811 results about "Band-pass filter" patented technology

A tracking and adaptive compensation method for power fluctuation of a pulse load of a ship is provided. The method includes: based on a microgrid topology model of the ship, a pulse load model of the pulse load, and an interharmonic power and pulse parameter relationship model, performing power fluctuation tracking, frequency selection and a power spectrum analysis to obtain filtering parameters of a low-pass filter and filtering parameters of a band-pass filter; performing waveform adaptation to eliminate a phase delay caused by the low-pass filter and the band-pass filter, and obtaining a control command for a power compensation strategy; and generating, by a power loop, a pulse width modulation (PWM) signal to control a switching tube in a bidirectional direct current (DC) / DC converter of each of an energy storage battery pack and a supercapacitor of a hybrid energy storage system.

The invention belongs to the technical field of signal acquisition and processing, and discloses a low-noise biopotential signal acquisition system and a low-noise biopotential signal processing method. An original bioelectricity signal of a human body is collected through an electrode array, and analog-to-digital conversion is carried out after the signal is processed by a multi-stage self-adaptive filtering and amplifying circuit. A digital signal is sequentially subjected to adaptive wavelet transform denoising and empirical mode decomposition to obtain a multi-level intrinsic mode function set, an intrinsic mode function of a characteristic frequency band is extracted from the multi-level intrinsic mode function set, and the signal is reconstructed. Introducing a dual noise reduction mechanism combining adaptive wavelet transform and empirical mode decomposition; a signal quality real-time evaluation system is established, and system parameters including the gain of a variable gain amplifier and the bandwidth of a dynamic band-pass filter are dynamically adjusted through closed-loop feedback. The self-adaptive optimization of the whole biopotential signal acquisition process is realized, various interferences are effectively inhibited, the signal characteristics are reserved, and the signal-to-noise ratio is remarkably improved.

The invention discloses a symmetrical structure S-band filter based on GaAs IPD, which belongs to the technical field of microwaves and comprises a first-order series resonance circuit, a coupling capacitor C1, a grounding inductor L2, a coupling capacitor C2, a second-order parallel resonance, a third-order parallel resonance, a grounding capacitor C6, a coupling capacitor C7, a fourth-order parallel resonance, a grounding capacitor C66, a fifth-order parallel resonance, a coupling capacitor C22 and a grounding inductor L22. And a coupling capacitor C11 and a sixth-order series resonance. The third-order parallel resonance and the fourth-order parallel resonance can improve the low-frequency out-of-band suppression degree of the band-pass filter; the first-order series resonance and the sixth-order series resonance as well as the second-order parallel resonance and the fifth-order parallel resonance can improve the high-frequency out-of-band suppression degree of the band-pass filter.

The invention relates to a time-varying power high-precision calculation technology of an electric drive system under strong electromagnetic noise interference, and mainly solves the problem of inaccurate power calculation of the electric drive system under strong electromagnetic environment noise and frequency time-varying fluctuation scenes. According to the core technology, a dominant frequency fluctuation curve of a signal is obtained through dynamic tracking of a dominant frequency, and a dynamic band-pass filter changing along with the dominant frequency of the electric drive system is constructed; suppressing pulse noise by combining amplitude self-adaptive filtering of a nonlinear weighting function; a phase demodulation technology fusing zero crossing point correction and Hilbert transform is adopted to eliminate the phase interference problem caused by complex waveforms and weak noise signals; and finally, establishing a time-varying power physical model based on the sliding window. According to the technology, the power calculation accuracy of the electric driving system under the conditions of strong field environmental noise and continuous main frequency conversion is remarkably improved.

The invention provides an artificial intelligence submarine topography inversion system and method using gravitational field spatial spectrum data, and the system comprises a gravitational field spatial spectrum calculation module which uses a plurality of band-pass filters to intercept gravity data under different wavelengths; and the gravity-water depth mapping relation establishing module is used for processing gravity and water depth data and establishing a correlation between the gravity and water depth data. A gravitational field spatial spectrum of a sparse ship water depth measuring position is obtained and is paired with water depth data. Dividing the data set into a training set and a test set in proportion; and designing an artificial intelligence model suitable for a regression task for training and predicting the water depth. And the artificial intelligence submarine topography inversion module is used for predicting a water depth value by using the gravitational field spatial spectrum of the trained model input test set, and evaluating a prediction effect through a precision index. The method has the advantages that the characteristics of the gravity data are enriched through the calculation of the gravity field spatial spectrum, and different degrees of influences of gravity on terrain inversion are considered.

The invention discloses an underwater sensor signal adaptive denoising method based on an attention mechanism and CNN-LSTM, and the method comprises the steps: S1, obtaining an original underwater signal collected by an underwater sensor, carrying out the preprocessing of the original underwater signal, carrying out the preliminary filtering of the signal through a band-pass filter, and removing an overhigh or overlow frequency component; s2, carrying out feature extraction on the preprocessed signal by adopting a convolutional neural network; and S3, performing time sequence information processing by adopting a long short-term memory network based on an attention mechanism. The invention discloses an underwater sensor signal adaptive denoising method based on an attention mechanism and CNN-LSTM, and aims to solve the problem of interference of complex noise in an underwater environment on sensor signals. In combination with an attention mechanism in deep learning, a key part in a signal is focused through self-adaptive weight distribution, so that a more accurate denoising effect is realized.

The invention discloses a composite fault signal separation method based on adaptive spectral kurtosis deconvolution. The method comprises the following steps: S1, carrying out noise reduction processing on an original composite fault signal; s2, separating the composite fault signal after noise reduction through Hilbert envelope demodulation; s3, optimizing a low-pass filter and a high-pass filter through a Bayesian objective function, and constructing a band-pass filter and a band elimination filter; and S4, carrying out iterative filtering on the composite fault signal after noise reduction through a band-pass filter and a band elimination filter, constructing a frequency-bandwidth fast spectral kurtosis graph according to a fast spectral kurtosis deconvolution method, obtaining a center frequency and bandwidth range corresponding to the maximum spectral kurtosis, and separating out the weak fault signal in the step S2. According to the method, a spectral kurtosis graph is constructed by combining a low-pass filter and a high-pass filter through a fast spectral kurtosis deconvolution method to determine the center frequency and the bandwidth range, targeted separation is carried out on composite fault signals, an initial filtering parameter range is provided for Bayesian optimization, and the fault separation efficiency and accuracy are improved.

The invention relates to a system and a method for making a colored low-light image. The system for making the color low-light-level image comprises a high-sensitivity CMOS imaging module which is used for enhancing the photon collection capability and reducing the noise level to complete imaging; the image enhancement processing module adopts a histogram equalization algorithm and comprises the steps of calculating a gray histogram of the original image, calculating a cumulative distribution function according to the gray histogram and performing gray mapping to obtain an enhanced gray value; the image noise reduction processing module is used for carrying out noise reduction on the image after enhancement processing, and filtering is carried out by adopting a night image noise reduction technology, a bilateral filtering method including spatial domain noise reduction and a band-pass filter including frequency domain noise reduction; and the colorful low-light-level image generation module obtains a colorful low-light-level night vision image by adopting an interpolation algorithm and makes a colorful low-light-level image. According to the system and the method for manufacturing the colored low-light-level image, special equipment is not depended on, the imaging quality of the colored low-light-level image can be improved, and the colored low-light-level image can be manufactured.

The invention belongs to the technical field of nondestructive testing, and discloses an acoustic emission, DIC and infrared technology combined integrated nondestructive testing method which comprises the following steps: acquiring damage related data of a material or a component; the method comprises the following steps of: acquiring data, preprocessing the acquired data, preprocessing acoustic emission data through a band-pass filter and feature extraction, carrying out DIC emission data preprocessing by using Brown distortion model correction image and distortion coefficient feature extraction, and carrying out infrared data preprocessing module processing through infrared image, radiance and black body calibration and feature extraction; and carrying out data fusion on the preprocessed data through a Kalman filter and a corresponding sensor. According to the method, combined application of the acoustic emission technology, the DIC technology and the infrared technology is integrated, mutual complementation can be achieved through combined application of the acoustic emission technology, the DIC technology and the infrared technology, limitation of a single technology is overcome, the damage state of the material can be recognized and evaluated more accurately, and data processing efficiency and accuracy are improved.

The invention discloses a permanent magnet motor turn-to-turn short circuit fault diagnosis method considering complex working condition influence, belongs to the technical field of permanent magnet motor fault diagnosis, and aims to solve the problems that a turn-to-turn short circuit diagnosis result of a permanent magnet synchronous motor for an electric vehicle is easily influenced by working conditions and slight faults are difficult to diagnose under complex operation working conditions. The method comprises the following steps: step 1, high-frequency signal injection and information acquisition; injecting the high-frequency rotating voltage signal into a motor control system under a natural coordinate system, and collecting each phase of high-frequency current and each phase of high-frequency voltage of the motor through a band-pass filter; 2, subtracting the high-frequency voltage from the healthy voltage under the condition that the high-frequency signal is injected, and calculating to obtain a high-frequency voltage residual error of each phase; 3, according to the high-frequency voltage residual error of each phase, obtaining two fault characteristic quantities, namely the standard deviation of the high-frequency voltage residual error and the absolute average value of the high-frequency voltage residual error of each phase; and 4, judging whether a turn-to-turn short circuit fault occurs or not according to the fault characteristic quantity, and judging a fault phase.

The invention relates to a test method of an organic electrochemical transistor tuning dual-mode flexible band-pass filter. The IPC classification number is G01N3 / 32. According to the organic electrochemical transistor tuning dual-mode flexible band-pass filter, the thickness of a silver metal film is gradually increased from the inner edge to the outer edge of a leading-out end part, connected with a filter functional area, of the organic electrochemical transistor tuning dual-mode flexible band-pass filter, and the thickness is gradually increased to 2-3 times from the thickness of the filter functional area; and an interface stress tolerance area between the silver metal film layer and the polyimide film is gradually transferred to the leading-out end part and presents a gradual change trend. When bending, folding and twisting tests are carried out on the flexible band-pass filter, the problems that the leading-out end part is cracked, fractured, peeled off and the like earlier than the functional area of the filter can be avoided, so that the mechanical property of the flexible band-pass filter can be accurately, objectively and completely tested in the whole test process; and the condition that the leading-out end part is damaged in advance when the mechanical property of the filter is not completely tested is avoided.

The invention relates to a fusion power supply harmonic suppression method based on an energy storage type STATCOM. The method comprises the following steps: determining a harmonic amplification factor K value; selecting and designing a proper discrete digital band-pass filter, and detecting a target frequency band and filtering characteristic sub-harmonics; the detected harmonic voltage amplitude and phase are used as references, an energy storage type STATCOM is adopted to output same-frequency and same-phase harmonic current, virtual damping is formed at a grid-connected point, a K value is used as a damping coefficient, the output harmonic current reference amplitude is determined, virtual harmonic damping is controlled, and harmonic resonance is suppressed. The virtual harmonic damping method for the energy storage type STATCOM is provided for accurate tracking of low-frequency harmonic and inter-harmonic voltage amplitudes and phases, the chain type STATCOM has the advantages of being high in high-voltage direct-hanging efficiency, high in redundancy fault-tolerant capability and the like and is suitable for high-voltage large-capacity scenes, virtual damping control achieves harmonic suppression by adjusting virtual damping at the harmonic frequency of a control structure, and the energy storage type STATCOM can be applied to high-voltage large-capacity scenes. And the system stability can be effectively improved while harmonic waves are treated.

The invention discloses a digital frequency band protection method for an integrated radio frequency system, belongs to the technical field of integrated radio frequency integration, and is used for performing receiving protection processing and transmitting protection processing on signals in a digital signal processing stage between a broadband radio frequency transceiving subsystem and a signal processing subsystem in the integrated radio frequency system. According to the method, from the aspect of frequency division multiplexing, required signal frequency points are selected through the configurable band-pass filter bank for subsequent processing, and frequency points interfering other load systems are filtered through the configurable band-stop filter bank, so that the frequency band protection function of the integrated radio frequency system is achieved, and guarantee is provided for multi-load cooperative work; meanwhile, through flexible implementation of a field programmable gate array (FPGA) device, the method can multiplex a hardware platform with a broadband radio frequency transceiving subsystem or a signal processing subsystem, and the problem that independent equipment must be adopted in a traditional electromagnetic signal processing method is solved.

The invention discloses a track fault identification method and system based on HSROA, and the method comprises the steps: calculating a frequency band entropy value of at least one IMF component signal, and selecting a sensitive IMF component signal from the at least one IMF component signal according to the frequency band entropy value; filtering the sensitive IMF component signal for the second time according to a band-pass filter to obtain a target signal, and performing envelope power spectrum analysis on the target signal to obtain a fault characteristic frequency; fusing the fault feature frequency with a time domain feature, a frequency domain feature and a time-frequency domain feature in the track vibration signal to obtain a fusion feature vector, and constructing a fusion feature matrix according to the fusion feature vector; and inputting the fusion feature matrix into a preset deep belief network for iterative training to obtain a track fault recognition model, inputting the obtained real-time track vibration signal into the track fault recognition model, and outputting the track fault recognition model to obtain a track fault recognition result.

A method and apparatus for converting an input frequency to a voltage signal using a passive band-pass filter. The method includes providing an input signal having a specified frequency and amplitude to a passive band-pass filter. The method also includes obtaining an attenuated signal corresponding to the input signal from the passive band-pass filter. The method also includes providing the attenuated signal to a peak detector to obtain a direct current (DC) signal having an output voltage proportional to the specified frequency. The passive circuitry includes a first circuit to receive an input signal having a specified frequency and amplitude, and output an attenuated signal corresponding to the input signal. The passive circuitry also includes a second circuit to convert the attenuated signal to a DC signal having an output voltage proportional to the specified frequency.

The invention discloses a self-adaptive damping controller and a wind power grid-connected system oscillation suppression method thereof, and the method comprises the steps: building a wind power grid-connected system simulation model, obtaining a system closed-loop transfer function, and connecting the damping controller between a wind power plant side and a power grid side; calculating a logarithmic derivative, analyzing impedance characteristics, judging whether the wind power grid-connected system has an unstable oscillation mode or not, and if so, calculating oscillation frequency; carrying out adaptive parameter setting on the damping controller according to the oscillation frequency, wherein the adaptive parameter setting comprises setting of parameters of a band elimination filter, setting of parameters of a band pass filter, setting of the capacity of the damping controller and setting of parameters of a phase shift link; a current reference signal is generated through the subsynchronous damping calculator and then is converted into a three-phase current through the subsynchronous current generator, the three-phase current is injected into a power grid, the impedance characteristic under the oscillation frequency is adjusted, and system oscillation is restrained. Parameters can be adjusted according to the oscillation frequency, complexity is low, implementation is easy, and high efficiency and accuracy of oscillation suppression are met at the same time.

The invention belongs to the technical field of bridge body monitoring, and discloses a bridge crack propagation evaluation method and system based on acoustic emission signals. The method comprises the following steps: arranging an acoustic emission sensor array at a preset part of a bridge to collect original acoustic emission signals in a preset time period; processing by adopting a band-pass filter to obtain a filtered acoustic emission signal, and separating the filtered acoustic emission signal by using an empirical mode decomposition technology to obtain an effective acoustic emission signal; converting the effective acoustic emission signal by using time-frequency transformation to obtain a signal time-frequency diagram; constructing a crack propagation evaluation model, and obtaining a crack propagation rate and a serious state grade; obtaining a crack space positioning result through crack space positioning; respectively carrying out weighted fusion on the crack propagation rate and the serious state grade of the J sensors, combining with a spatial positioning result and a bridge model, and presenting in a three-dimensional form; according to the invention, more accurate crack positions can be obtained.

The invention provides a vital sign detection method and device based on a millimeter wave radar, electronic equipment and a storage medium. The method comprises the following steps: obtaining a distance frequency domain signal based on a radar echo signal; performing spectral analysis on the distance frequency domain signal, positioning the position of the to-be-detected object, and extracting phase information at the position; filtering through a band-pass filter to obtain a breathing frequency band interval signal and an initial heartbeat frequency band interval signal; performing real-time respiration rate estimation based on the respiration frequency band interval signal to obtain a respiration frequency, and eliminating respiration harmonics in the initial heartbeat frequency band interval signal by using an adaptive wave trap based on the respiration frequency to obtain a heartbeat frequency band interval signal; and with the minimum fuzzy entropy as an optimization target, decomposing the heartbeat frequency band interval signal by using a variational mode decomposition algorithm to obtain a heartbeat signal, and carrying out real-time heart rate estimation based on the heartbeat signal to obtain a real-time heart rate. According to the method, the device, the electronic equipment and the storage medium provided by the invention, the accuracy of heart rate measurement can be improved.

The invention relates to the technical field of medical signal processing, in particular to a BCG signal processing method combining TimeGAN and a Butterworth filter, which comprises the following steps: carrying out preliminary noise reduction on an input BCG signal by adopting a Butterworth band-pass filter to obtain a filtered signal; performing phase compensation on the filtered signal by adopting a bidirectional filtering mode to obtain a signal without phase distortion; the trained TimeGAN model is adopted to carry out signal optimization on the signal without phase distortion, and an optimized signal is obtained; the TimeGAN model comprises a convolutional neural network which is used for inputting data in the TimeGAN model to carry out feature extraction so as to obtain corresponding local features; the long short-term memory network is used for carrying out time sequence modeling on the local features to obtain corresponding time sequence features; the multi-head attention mechanism is used for calculating weighted features based on the time sequence features; and the generator is used for generating an optimized signal according to the weighted characteristics.

The invention discloses an equipment micro-vibration real-time monitoring method and system based on visual enhancement, and belongs to the field of equipment micro-vibration monitoring, and the method comprises the following steps: S1, collecting a high-frame-rate video, and recording collection parameters in real time; s2, constructing a Gaussian pyramid, constructing a Laplacian pyramid through adjacent layer image difference of the Gaussian pyramid, and decomposing the collected video into different spatial frequency bands; s3, designing a band-pass filter to extract a specific frequency band where the equipment vibration signal is located, and enhancing and reconstructing the micro vibration signal; s4, carrying out region selection from the enhanced image frame, calculating an optical flow in a selected region through an optical flow method, and extracting a characteristic frequency of vibration; and S5, performing data visualization, and generating a vibration signal image in real time to display the motion characteristics of the target area. According to the invention, the problems of insufficient sensitivity and poor real-time performance of small vibration detection of equipment in a traditional vibration monitoring method can be solved.

The invention relates to the technical field of fault diagnosis, in particular to a sun gear fault tooth positioning method based on combination of rotor sensing and tidal period effect, which comprises the following steps of: fixing a sensor module on an input shaft of a planetary gear box through a thermocouple adhesive, establishing a reference frame of a fixed shaft system and a rotating coordinate system, collecting radial vibration signals, and determining the radial vibration signals; mathematical modeling analysis is carried out on the collected radial vibration signals, and low-frequency components of the vibration signals are extracted by using a low-pass filter and can be used as absolute phase reference signals; the method comprises the following steps: performing time domain compensation on a meshing event of a sun gear and a single planetary gear by calculating meshing dynamic excitation time offset of the sun gear and simplifying a gearbox model, and ensuring the integrity of the single-tooth meshing times of the sun gear in a complete meshing period, so as to accurately analyze the meshing characteristics of each single tooth of the sun gear and the planetary gear; a sun gear fault working condition is simulated through an experiment, and periodic change of fault tooth meshing is analyzed; deterministic components and random components in the vibration signals are separated through cepstrum analysis; a band-pass filter is used for extracting gear meshing components from deterministic components; a minimum entropy deconvolution filtering technology and a square envelope technology are used for carrying out fault feature enhancement on random components; finally, absolute phase reference provided by gravitational acceleration of a rotor perception sensor is used, and a tidal period effect is combined; and calculating a single-tooth meshing frequency code of the fault tooth lag absolute phase reference point, and determining the position of the fault tooth by using different codes corresponding to different fault positions. The complexity of the monitoring system is effectively reduced, the influence of monitoring equipment on the operation of the planetary gear box is reduced, and the fault positioning accuracy of the sun gear is effectively improved.

An apparatus, including: a first antenna port; a first set of one or more band filters coupled to the first antenna port; a first set of one or more low noise amplifiers (LNAs) coupled to the first set of one or more band filters, respectively; a second antenna port; a second band filter; a second low noise amplifier (LNA); a first switching device coupled between the second antenna port and the second LNA; and a second switching device coupled between the second antenna port and the second band filter.

The present disclosure provides a microwave transmission method and a single-input multiple-output waveguide microwave system based on frequency control, an electronic device. The method includes: adjusting frequency of an input microwave, each of different input microwaves with different frequencies being input microwave of the single-input multi-output waveguide microwave system; assigning the input microwave to a target output port among multiple output ports of the single-input multiple-output waveguide microwave system, according to the frequency of the input microwave; and performing microwave output through the target output port.

The invention discloses an underground target positioning method based on a rotary permanent magnet type magnetic beacon, and belongs to the field of navigation, guidance and control. According to the invention, the problem of low precision of an existing positioning method caused by attitude errors in an underground positioning scene is solved. The method specifically comprises the following steps of: 1, respectively placing four same rotary permanent magnet type magnetic beacons at four points with known spatial positions, and respectively rotating the four magnetic beacons around a fixed shaft at a set rotating speed; 2, placing a magnetic sensor at an underground target point, and collecting mixed alternating magnetic field data under a sensor coordinate system by using the magnetic sensor; step 3, filtering the acquired mixed alternating magnetic field data by using a designed band-pass filter to obtain an alternating magnetic field vector of each rotating permanent magnet type magnetic beacon at the underground target point; constructing a positioning model according to the alternating magnetic field vector; and 4, obtaining an estimated target point position according to the positioning model. The method can be applied to underground target positioning.

The embodiment of the invention provides a chip atomic clock based on a speed grating spectrum and an implementation method. Comprising a multi-frequency coherent laser source, a quarter-wave plate, an atomic gas chamber, a photoelectric detector, a band-pass filter, a microwave modulation and demodulation module, a crystal oscillator, a phase-locked loop module, a bias-tree module, a DC modulation and demodulation module and a servo control module. The multi-frequency coherent laser source is sequentially connected with the quarter-wave plate, the atomic gas chamber, the photoelectric detector and the band-pass filter, the first output end of the band-pass filter is sequentially connected with the microwave modulation and demodulation module, the crystal oscillator and the phase-locked loop module, and meanwhile the microwave modulation and demodulation module is connected with the phase-locked loop module. And the second output end of the band-pass filter is connected with the DC modulation-demodulation module and the servo control module in sequence. And the bias-tree module is connected with the servo control module and the phase-locked loop module and feeds back a coupled signal to the multi-frequency coherent laser source so as to complete whole clock locking. The atomic clock is used for achieving the effect of improving the spectral line signal-to-noise ratio.

The invention discloses a single-bit interference synthetic aperture radar data processing method based on a joint channel variable threshold, which relates to the technical field of signal processing, and comprises the following steps: firstly, setting a quantization threshold, and separating noise and useful signals in a frequency spectrum; then designing a band-pass filter to suppress quantization noise; finally, according to the strong correlation of adjacent pixel points of the radar image and the weak correlation of residual quantization noise, coherent accumulation is carried out on pixel energy, and the signal-to-noise ratio is improved; according to the single-bit interferometric synthetic aperture radar data processing method based on the joint channel variable threshold, the estimation precision of the interferometric phase can be improved, so that a high-quality ground object digital elevation image is obtained.

The invention discloses a non-contact heart rate estimation method and system based on multi-modal signal fusion, and relates to the technical field of image processing, and the method comprises the steps: positioning a region of interest in a face video, extracting HSV and Lab color space signals, and fusing the HSV and Lab color space signals; suppressing ambient light interference through background brightness compensation to obtain a color conversion signal and normalizing the color conversion signal; adjusting the bandwidth filtering signal of a band-pass filter by using the historical heart rate to generate an rPPG signal; performing time domain and frequency domain analysis on the rPPG signal, and performing weighted averaging by combining two results to obtain a heart rate estimation value; a historical data smoothing strategy is adopted to correct a heart rate estimation result to ensure accuracy. According to the method, high-precision non-contact heart rate estimation is realized through extraction and fusion of HSV and Lab color space signals, background brightness compensation, signal normalization and processing of human face video signals based on a historical heart rate adjustment band-pass filter.

The invention discloses an unbalanced load compensation method for a three-phase four-wire three-level converter. According to the method, a three-phase four-wire system three-level converter bridge arm voltage mathematical model is established based on sine carrier in-phase laminated modulation, and harmonic content analysis is completed; an SOGI-pro module is established (an error integration link is added at the input front end of a D axis of an SOGI filter, and D and Q axis second-order band-pass filters are transformed into third-order band-pass filters), so that the positive and negative sequence separation precision of three-phase unbalanced load voltage is improved. According to the method, the order of the SOGI filter is improved by reasonably designing a closed-loop transfer function, and the filtering effect of the SOGI filter in high and low frequency bands is enhanced. And a sequence-dividing imbalance compensation control loop is designed based on the three-sequence dq0 coordinate system, so that zero-static-error tracking of a positive-sequence fundamental component and powerful suppression of negative-sequence and zero-sequence imbalance components are realized. According to the invention, the accuracy of traditional positive and negative sequence separation is improved, so that the unbalanced load compensation effect under sequence separation control can be improved.

The invention discloses a correlation analysis-based magnetic suspension rotor system on-line time-lag identification method, which comprises the following steps of: generating a sine excitation signal through an excitation signal generator to excite a magnetic suspension rotor system, collecting a control voltage and a displacement signal, and introducing the control voltage and the displacement signal into a cross-correlation time-lag identifier to carry out time-lag identification. The time-delay identifier is composed of a band-pass filter, a conversion transfer function, a data storage module and a cross-correlation time-delay identification operation module. Voltage and displacement signals which are introduced into the cross-correlation time-lag identifier are firstly filtered through a band-pass filter and then converted into homologous signals through a conversion transfer function, then data storage and iteration are carried out by utilizing a data storage module, and finally the required time-lag amount is identified by utilizing a cross-correlation operation module. According to the method, the advantage that the magnetic suspension rotor system is active and controllable is utilized, extra testing equipment does not need to be used, the structure is simple, few computing resources are occupied, time delay information in the system can be obtained online, and time delay identification of the magnetic suspension rotor system is achieved.

The invention provides a multi-antenna switching system and a control method. The system comprises a radio frequency interface module, a single-pole double-throw switch module, a single-pole three-throw switch module, a coupler, a band-pass filter, a power amplification module, a power detection module and a control module. The method comprises the following steps: controlling a current working antenna, and collecting a real-time performance data set of each group of antennas; evaluating and comparing all the antenna groups, and screening out a target antenna group; and judging whether the current working antenna and the target antenna group are the same group or not to perform antenna switching to obtain a new antenna group, and continuously monitoring the performance change of the new antenna group. According to the invention, the automatic selection and adaptive switching of the optimal antenna of the communication equipment under the multi-antenna condition are realized, the signal quality and stability are greatly improved, manual intervention is avoided, the self-healing and adaptive capabilities of the equipment are improved, the dynamic complex change of a network environment is supported, and the method can be widely applied to scenes such as 5G, Internet of Things, wireless communication and mobile terminals.