1044results about "Digital technique network" patented technology

The invention relates to the technical field of water resource analysis, and discloses a water resource predictive analysis method based on artificial intelligence. The method relates to the technical field of water resource analysis, and comprises the following steps: acquiring an original hydrological data set including rainfall intensity, river flow and the like through a sensing terminal, and performing multi-modal data alignment to generate a hydrological space-time tensor; constructing a dynamic water level threshold response mechanism in combination with watershed topographic features to obtain a partition water level calibration matrix; inputting the hydrological feature map into a spatial-temporal feature coupling network containing a long-short-term memory module and a spatial self-attention module to generate a hydrological feature map; constructing a multi-dimensional abnormal association tensor based on the multi-dimensional abnormal association tensor, and identifying rainfall flood event nodes by using an adaptive sliding window detection algorithm; and an optimal hydrological parameter set is obtained through genetic algorithm optimization, and the three-dimensional hydrological dynamic model is driven to establish a mapping relation chain. The method can effectively fuse hydrological data spatio-temporal characteristics, and improves the accuracy and efficiency of water resource prediction analysis.

A GNSS positioning slowly-varying fault detection method based on residual-SVR regression comprises the steps that an observation information sequence is acquired based on a Kalman filter, and a covariance matrix of the observation information sequence is calculated; accumulating multi-step information through a sliding window, and constructing chi-square statistics; based on the fault-free data, constructing a training set by taking an innovation sequence as input and chi-square statistics as output, and generating an innovation-statistics mapping function; and fitting a normal slope threshold value based on an SVR predicted value, carrying out least square fitting on an observation statistic curve by sliding a window in real time, and judging whether to start a slow change fault alarm or not. According to the method, the residual error sequence is directly used as model input, and the dynamic chi-square statistical magnitude is used for replacing a traditional dichotomy label, so that the detection delay is reduced; an SVR detection model based on grid search and cross validation collaborative optimization is utilized, and an optimal parameter combination of a minimum mean square error (MSE) is screened through logarithm uniform sampling, interval linear sampling and five-fold cross validation, so that the average absolute error of slowly varying fault detection is reduced.

The invention discloses a multichannel electrophysiological signal acquisition system and an acquisition method thereof, and the multichannel electrophysiological signal acquisition system comprises a power supply module electrically connected with a controller, an analog front-end chipset, a filter module and an analog-to-digital conversion module; the analog front-end chip set is used for acquiring an analog signal and preprocessing the analog signal; the pre-processed analog signal is converted into a digital signal through a filter module and an analog-to-digital conversion module, and the digital signal is transmitted to a controller; the filter module is used for filtering and denoising; the timer module connected with the controller generates a sampling frequency, transmits the sampling frequency to the analog-to-digital conversion module, and provides a time sequence signal for the analog-to-digital conversion module. The invention discloses a multi-channel electrophysiological signal acquisition system, which solves the problem of synchronous sampling time sequence control of a high-density electrode array and eliminates signal phase deviation caused by clock jitter among multiple channels under the constraint of maintaining the total power consumption of the system. And real-time power frequency interference suppression is realized.

The invention relates to the technical field of narrow-band filters, and discloses an ultra-low power consumption narrow-band filter implementation method based on a digital phased array system, and the method comprises the following steps: S1, collecting input signal data, carrying out the adaptive preprocessing, and generating preprocessed signal data; s2, performing digital beam forming processing based on the preprocessed signal data to generate digital beam forming data; s3, performing narrowband filtering parameter matching processing according to the digital beam forming data to generate narrowband filtering parameter data; in the narrowband filtering processing process, disturbance of environmental electromagnetic interference to a target signal is identified and eliminated in real time through adaptive noise suppression and a multi-dimensional signal preprocessing mechanism, so that the system can guarantee the pointing precision of digital beam forming, the pointing offset problem in the space signal capturing process is avoided, the accuracy of narrowband signal extraction is improved, and the accuracy of narrowband signal extraction is improved. And the reliability of filtering output and the signal fidelity are enhanced.

The invention discloses a wide-range weak feature scene measurement system based on multi-sensor fusion and structured light scanning, and relates to the technical field of wide-range scene scanning, in the system, an extended Kalman filtering algorithm is adopted, fusion is carried out based on positioning data provided by an inertial measurement module and a positioning sensing module, and a wide-range weak feature scene is obtained. And the distance measurement information provided by the laser distance measurement module is combined to correct the fused positioning data, so that the precision and robustness of subsequent point cloud registration are ensured. Then, according to position information and attitude information of the binocular structured light scanning camera during scene scanning, calculating a relative rotation matrix and a relative displacement matrix of each frame of scanning point cloud data relative to the first frame of scanning point cloud data, and performing coarse registration; in the coarse registration process, all frames of point clouds can be converted into a unified coordinate system by directly utilizing global pose information, and the efficiency of coarse registration is greatly improved. And finally, extracting laser marking point clouds projected by the non-contact laser marking device in each frame of scanning point cloud data, and performing iterative precise registration on each frame of scanning point cloud data by using color features and geometric distribution rules of the extracted laser marking point clouds. In conclusion, high-precision, high-efficiency and high-robustness point cloud registration in a large-scale weak feature scene is realized, and the method can be used for realizing high-precision non-contact measurement.

The invention relates to the technical field of ground resistance detection, in particular to a single-core cable ground resistance detection method capable of resisting strong power frequency interference. High-frequency signals are injected in a non-contact mode through a coupling type capacitor clamp, background voltage and current signals are collected firstly, and injection frequency far away from power frequency and harmonic waves is selected through Fourier analysis; cancelling background noise by adopting a normalized least mean square adaptive filter to generate an enhanced signal; the signal is down-converted to a base band through digital quadrature demodulation, a Kalman filter estimates the amplitude and the phase in real time, and the state and noise parameters are periodically calibrated through a compressed sensing algorithm; and finally, loop impedance is calculated according to the voltage and current amplitudes and the phase difference to obtain grounding resistance. The method has the advantages of being non-contact, high in safety, strong in anti-interference capability, high in measurement precision and the like, and is suitable for monitoring the grounding state of the cable in a complex electromagnetic environment.

The invention relates to the technical field of equipment full-life-cycle management, in particular to an equipment full-life-cycle tracing and management and control system based on digital threads. Comprising a digital thread generation unit which is used for generating a dynamic digital thread penetrating through the whole life cycle of technical improvement purchasing, operation maintenance and decommissioning of equipment; a full life cycle data integration unit; and a business process management and control unit. According to the method, a dynamic digital thread which runs through the whole life cycle of technical improvement purchasing, operation overhaul and decommissioning of equipment is constructed, and a multi-dimensional data anchoring algorithm fused with weighted Bayesian estimation is combined, so that probabilistic association matching between heterogeneous physical data in each stage and a corresponding physical scene is realized; and a unique device identifier is bound to form dynamic association of physical state-data record-time node, so that the problems of fragmentation of data in the whole life cycle of the device and lack of association between the data and a physical scene in the prior art are solved.

The invention discloses an interactive multi-model underwater maneuvering target tracking method and system based on a pure azimuth second-order EKF. The method comprises the following steps: establishing a discrete state space model of a pure azimuth target tracking system; performing second-order linearization on the pure azimuth measurement model; calculating mixed input of a sub-filter corresponding to each model in the model set of the interactive multi-model algorithm; estimating a target state through parallel filtering of the azimuth-pure second-order EKF sub-filter corresponding to each model in the model set; updating the probability of each model in the model set; and combining the estimation results of all the sub-filters to obtain a final estimation result of the target state. According to the method, the target tracking precision can be improved, the problem of highly nonlinear measurement of the UUV on a target detection and tracking system through a passive sonar is effectively solved, good real-time performance is achieved, and real-time tracking of the UUV on the motion state of the underwater maneuvering target is achieved through adaptive matching of the real motion of the target through the interactive multi-model algorithm.

The invention relates to a house building construction stage carbon emission dynamic estimation method and system based on full life cycle data, and the method comprises the steps: dividing a construction region based on a BIM model, laying a multi-source sensor network, fusing static BIM data and a dynamic Internet of Things monitoring flow, building a four-dimensional space-time label data set, and carrying out the construction stage carbon emission dynamic estimation based on a double-layer dynamic correction model. Kalman filtering is utilized to eliminate instantaneous interference, LSTM transfer learning is combined to predict mechanical efficiency attenuation, a dynamic correction coefficient matrix of a mechanical aging rate, operator skills and environmental factors is embedded, and a carbon emission value is calibrated in real time; when abnormal emission is detected, a key pollution source is traced and positioned through a graph neural network, a three-dimensional thermodynamic diagram is generated in the digital twinborn model, and component-level carbon flow analysis and early warning are performed, so that the carbon emission estimation precision is remarkably improved, the abnormal traceability time consumption is shortened, and the timeliness is remarkably improved.

The invention relates to the technical field of charging pile operation and maintenance systems, and particularly discloses a charging pile operation unmanned inspection and automatic operation and maintenance system which comprises a data acquisition module, a state initial judgment module, a fault diagnosis module and an automatic operation and maintenance module. An unmanned three-dimensional inspection network is constructed through an unmanned aerial vehicle and an Internet of Things sensor, accurate fault diagnosis is realized in combination with multi-modal feature fusion, a dynamic operation and maintenance priority is generated and a differential strategy is formulated based on a machine learning model, and a complete operation and maintenance closed loop of acquisition, diagnosis, execution, feedback and optimization is formed at the same time. According to the method, the inspection real-time performance and the fault recognition accuracy are greatly improved, the operation and maintenance resource configuration efficiency is optimized, the operation and maintenance cost is reduced, the equipment downtime can be shortened, the charging experience of a user is improved, the operation and maintenance capability can be continuously iteratively optimized through data accumulation, and powerful support is provided for stable and reliable operation of a charging pile network.

The invention relates to the technical field of data processing, in particular to a multi-channel controllable power converter for realizing filtering processing and a filtering processing method, and the method comprises the steps: obtaining the signal delay time and voltage signal data of the multi-channel controllable power converter in a current monitoring time period and a historical monitoring time period; according to peak value distribution and frequency distribution of the voltage signal data in each historical monitoring time period, analyzing a noise interference degree, and combining the noise interference degree and the difference of a pulse width parameter change trend to obtain a synchronization characteristic index; according to the signal delay time of the current monitoring time period and the historical monitoring time period, combining the synchronization characteristic index to obtain a filtering weight; and decomposing the voltage signal data in the current monitoring time period according to the filtering weight, and filtering in combination with Gaussian characteristics of decomposed signal components to obtain filtered voltage signal data. The filtering processing result has a good processing effect, and the stability of power supply output is ensured.

The invention relates to the field of transaction anti-fraud, and discloses a real-time transaction anti-fraud system based on a multi-modal behavior atlas, and the system comprises an acquisition processing module which is used for obtaining time sequence data of equipment, transaction and geographic modals and carrying out the preprocessing of the time sequence data, and obtaining the processed data; the multi-mode construction module is used for calculating the time-varying fluctuation rate of a transaction mode, the local dispersion degree of an equipment mode and the trajectory bending degree of a geographic mode, and constructing the processing data into random manifold features containing a Riemannian metric tensor; and the cross-modal interaction module is used for modeling a time-varying driving relation between random manifold characteristics based on a stochastic differential equation and a Poisson process. The method comprises the following steps: converting equipment, transaction and geographic data into random manifold features containing Riemannian metric tensor, reserving nonlinear time sequence association of multi-modal data, and describing a random drive of'equipment motion-geographic trajectory 'and a time-varying trigger relationship of'transaction-equipment activity' through a stochastic differential equation and a Poisson process.

The invention belongs to the technical field of multivariable measurement and data analysis, and relates to a multi-source data joint measurement and analysis method based on a physical consistency relationship, which comprises the following steps of: 1, acquiring and preprocessing multi-source data; 2, modeling physical characteristics; 3, constructing a physical consistency relationship; 4, multi-source joint feature extraction; 5, carrying out consistency evaluation and abnormity identification; and 6, result fusion and dynamic updating. According to the method, collaborative analysis and consistency feature extraction of different types of measurement signals are realized by establishing a physical constraint model among multi-source sensor data, so that the reliability and precision of a multivariable measurement system are improved, the robustness of the system to measurement errors, noise and abnormity under complex working conditions is effectively enhanced, and the measurement accuracy of the system is improved. The method is suitable for the fields of intelligent driving, industrial monitoring, multi-sensor fusion measurement and the like.

The invention discloses a mixing parameter regulation and control method and system for an SBS-T modified asphalt mixture and a terminal. The method comprises the following steps: analyzing a modification mechanism through a scanning electron microscope and X-ray photoelectron spectroscopy combined technology, dividing three stages of rapid melting and the like, and establishing a temperature-viscosity model; constructing a multi-scale capture system by using an atomic force microscope, a Fourier transform infrared spectrum and a dynamic shear rheometer; designing a five-factor three-level test matrix by adopting a response surface method, and establishing a road performance prediction model in combination with a BP neural network; mixing parameters are optimized in a multi-objective mode based on a genetic algorithm, and dynamic correction is achieved through an Internet of Things sensor and Kalman filtering. The system comprises a mechanism analysis module, a multi-scale detection module, a terminal integrated storage unit, a processing unit and a man-machine interaction unit. According to the scheme, the limitation of traditional single-factor analysis is broken through, microscopic and macroscopic collaborative optimization and dynamic parameter regulation and control are achieved, and the construction adaptability and precision are improved.

The invention provides a continuous time linear equalizer based on a low-pass and band-pass mixed structure. The continuous time linear equalizer comprises a frequency selection coupler, a low-pass transconductance unit, a band-pass transconductance unit and a load unit. The frequency selection coupler is used for separating the differential analog signal into a first voltage component in a first band-pass frequency range and a second voltage component in a low-pass frequency range, the first band-pass frequency range comprises a target frequency expected to be compensated, and the frequency in the first band-pass frequency range is greater than the frequency in the low-pass frequency range; the band-pass transconductance unit is used for converting the first voltage component into current and synchronously realizing gain amplification to obtain a first current signal; the low-pass transconductance unit is used for converting the second voltage component into current and synchronously realizing gain amplification to obtain a second current signal; the load unit is used for summing the first current signal and the second current signal and converting the sum to a differential output voltage signal. According to the invention, the frequency corresponding to the gain peak point and the gain amplitude can be improved.

The invention relates to the technical field of data processing, in particular to a coal mine environment data monitoring method and system based on the Internet of Things, and the method comprises the steps: obtaining an environment data sequence of each type of sensors in a coal mine; constructing a target window for any type of sensors, obtaining a covariance matrix through a Kalman filtering algorithm, and obtaining the data change degree of the target window; any type of sensors in a coal mine serve as target sensors, the overall window similarity is obtained, window length adjustment is conducted on target windows corresponding to the target sensors, a new target window is obtained, a preset number of sliding windows are constructed, and according to data of the new target window and data of each sliding window, a preset number of sliding windows are obtained. The sampling frequency of the target sensor at the current moment is adjusted to obtain the self-adaptive sampling frequency of the target sensor at the future moment, so that the self-adaptive sampling frequency of the target sensor at the future moment is more adaptive to change characteristics of different environmental factors, and the requirement for efficient and intelligent monitoring of coal mine environmental data is met.

The invention discloses a carbon emission checking method and system based on a multi-mode inversion model, and relates to the technical field of carbon emission checking. Air-based monitoring, foundation monitoring, mobile monitoring and maneuvering monitoring are adopted to form a three-dimensional monitoring network; the intelligent inversion calculation layer fuses global background concentration and regional real-time monitoring data, and adopts a GSI 4DVar algorithm to optimize a three-dimensional concentration field; in the first inversion stage, random disturbance is applied to the prior emission list, multiple emission sets are generated, each emission set corresponds to a grid area of a three-dimensional concentration field, and concentration distribution is simulated through a WRF-CMAQ model; in the second inversion stage, an EnSRF algorithm is adopted to assimilate measured data, and emission parameters are iteratively optimized; according to the invention, various monitoring means, advanced algorithms and data analysis methods are organically integrated, and automation and intelligentization of the whole process from data acquisition, processing and analysis to abnormity determination are realized. The method provides efficient and scientific technical support for carbon emission supervision, and is helpful for promoting the realization of carbon emission fine management and energy conservation and emission reduction targets.

The invention relates to the technical field of electronic circuits, in particular to a filter circuit, a voltage filter control circuit, a chip and electronic equipment. The filter circuit comprises a counter, a first data selector, a digital operation circuit and a register, the counter is used for receiving the counting enable signal, outputting a counting mark value to the first data selector, determining a corresponding current logic operation mode according to the current counting mark value, and performing logic operation on the intermediate input parameter according to the current logic operation mode to obtain a first voltage error value after filtering processing; by adopting the filter circuit provided by the invention, required logical operation can be completed by virtue of the first data selector and the digital operation circuit, so that the first voltage error value is output, and the filtered voltage signal is adjusted according to the first voltage error value, so that the set frequency component in the output voltage signal is filtered out; in this way, complex filter coefficients do not need to be configured, a processor with higher computing power does not need to be used, and hardware cost is saved.

The invention discloses a time-frequency analysis method and system for non-stationary signals of periodic pulses, and the method comprises the following steps: S1, carrying out the preprocessing of a vibration signal through a rapid CMSP method, and obtaining a periodic pulse component in the vibration signal; s2, carrying out iterative estimation on group delay by utilizing fixed point iteration; s3, utilizing iteration group delay estimation, and redistributing time-frequency coefficients of the STFT through time rearrangement multiple times of synchronous extrusion transformation; s4, performing integration on a time rearrangement multiple-time synchronous extrusion transformation result along a time direction so as to reconstruct the signal; according to the method, the problem that STFT time-frequency representation is fuzzy is solved through a fixed point iterative algorithm, meanwhile, signal reconstruction can be achieved, synchronous extrusion operation is carried out through iterative group delay estimation, an estimated value is closer to real group delay, divergent time-frequency coefficients in STFT after FC processing are redistributed, and the estimation accuracy is improved. Therefore, the energy concentration degree of time-frequency representation is improved.

An apparatus for calibrating a digital filter to replicate a transfer function of a signal processing device comprising a detector with a first input to receive a first signal; a second input to receive a response signal of the signal processing device to the first signal; a signal modification block; a comparison block and a decimation block; wherein the comparison-block compares a phase and amplitude of the first signal after a correction has been applied by the signal modification block and decimation has been applied by the decimation block; and a feedback loop; wherein detector is configured to determine at least a feedback control signal at a first frequency and a second frequency, different to the first frequency and determine calibration information for programming of the transfer function of said digital filter.

The invention provides an ultrasonic water meter flow measurement data processing method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining ultrasonic signals in a downstream direction and a countercurrent direction, and respectively forming a first time domain signal and a second time domain signal; performing window function windowing and framing processing on the two time domain signals to obtain a corresponding signal frame sequence; respectively executing Fourier transform and frequency domain filtering, and recovering the first time domain signal frame sequence and the second time domain signal frame sequence through inverse transformation; splicing the recovered frame sequence, and analyzing and extracting a propagation time difference through a cross-correlation function; calculating the flow velocity according to the propagation time difference, and obtaining the water flow in combination with the pipeline cross-sectional area. Thus, the most probable propagation time difference is extracted through the cross-correlation peak value, the signal quality is enhanced in combination with frequency domain filtering, and the anti-interference performance and the overall precision of flow velocity measurement can be effectively improved.

The invention relates to the technical field of radio frequency signal processing, and discloses a digital filtering repair method and system for signal distortion, and the method comprises the steps: obtaining a frequency domain amplitude-frequency response and a phase response; constructing a phase compensation amount by adopting piecewise polynomial fitting and a phase inversion mechanism; a complex number logarithm domain mapping mechanism is adopted to execute composite frequency response inversion; constructing a switchable hybrid digital filter with an amplitude path and a phase path coupled in parallel; multi-band adaptive scheduling is executed; and outputting the radio frequency baseband signal stream. The technical problems that in the prior art, frequency response nonlinear distortion in a broadband range cannot be dealt with by adopting a fixed template or a single-path filter, and particularly, a high-precision and low-delay dynamic compensation effect cannot be realized in a scene that multi-band coupling interference exists in a radio frequency ADC channel with the bandwidth exceeding 800MHz are solved. Due to the fact that the switchable hybrid digital filter is constructed, accurate modeling and flexible recovery of distortion characteristics in broadband signals are achieved.

The invention relates to a method and device for judging whether a grounding mechanism of a switch cabinet works normally or not, a grounding resistance online measurement module is arranged on a grounding knife switch structure of the switch cabinet, the resistance value of the grounding resistance is detected in real time, and whether grounding is correct or not is judged by judging whether the grounding resistance is in a normal range or not; the grounding resistance on-line measurement module is internally provided with a switch-on grounding state detection algorithm based on deep fusion of a neural network and Kalman filtering. According to the method, multiple factors such as the cumulative closing times, the contact resistance change rate, the oxidation coefficient, meteorological interference and the temperature are comprehensively considered, a dual-network self-adaptive modeling and federated Kalman filtering framework is adopted, high robustness and nonlinear processing capacity are achieved, and whether the switch cabinet grounding mechanism works normally or not is judged with high accuracy.

There is provided a phase shifter circuit of an optical encoder. The phase shifter circuit receives a first signal, a second signal, a third signal and a fourth signal sequentially having a 90-degree phase shift, and includes a first cascaded resistor string, a second cascaded resistor string, a third cascaded resistor string and a fourth cascaded resistor string. The first, second, third and fourth cascaded resistor strings respectively delay the first, third, second and fourth signals by selecting a switch connected at a tap-out node of the first, second, third and fourth cascaded resistor strings to correct phase deviations between incremental signals and an index signal and / or between incremental signals.

The invention provides a control system for suppressing peak of output voltage and current of a power amplifier. The system comprises a PS signal processing module, a PL signal processing module and a high-voltage power circuit, wherein the PS is configured to receive a bus signal issued by an upper computer, execute digital Gaussian filtering processing on the bus signal and then transmit the bus signal to the PL signal processing module; meanwhile, relevant data of the power amplifier are collected and uploaded; the PL signal processing module is configured to receive a signal which is issued by the PS and is subjected to digital Gaussian filtering processing, and pre-process the signal; and transmitting the processed signal to a high-voltage power circuit to control the high-voltage power circuit to execute power conversion operation on the load. According to the method provided by the invention, smooth transition is realized at the phase jump position of the signal by adjusting the parameters of the digital Gaussian filter, so that the peak of the output voltage and current of the power amplifier is inhibited, the stress of a post-stage high-voltage power circuit device is reduced, the post-stage output power is effectively improved, and the stability of the power amplifier is improved.

The invention discloses a crystal oscillator taming system based on Kalman filtering and adaptive PID, and relates to the technical field of time-frequency equipment. Comprising a crystal oscillator time frequency module used for generating a local time frequency signal, a reference module used for receiving an external reference time frequency signal, an error measurement module used for measuring the phase deviation between the local time frequency signal and the reference time frequency signal, and a Kalman filtering estimation module used for performing Kalman filtering estimation based on the phase deviation. The Kalman filtering module is used for outputting phase deviation estimation and covariance estimation and adaptively adjusting PID parameters according to the phase deviation estimation, the position deviation estimation and the covariance estimation; the control feedback module is used for superposing the voltage-controlled voltage adjustment quantity to the crystal oscillator time frequency module to adjust the output frequency of the crystal oscillator; according to the method, the crystal oscillator taming parameters are dynamically adjusted through Kalman filtering in combination with self-adaptive PID, high-precision and robust taming of the crystal oscillator is achieved, and the long-term frequency stability and the time synchronization precision of the crystal oscillator are improved.

The invention discloses an FIR filter circuit structure, and the structure comprises a path control unit which generates a first control signal and a second control signal according to the number and order of filters which are customized by a user; the routing unit correspondingly transmits the filtering data received by the filtering data channel unit to the multiply-add unit array based on the first control signal; the multiply-add unit array comprises N multiply-add units, and the multiply-add units are connected through data selectors; the path control register unit is connected with a selection port of the data selector, and the path control register unit controls a data path of the multiply-add unit array through the data selector based on a second control signal; and the filtering result operation unit adds the multiplication and addition results of the corresponding multiplication and addition unit to obtain the filtering result of the corresponding filter. According to the invention, the multiplication and addition unit structure of the filter circuit can be customized according to user requirements, and the FIR filter circuit with low circuit resource ratio and high operation speed is configured.

The invention discloses a radar system clutter background modeling and adaptive suppression method and system, and relates to the technical field of radar signal target detection. The radar system clutter background modeling and adaptive suppression method comprises the following steps of covariance matrix construction, clutter model construction, clutter adaptive suppression and adaptive suppression processing optimization. According to the method, covariance matrix stability evaluation is carried out through the constructed covariance matrix, whether covariance matrix correction is carried out is judged, then the initial clutter model is established according to the covariance matrix and the preset probability distribution model, then clutter model adaptability evaluation is carried out, whether clutter model optimization is carried out is judged, and clutter model optimization is carried out. According to the method, the radar signal is subjected to self-adaptive suppression processing, and finally the judgment result of self-adaptive suppression processing optimization is obtained based on the signal-to-noise ratio of the radar signal after self-adaptive suppression processing, so that the clutter suppression effect in the radar signal is improved, and the problem of poor clutter suppression effect in the radar signal in the prior art is solved.

The invention relates to the technical field of servo control, in particular to a servo driving current harmonic compensation method and system for electromagnetic interference suppression. The method comprises the following steps: extracting common-mode and differential-mode interference by using current and voltage sampling and combining differential measurement, and configuring a multi-stage passive filter according to spectrum characteristics to construct a suppression channel; establishing a digital interference cancellation mechanism, generating a reverse compensation signal by adopting self-adaptive trapped wave and a DSP (Digital Signal Processor), and injecting the reverse compensation signal into a control loop to form a software-defined multi-channel suppression architecture; after interference suppression, a high-order tensor model is constructed for the purified three-phase current, and an alternating least square method is adopted for decomposition so as to separate multi-band harmonic waves; a graph neural network is introduced, harmonic coupling is represented, and dominant and residual harmonic decoupling is realized through message passing; according to a grading progressive strategy, dominant harmonic waves are firstly subjected to coarse compensation, then residual harmonic waves are finely adjusted, and a compensation sequence is adaptively optimized through iterative feedback, so that high-robustness closed-loop control of servo driving is realized.

The invention discloses a lithium battery broadband impedance online measurement system and method without an additional circuit, and relates to the technical field of lithium battery state monitoring. The system comprises a power DC-DC converter, a driving circuit, a sampling module and a digital controller, the digital controller comprises a converter control module and an impedance calculation and output module, the output end of the driving circuit is connected with the control end of a switching device of the power DC-DC converter, and the output end of the power DC-DC converter is connected with the input end of the sampling module. The output end of the sampling module is connected with the input end of the converter control module and the input end of the impedance calculation and output module. The output end of the converter control module is connected with the input end of the drive circuit. According to the invention, no extra hardware circuit is needed, and online, high-precision and low-cost measurement of the broadband impedance of the lithium battery is realized.