding a cascaded output voltage expression by using a Fourier series to obtain an expression of harmonic amplitude; according to a harmonic to be eliminated, making the corresponding harmonic amplitude expression 0, thereby establishing a nonlinear equation group; converting the nonlinear equation group into a single-target optimization problem by using an ant colony algorithm; taking the switch angle obtained by the ant colony algorithm as a switch angle initial value of a Newton iteration method to calculate a high-precision switch angle; and generating a driving pulse of the cascaded H-bridge by using the switch angle calculated by the algorithm. The application greatly reduces the calculation amount, improves the convergence speed, makes the calculated switch angle more accurate than a single intelligent algorithm, basically eliminates the selected harmonic, greatly reduces the switch loss, and makes the application more applicable to engineering.

This invention relates to the field of transformer technology and discloses a method and apparatus for harmonic suppression in a transformer for AI computing power supply and energy storage devices. The method involves: acquiring the current on the primary side of the transformer and calculating the characteristic harmonic amplitude data injected into the primary side of the transformer and the phase angle difference parameters of the multi-split windings when the GPU server switching power supply is running in parallel; introducing inter-winding phase angle differences for each split winding and arranging the turns ratio so that the low-order characteristic harmonic currents cancel each other out when superimposed on the primary side by each split winding, and obtaining the residual harmonic current after mutual cancellation; extracting high-order harmonic components through an active harmonic compensation unit integrated within the transformer, and injecting a first compensation current with equal amplitude and opposite phase to the high-order harmonic components into the common node of the transformer windings. This invention achieves stable suppression of the total distortion rate of transformer-side harmonic currents under all operating conditions of AI computing power.

This invention discloses an online diagnosis and location method for generator rotor faults, belonging to the field of generator fault diagnosis technology. The method includes the following steps: S1, arranging a magnetic field sensor array to synchronously acquire the time-domain signal of the air gap magnetic field during operation; S2, performing spectrum analysis to extract the amplitude of the harmonic components at twice the electrical frequency; S3, online diagnosis of either a loose pole bolt fault or a mass imbalance fault; S4, when an online diagnosis of a loose pole bolt fault is made, a shutdown and turning operation is performed. By monitoring the signal strength of the magnetic field sensor located directly below the rotor and finding the point of maximum signal strength, the mechanical angle position of the loose pole is determined. This invention, based on a magnetic field sensor array arranged along the stator circumference and axis, extracts the spatial distribution characteristics of the harmonic amplitude at twice the electrical frequency and compares it with a threshold, enabling accurate online differentiation between loose pole bolt faults and mass imbalance faults, greatly improving the accuracy of online diagnosis.

The invention discloses an inductance harmonic measurement and analysis method, which is based on an alternating current static measurement method and comprises the following steps of: 1, establishing an inductance harmonic model: respectively constructing a self-inductance model of a stator winding, an inter-phase mutual inductance model and a self-inductance and mutual inductance matrix model of a three-phase winding; 2, an alternating current static measurement circuit is adopted, alternating current with a fixed frequency is introduced into two-phase windings of the motor, a motor rotor is kept static at different space angle positions, and voltage and current parameters between the two phases are measured; step 3, based on a measurement result, calculating to obtain a comprehensive inductance parameter which is LAA-MAB + LBB-MAB and changes along with the rotor position angle theta; and 4, extracting second-order and fourth-order harmonic amplitudes of the inductor to obtain the harmonic content of the inductor of the motor. According to the method, the second-order and fourth-order harmonic amplitudes of the winding inductance of the permanent magnet synchronous motor can be accurately extracted, so that the harmonic content of the inductance of the motor body related to second-order and fourth-order noise is effectively evaluated, and accurate inductance harmonic data is provided for noise optimization of an EPS system.

The invention discloses a permanent magnet synchronous motor full-frequency-domain harmonic suppression method based on collaborative observation and spectrum expansion, relates to the technical field of permanent magnet synchronous motor control, and aims to solve the problems that low-order harmonics are introduced into an existing permanent magnet synchronous motor due to nonlinear factors of an inverter, high-frequency sideband harmonics are introduced into the existing permanent magnet synchronous motor due to fixed carrier frequency, and the harmonic suppression efficiency is low. And the problem that the low-order harmonic amplitude is increased after the asymmetric rotor structure is optimized is solved. According to the method, an active-disturbance-rejection control module is constructed to suppress low-order harmonics, a random SVPWM modulation module is designed to suppress high-frequency sideband harmonics, and a full-frequency-domain harmonic collaborative suppression strategy is formed. The method provided by the invention can effectively reduce fifth and seventh current harmonic amplitudes, high-frequency sideband current harmonic amplitudes and carrier vibration amplitudes, remarkably improves the operation stability and NVH performance of the permanent magnet synchronous motor, and is suitable for a permanent magnet synchronous motor driving system for an electric vehicle.

The application relates to the field of electric digital processing, in particular to a power grid harmonic identification method and system based on deep learning, which comprises the following steps: inputting processed voltage data and current data into an LSTM model, outputting predicted data of voltage and current, obtaining voltage sequences and current sequences after processing, performing window division on the voltage sequences and the current sequences, obtaining local waveform differences in combination with amplitude spectra of corresponding windows, obtaining harmonic amplitude sequences by the amplitudes of the frequency corresponding to odd harmonics in the window sequence amplitude spectrum, obtaining harmonic amplitude change sequences after processing, obtaining harmonic similarity in combination with the local waveform differences, obtaining the harmonic contribution degree of a load feeder by using the harmonic amplitude sequences of different odd harmonics in the common coupling point voltage sequence to obtain the integrated harmonic similarity of the recognition significance degree, and sorting the harmonic contribution degrees and selecting a preset proportion of harmonic contribution degrees that meet preset conditions. The application has the effects of accurately locating a harmonic source and improving harmonic source identification accuracy.

The invention relates to the field of electric digital processing, in particular to a power grid harmonic recognition method and system based on deep learning, and the method comprises the steps: processing collected voltage data and current data, inputting the processed data into an LSTM model, outputting the prediction data of voltage and current, obtaining a voltage sequence and a current sequence after processing, carrying out the window division, and obtaining a current sequence; obtaining a local waveform difference by combining the amplitude spectrum of the corresponding window, obtaining a harmonic amplitude sequence through the amplitude of the frequency corresponding to the odd harmonic in the amplitude spectrum of the window sequence, obtaining a harmonic amplitude change sequence after processing, and obtaining harmonic similarity by combining the local waveform difference; the harmonic amplitude sequences of different odd harmonics in the common coupling point voltage sequence are utilized to obtain the harmonic contribution degrees of the load feeder line by integrating the significance degree and the harmonic similarity, the harmonic contribution degrees are sorted, and the harmonic contribution degrees with the preset proportion are selected to meet the preset condition. The method has the advantages that the harmonic source can be accurately positioned, and the harmonic source identification accuracy is improved.

The invention discloses an asynchronous motor harmonic suppression method, device and equipment and a storage medium, and relates to the technical field of motor control, and the asynchronous motor harmonic suppression method comprises the steps: obtaining a harmonic component in the current of an asynchronous motor, and generating a voltage harmonic compensation signal for suppressing the harmonic component; generating a randomly changing carrier frequency signal; injecting the voltage harmonic compensation signal into a voltage signal output by a current inner loop; and modulating the voltage signal after injection compensation based on the carrier frequency signal so as to generate a driving signal and act on the asynchronous motor. According to the invention, the common-mode voltage and the harmonic current can be suppressed at the same time, the harmonic content and the harmonic amplitude are significantly reduced, and the hardware cost is not increased.

The invention discloses a method for identifying first third-order harmonic waves of unbalanced mass of a hemispherical resonator based on vibration excitation, and belongs to the field of parameter identification of hemispherical resonators. The method solves the problems of low leveling efficiency and precision caused by difficult data identification and long measurement time of an existing method for identifying the first third-order harmonic waves of the unbalanced mass. Under vibration excitation, the vibration amplitude and the standing wave azimuth angle of the hemispherical harmonic oscillator are associated with the first-order harmonic and the third-order harmonic of the unbalanced mass; under vibration excitation, the vibration amplitude and the standing wave azimuth angle of the hemispherical harmonic oscillator are associated with the second-order harmonic of the unbalanced mass. And the first three-order harmonic amplitudes and azimuth angles are solved by constructing a corresponding coupling relationship. The method is mainly used for identifying the first third-order harmonic waves of the unbalanced mass of the hemispherical harmonic oscillator.