948 results about "Frequency detection" patented technology

The invention relates to the field of chip packaging testing, in particular to a BGA chip packaging testing method. The method comprises the following steps: carrying out full-flow thermal imaging scanning on a BGA chip packaging process, carrying out space temperature gradient diffusion distribution analysis, and constructing a temperature diffusion distribution map of each region; according to the probe array, acoustic scanning is carried out on the BGA chip solder ball contact surface, abnormal frequency detection is carried out, and abnormal acoustic nodes are marked; performing transient temperature mutation detection and potential packaging defect positioning analysis on the temperature diffusion distribution map based on abnormal acoustic nodes, and extracting a potential packaging defect area; and carrying out multi-threshold micro-vibration excitation on the potential packaging defect area, carrying out comprehensive evaluation on the reliability of the defect area structure, and generating a reliability evaluation report of the solder ball contact surface structure. According to the invention, accurate packaging test failure prediction is realized, packaging process parameters are optimized, and chip packaging quality and stability are improved.

The invention provides a multi-parameter MIMO (Multiple Input Multiple Output) aviation time-frequency detection system and method, which can be applied to the technical field of underground medium detection. The system comprises a flying platform, a transmitting subsystem, a receiving subsystem and a measurement and control subsystem, and the transmitting subsystem is configured to load a first current pulse into a transmitting coil through a first current transmitter to achieve primary electromagnetic field excitation and load a second current pulse into a compensation coil through a second current transmitter to achieve secondary electromagnetic field excitation. Compensation electromagnetic field excitation is realized; the receiving subsystem is configured to be used for sampling the first current pulse and the second current pulse and collecting secondary electromagnetic field response to obtain underground medium electrical information of the target detection area; and the measurement and control subsystem is configured to send a control instruction to the transmitting subsystem and the receiving subsystem according to a sampling result and set detection parameters and monitor the working state of the detection system, and the measurement and control subsystem adjusts the first current pulse and the second current pulse in real time.

The invention relates to the technical field of vehicle safety monitoring, and discloses a non-contact type in-vehicle driver respiratory rate detection method and device. Physiological signal data are collected through a millimeter wave radar, infrared thermal imaging and a microphone array, breathing frequency band signals are extracted through self-adaptive wavelet transform, and breathing signal waveforms are reconstructed through time-frequency joint analysis. A model formed by combining a multi-channel convolutional neural network and a bidirectional gating circulation unit is adopted to extract a respiratory rhythm feature vector, interference is eliminated based on a dynamic time warping algorithm, and a respiratory frequency value is estimated by applying methods such as variational mode decomposition. And processing abnormal points and missing data through a sliding window mechanism, and outputting a stable monitoring result. The invention further provides a sensor data synchronous calibration and model online updating method. According to the invention, the breathing frequency can be detected with high precision in a complex in-vehicle environment, and the safety and intelligent level of the vehicle are improved.

The invention provides a clock signal generating circuit, a wired communication transceiver and electronic equipment, and the circuit outputs a first DC voltage comprising phase difference information and frequency difference information of a reference clock signal and a feedback clock signal through a phase frequency detection module. The pulse generator generates a narrow pulse signal based on the DC voltage and a reference clock signal, the oscillation frequency of each secondary ring oscillator in the cross-coupled ring oscillator is controlled by the first DC voltage, and the cross-coupled loop performs synchronous coupling and phase sequence adjustment processing on each secondary ring oscillator. One output node in the cross coupling ring oscillator receives the narrow pulse signal, frequency and phase locking is completed in an injection locking mode, and the frequency divider is used for conducting frequency division processing on any high-frequency clock signal and outputting a feedback clock signal. Therefore, a high-frequency multi-phase clock signal with low phase noise and high phase precision can be generated by using the low-frequency reference clock signal.

The invention discloses a quadruped inspection robot space positioning method and system based on gravity center sensing, and aims to construct a gravity center potential energy field through foot end contact force and body attitude information, form a gravity center disturbance mode in combination with fluctuation spectrum analysis, and reveal a disturbance propagation mechanism. A reverse compensation technology is adopted to generate an anti-disturbance sequence, a foot end force distribution topology is reconstructed, and active disturbance suppression is achieved; a multi-frequency detection wave beam and coherent superposition technology is introduced, an environment hologram is generated, geometric topology is reconstructed, and a high-precision environment sensing system is established; high and low impedance regions are identified through energy density analysis, and an energy optimal path is constructed in combination with double strategies of potential field bypassing and streamline tracking; establishing an oscillation analysis space for path projection simulation, identifying resonance risk points and determining stabilization parameters; finally, a coordinate reference is generated by adopting a quantum entanglement type multi-anchor-point synchronization mechanism, accurate positioning is realized by fusing environmental geometric information, and a technical closed loop from gravity center dynamics analysis to environmental perception navigation is realized.

The invention discloses an unmanned aerial vehicle co-frequency resonance deicing device and a deicing method, and relates to the field of high-voltage overhead conductor deicing, an unmanned aerial vehicle device is provided with a deicing device, the deicing device comprises a microwave generator and an ultrasonic generator which are oppositely arranged, and a power transmission line is located between the microwave generator and the ultrasonic generator. Microwaves and ultrasonic waves emitted by the microwave generator and the ultrasonic generator face the power transmission line; the deicing device comprises a resonant frequency detection device, the resonant frequency detection device is used for obtaining the resonant frequency of the icing position of the power transmission line, the frequency of ultrasonic waves emitted by the ultrasonic generator is the same as the resonant frequency of the icing position of the power transmission line, and the frequency of microwaves emitted by the microwave generator is the same as the resonant frequency of the icing position of the power transmission line. The ice layer is cracked by utilizing high-frequency vibration heating generated by ultrasonic waves and microwaves, so that the purpose of removing the ice layer is achieved. According to the method, a power grid line does not need to be contacted, and line damage possibly caused by direct impact is avoided.

The invention relates to a phase-sensitive optical time domain reflectometer based on multi-frequency reference switching. Continuous laser generated by a continuous laser is divided into a local path and a detection path through an optical coupler; the local path is input to the polarization coherent receiving module, the detection path is incident to a light intensity modulator driven by the signal generation circuit module, and the light intensity modulator is converted into a multi-frequency pulse laser sequence with intensity modulation; the multi-frequency pulse laser sequence enters the sensing optical fiber to be measured through the optical circulator; generated Rayleigh backscattered light and local continuous laser are subjected to beat frequency coherent receiving in a polarization coherent receiving module through a circulator; and the signal acquisition circuit adopts a demodulation algorithm to compensate phase drift and sensitivity difference of detection pulse demodulation signals with different frequencies so as to realize dynamic strain sensing. Compared with the prior art, the phase drift and the sensitivity difference between the frequencies are extracted to realize the compensation of the interleaved signals, and the method does not depend on the fixed reference frequency, so that the robustness and the adaptability of the system in a complex environment are remarkably enhanced.

The invention provides a power grid frequency detection method, system and device and a medium, and the method comprises the steps: carrying out the narrowband signal decomposition of an obtained input voltage signal of a power grid through a null-space tracking algorithm, and obtaining a fundamental main mode component of the input voltage signal; performing low-pass processing on the fundamental wave main mode component to obtain a fundamental wave signal of the fundamental wave main mode component; performing discrete Fourier transform on the fundamental wave signal to obtain phase information of the fundamental wave signal; according to the phase information of the fundamental wave signal, calculating phase deviation information of the fundamental wave signal in pre-selected adjacent cyclic waves to obtain frequency estimation information of the power grid; according to the invention, narrow-band decomposition is carried out on an input voltage signal through a null-space tracking algorithm, so that a fundamental main mode can be accurately extracted; and phase deviation information can be determined based on discrete Fourier transform, so that when the interference frequency of the power grid is close to the fundamental frequency, high separation precision can be kept, and the accuracy of power grid frequency estimation can be improved.

The invention relates to an integrated microcavity optical comb repetition frequency and optical frequency locking device and method, and belongs to the technical field of integrated microcavity optical combs. The locking device comprises a pumping module, a power amplification module, a phase modulation module, an electro-optic driving module, an acousto-optic modulation module, an acousto-optic driving module, a band-pass filtering module, a micro-ring resonant cavity and a beam splitting module; the device comprises a soliton detection module, a control module, a repetition frequency detection module, a first feedback control module, an acetylene frequency stabilized laser, a beat frequency module, an optical frequency beat frequency detection module and a second feedback control module. The locking device can achieve full frequency locking of the microcavity optical comb, has the advantages of being high in frequency stability, wide in servo bandwidth, simple and compact in structure, tight in locking, low in noise, high in reliability and low in cost, and can provide a powerful tool for the field of precision measurement.

The invention relates to the technical field of frequency detection, in particular to a frequency measurement method and device based on Kalman filtering, electronic equipment and a storage medium, and the method comprises the steps: obtaining a posterior estimation value of frequency measurement data at a previous moment and an observation value at a current moment; calculating a prior estimation value at the current moment by using the posterior estimation value at the previous moment, calculating an observation error between the prior estimation value at the current moment and the observation value at the current moment, and judging whether the observation error is greater than a preset error threshold value or not; and if the observation error is greater than a preset error threshold value, updating the prior estimation value at the current moment by using a preset Kalman filter, and taking the updated prior estimation value at the current moment as an output value of the frequency measurement data at the current moment. Therefore, the problem that the frequency measurement requirements of complex signal processing, real-time monitoring and quick response to signal change are difficult to meet in the related technology is solved, accurate system state estimation can be provided, and the method has good real-time updating and signal processing capabilities.

The invention relates to a SiC crystal ingot facet detection method based on Raman combined with resistivity detection, which comprises the following steps: S1, providing a silicon carbide workpiece, acquiring resistivity rho k of different detection areas on the surface layer of the workpiece based on a preset resistivity detection scanning path, and further preliminarily screening out resistivity abnormal areas; s2, on the basis of a preset Raman detection scanning path, obtaining the edge area on the surface layer of the workpiece, the Raman characteristic peak frequency omega ij of different detection points of the resistivity abnormal area obtained in the S1, a detection image, and an XY coordinate position on an XY plane perpendicular to the height direction of the workpiece; and S3, based on a preset n-rho inverse proportion function model of the doping concentration n and the resistivity rho, and a delta omega-n linear model of the Raman frequency shift delta omega and the doping concentration n, determining and associating the XY coordinate positions of the S2 and the corresponding resistivity rho ij, and constructing a resistivity distribution diagram of the surface layer of the workpiece. The method has the advantages of small detection error and short detection time.

The invention discloses an identification and positioning method for power cable defects and short-circuit faults. The defect identification and positioning method comprises the following steps: establishing a power cable transmission line simulation model and a partial discharge simulation model by using electromagnetic transient simulation software; obtaining a partial discharge signal according to the power cable transmission line simulation model and the partial discharge simulation model, and identifying the partial discharge signal based on an SSA-BP algorithm; performing preliminary positioning on the power cable by adopting an ultrasonic, high-frequency and ultrahigh-frequency detection method; accurate positioning of power cable defects is realized through an infrared heat and sound wave positioning principle. According to the method, a simulation analysis method is adopted to obtain a sample, and then accurate identification of a cable fault is realized through a BP neural network (SSA-BP) optimized based on a sparrow search algorithm. And meanwhile, accurate cable fault positioning is realized aiming at different fault positions.

The invention relates to the technical field of information management, in particular to a smart agriculture precision big data information management system, which comprises a growth index extraction module, a stage data clustering module, a nutrient fluctuation identification module, an agricultural material strategy generation module and a scheduling information scheduling module. According to the method, the acceleration criterion is constructed based on the continuous period leaf area index change sequence, transition node identification is completed in combination with the photosynthetically active radiation utilization rate and the nitrogen absorption rate change trend, accurate positioning of crop growth stage change time points is achieved, the stability of stage classification in a space region is enhanced, and the accuracy of crop growth stage classification is improved. The agricultural material putting grade is judged and the fertilization frequency and dosage are blended by analyzing a root zone soil nutrient concentration difference value and a rate fluctuation frequency detection mode in combination with moisture content and root activity conditions, and operation period adjustment is guided in a task schedule in cooperation with a meteorological element fluctuation rate. The precision of farmland crop stage identification and the timeliness of nutrient fluctuation response are integrally improved.

The invention relates to the technical field of wireless communication, in particular to an OTA upgrading method and system for Bluetooth sound equipment. The method comprises the following steps: acquiring to-be-upgraded firmware data and currently played audio data, and acquiring power amplifier current feedback data of a sound speaker by sending a double-frequency detection signal containing 21kHz and 22kHz; acquiring equipment transmission capability confirmation data according to a silent response mode of the sound equipment to the preset handshake signal; and calculating a nonlinear distortion coefficient of the loudspeaker according to the intensity of the 1kHz difference frequency component in the power amplifier current feedback data, and obtaining real-time channel evaluation data based on current waveform deviation analysis. According to the method, the nonlinear distortion degree of the loudspeaker is accurately evaluated through the 1kHz difference frequency component generated by the 21kHz and 22kHz dual-frequency detection signals, so that the reliability of data transmission is more accurately predicted.

The invention discloses an AC synchronous electric energy metering method and system based on a GPS Beidou satellite clock, and relates to the technical field of electric energy metering, and the method comprises the steps: receiving a satellite signal, and analyzing the quality score of the satellite signal; according to the quality score of the satellite signal and the time reference data, generating a high-precision unified time reference; performing regional error correction on the high-precision unified time reference based on the high-precision unified time reference in combination with differential time service information of a ground base station to generate a standard time reference; acquiring actual frequency data of a power grid in real time by using power grid frequency detection equipment, calculating power grid frequency deviation, and generating a power grid frequency deviation correction factor; and dynamically adjusting the standard time reference based on the power grid frequency deviation correction factor, and performing accurate time sequence synchronization on the electric energy metering data in the alternating current power grid according to the adjusted standard time reference. The dynamic adaptability, the precision and the reliability of the electric energy metering method are remarkably improved.

The invention discloses a method for detecting juggling times in football training and a computer readable storage medium. The method comprises the following steps: step 1, acquiring a juggling training video; 2, intercepting a juggling training video into multiple frames of images, and sequentially inputting the multiple frames of images into the trained football juggling key point detection network to obtain human skeleton point location information and football point location information in each frame of image; 3, based on the human skeleton point location information and the football point location information in the image, judging whether a juggling condition is met or not according to the relevance between the football point location and the human skeleton point location in the juggling process, and recording juggling once if the juggling condition is met; 4, the images are traversed in sequence, and the juggling times of football training are obtained. According to the football training method and device, the needed football training video is collected through the user equipment with the camera shooting function, the football training juggling times of the football trainee can be accurately detected through subsequent processing, and the mode that in the existing football training process, a coach or co-trainee observes and counts all the time is changed.

An energy storage system (ESS) includes an energy storage unit, a power conditioning system (PCS), a frequency detection circuit, and a controller. The controller performs first / second frequency adjustment control on the PCS, adjusts a weight of the first / second frequency adjustment control based on a frequency difference between a frequency of an output voltage of the power conditioning system and a target frequency, controls the frequency of the output voltage of the power conditioning system to be the target frequency, and detects that islanding occurs in the power conditioning system. After islanding occurs in the power conditioning system in the energy storage system, the controller can adjust the frequency of the output voltage of the power conditioning system in which islanding occurs to the target frequency, so that islanding can be detected and an anti-islanding protection action can be completed.

The invention relates to an unmanned aerial vehicle and bird identification method based on confidence coding super-dimensional calculation. The method is mainly suitable for classification and identification of the unmanned aerial vehicle and the flying bird by a low-resolution radar with high repetition frequency detection capability. The method mainly comprises the following steps: in a training stage, firstly, preprocessing track information and micro-Doppler spectrum data, and constructing a fusion feature vector; estimating the confidence coefficient of each element of the feature vector, and carrying out vector weighted coding on the feature vector; constructing an unmanned aerial vehicle and bird training super-dimensional vector set; and in a test stage, performing similarity measurement on the test sample super-dimensional vector and the training super-dimensional vector set, and performing unmanned aerial vehicle and bird classification identification according to a calculation result. The method provided by the invention has the characteristics of simple engineering implementation, low system resource consumption, sufficient theoretical basis of the used method and the like, and can quickly and effectively solve the problem of identifying the unmanned aerial vehicle and the flying bird.

The invention belongs to the technical field of geophysical exploration, and provides an ultra-wideband active electromagnetic intelligent detection method and platform, and the technical scheme comprises the steps: configuring detection parameters of an unmanned plane transient electromagnetic detection module and an unmanned plane ground penetrating radar module according to a cooperative detection demand; based on the configured detection parameters, performing preliminary detection on the specified detection area to obtain transient electromagnetic data and ground penetrating radar data; interpreting the transient electromagnetic data and the ground penetrating radar data to generate an imaging result; and determining the depth and position of the detection target based on an imaging result, re-determining an abnormal region range based on the depth and position of the detection target, and determining an optimal detection parameter combination of the unmanned aerial vehicle transient electromagnetic detection module and the unmanned aerial vehicle ground penetrating radar module according to the abnormal region range. According to the method, the unmanned aerial vehicle cooperative detection technology, the multi-frequency detection technology and the imaging technology are combined, the limitation of the prior art is solved, a new refined cooperative detection method is provided, and the method is suitable for various application scenes.

The invention discloses a membrane bioreactor membrane pollution prediction method and system, and relates to the technical field of pollution detection. The method comprises the following steps: setting a frequency detection strategy, and connecting a membrane bioreactor to obtain a membrane feedback signal based on the frequency detection strategy; performing feedback signal fluctuation time sequence characteristic analysis based on the membrane feedback signal to obtain a feedback signal characteristic; the feedback signal features are combined with reactor operation parameters to be imported into a mechanism hybrid prediction model, mechanism constraint is carried out through a mechanism constraint layer according to the feedback signal features, data analysis is carried out on time series data features on the basis of the mechanism constraint through a data driving prediction layer, and a membrane state prediction result is obtained; and performing membrane pollution state analysis and progress prediction according to the membrane state prediction result, and generating a membrane pollution prediction data chain. The technical problems that in the prior art, membrane pollution prediction depends on an empirical threshold, so that recognition lags and precision is insufficient are solved, and the technical effect of improving membrane pollution prediction accuracy and real-time performance is achieved.

The present invention proposes a breathing frequency detection method based on time-frequency analysis of Hilbert-Huang transform. First, a WiFi link with strong environmental perception sensitivity is selected to construct a channel state information (CSI) ratio model. Secondly, the filtered CSI ratio time series is projected, and candidate sets of different breathing mode signals are generated by combining amplitude and phase information. Thirdly, the selected breathing modes are subjected to signal variational mode decomposition (VMD) and time-frequency analysis of Hilbert-Huang transform, so as to remove non-human breathing frequency components. On this basis, reconstruction is carried out, and the reconstructed signals are fused using principal component analysis (PCA). Finally, the breathing frequency is calculated through a false peak detection algorithm. The breathing frequency detection algorithm designed by the present invention not only expands the sensing range and eliminates "blind spots" while removing time-varying phase offsets and high-frequency noise and selecting the optimal subcarriers, but also improves the breathing frequency detection accuracy, providing a more accurate detection method for non-contact breathing frequency detection.

The invention provides a battery charging and discharging pulse frequency detection method and system, and the method comprises the steps: dividing a pulse current signal of a target battery during charging and discharging into a plurality of pulse signal segments, and determining the static deviation of the current of the target battery during charging and discharging based on the local current characteristics of each pulse signal segment; determining the time domain positioning error of the time interval through the static offset and the pulse width of the pulse current signal; monitoring the surface temperature of the target battery during charging and discharging, and determining the disturbance characteristics of the temperature of the target battery during charging and discharging to the current according to all the monitored temperatures and the pulse current signal; and performing pulse identification on the pulse current signal according to all the time domain positioning errors and disturbance characteristics to obtain an effective pulse time mark sequence of the target battery during charging and discharging, and determining an effective pulse frequency of the target battery during charging and discharging based on the effective pulse time mark sequence. According to the scheme, the influence of current signal drift on pulse frequency detection in the battery charging and discharging process can be reduced.

The invention relates to the technical field of battery pack linkage, and discloses a multi-string battery pack voltage collection and protection linkage method and device and computer equipment, and the method comprises the steps: carrying out the data collection of each series unit in a multi-string battery pack, and obtaining basic monitoring data; performing junction temperature calculation on power loss and thermal resistance characteristics of the MOSFET devices in each series unit to obtain real-time junction temperature data; carrying out oscillation frequency detection on the grid voltage change of the MOSFET device in each series unit to obtain grid oscillation frequency data, and carrying out thermal resistance oscillation coupling detection to obtain a dynamic protection threshold parameter; performing temperature compensation and cross interference elimination on the voltage acquisition channel of each series unit to obtain target voltage data; according to the anti-oscillation locking protection method, the problem that the MOSFET fails due to overheating is effectively prevented, the coordinated protection among the series units is ensured, and the influence of single-point failure on the whole battery pack is avoided.

The invention belongs to the technical field of gas detection and recognition, and particularly relates to a mixed gas component acoustic qualitative recognition method based on a deep learning network and a network training method. Testing a plurality of groups of sound velocities and sound absorption coefficients corresponding to different sound wave frequencies of the to-be-identified gas under the conditions of preset temperature and pressure, and then calculating to obtain effective heat capacities corresponding to the plurality of groups of to-be-identified gas according to the plurality of groups of sound velocities and sound absorption coefficients; decomposing the effective heat capacity according to a mixed gas acoustic relaxation decoupling model to obtain a gas relaxation information parameter; and taking the gas relaxation information parameter as the input of the trained mixed gas vibration characteristic frequency detection network, namely outputting the gas type in the to-be-identified gas. The invention provides a new way for identifying gas types, and the model is high in identification accuracy and wide in application scene.

The invention discloses an oil abrasive particle enrichment chip based on sound control and an LIBS (laser-induced breakdown spectroscopy) detection system and method.The enrichment chip is internally provided with an enrichment flow channel, and enrichment of oil abrasive particles is achieved through sound field driving; the detection system comprises a driving device, an enrichment chip, a detection chip, a pulse pump and an LIBS spectral analysis module, the driving device is used for sending out an electric signal with a preset frequency to excite piezoelectric ceramics to form a preset sound field in an enrichment flow channel, and oil abrasive particles are directionally gathered under the action of the sound field; the pulse pump is used for pumping the oil liquid enriched by the enrichment chip into the detection chip; the detection chip is used for carrying out secondary dispersion on the enriched oil liquid; the LIBS spectrum analysis module is used for carrying out breakdown detection on the oil liquid dispersed by the detection chip so as to obtain oil liquid spectrum data. Through a closed-loop system of sound field dynamic enrichment, pulse pump time sequence conveying and LIBS high-frequency detection, real-time continuous analysis of oil abrasive particle components is achieved, and the limitation of a traditional static sampling mode is broken through.

The invention discloses a battery changing station battery digital intelligent management system, and relates to the technical field of battery changing station battery management, and the system comprises a charging strategy optimization module which integrates historical battery changing data, a power grid load and time-of-use electricity price information, employs a time sequence prediction algorithm to predict a battery changing demand, and carries out the optimization of a charging strategy according to the battery changing demand; the battery performance monitoring module is used for carrying out dynamic frequency detection on the battery of the battery swap station by adopting a grading detection strategy and carrying out real-time parameter abnormity monitoring on the battery of the battery swap station; and the dynamic tracking and scheduling module is used for distributing coding information for the battery swap station batteries, updating the coding information in real time and performing dynamic tracking and scheduling on the battery swap station batteries according to the coding information. Through combination of the charging strategy optimization module, the battery performance monitoring module and the dynamic tracking scheduling module, full life cycle management of the battery of the battery swap station is realized, and the operation efficiency and the resource utilization rate of the battery swap station are improved.

The invention discloses a non-destructive testing system and method for a boiler pressure pipeline based on image processing, relates to the field of non-destructive testing, and solves the problem that an existing detection method for the boiler pressure pipeline is poor in effect. The sensor module is used for carrying out sensor detection on the boiler according to the boiler image processing data and respectively obtaining a pipeline pressure detection coefficient, a pipeline temperature detection coefficient and a pipeline vibration frequency detection coefficient to obtain boiler sensor data; and the nondestructive testing module is used for carrying out nondestructive testing on the boiler pipeline to be detected according to the boiler sensor data and the boiler image processing data, and issuing an abnormal early warning according to a detection result. The accuracy and comprehensiveness of nondestructive testing of the boiler pressure pipeline can be ensured.

The invention relates to the technical field of impedance matching, and discloses an impedance matching method and device, external line gateway equipment, a storage medium and a computer program product, the method is applied to the external line gateway equipment, the external line gateway equipment is connected with a telephone network for use, and the method comprises the following steps: sending a multi-frequency detection signal to the telephone network based on a preset period, echo signal attributes corresponding to the collected echo signals are obtained; feature extraction is carried out according to the echo signal attribute to obtain a feature vector, the normalized feature vector is input into a preset neural network prediction model to obtain a prediction impedance value, and the preset neural network prediction model is obtained by training the sample impedance value and the sample feature vector; and obtaining a target impedance value based on a preset smooth transition algorithm and the predicted impedance value, and performing impedance matching according to the target impedance value. Since the corresponding target impedance value is generated in real time for impedance matching, the equipment can adapt to different telephone network line characteristics for impedance matching.

The invention discloses an MEMS resonator low ripple error temperature measurement system based on voltage feedback compensation, and the system comprises a trans-impedance amplifier, an analog-to-digital converter, a frequency detection module, a PI controller, a variable gain amplifier, a Schmitt trigger, a first digital-to-analog converter, a biasing circuit, mode switches S1 and S2, and a voltage feedback compensation loop. The compensation loop comprises an amplitude detection module, a lookup table, a second digital-to-analog converter and an adder; the amplitude detection module receives the digital signal from the analog-to-digital converter and outputs a vibration amplitude signal in real time; the lookup table receives the vibration amplitude signal, inquires and outputs a corresponding digital compensation voltage, and converts the digital compensation voltage into an analog voltage through a second digital-to-analog converter; the adder adds the analog voltage and a fixed bias voltage to generate a dynamic bias voltage and applies the dynamic bias voltage to a drive electrode of the MEMS resonator. According to the system, an amplitude-driving end bias voltage feedback compensation loop is introduced, so that the periodic ripples of the resonant frequency are effectively suppressed.

The invention discloses an active protection control system and method of a motor controller and an electric vehicle. Comprising a phase current frequency detection module, a voltage conversion module, a driving chip, a control module, a high-voltage alternating-current electricity taking module and a power module, the phase current frequency detection module is used for detecting a real-time phase current frequency value of a three-phase winding of the motor in real time; the control module is used for storing a phase current frequency limit value and outputting an enable signal of the voltage conversion module; the high-voltage alternating current power taking module is used for obtaining at least one phase of alternating current in the three-phase alternating current and supplying power to the voltage conversion module; the voltage conversion module is used for receiving the voltage conversion enable signal, starting working, converting at least one phase of alternating current into working voltage required by the power module, and outputting the working voltage to a fault pin of the driving chip and a grid electrode of a driving tube of an upper bridge arm or a lower bridge arm in the power module; the active short-circuit protection of the motor in a galloping or overspeed state is realized, and the overvoltage damage of the motor controller is avoided.