1952 results about "Signal frequency" patented technology

The invention relates to the technical field of communication optimization, in particular to a wireless communication method and system of a vehicle diagnosis system. The method comprises the following steps: identifying a plurality of signal sources in an environment and three-dimensional space data of a current position of a vehicle; performing scene interference intensity comprehensive evaluation on the plurality of signal sources in the environment to obtain a current scene interference intensity evaluation value of the vehicle; environment obstacle space layout analysis is carried out on the three-dimensional space data of the current position of the vehicle, environment three-dimensional modeling is carried out, and a vehicle environment three-dimensional point cloud model is constructed; signal multi-path propagation evolution is carried out according to the current scene interference intensity evaluation value of the vehicle and the vehicle environment three-dimensional point cloud model, and optimal signal frequency band analysis is carried out, so that optimal signal frequency band parameters are extracted; and carrying out dynamic transmission frequency modulation and signal adaptive coding based on the optimal signal frequency band parameter, and constructing a dynamic signal transmission strategy. According to the invention, efficient and stable wireless communication is realized, and the vehicle-mounted communication performance is improved.

The invention relates to the technical field of semiconductors, and discloses a full-temperature-zone polynomial digital temperature compensation method and system based on an SOI chip, and the method comprises the steps: obtaining the temperature frequency data of a preset temperature zone of a target SOI chip, fitting a full-temperature-zone curve, extracting a critical point of the temperature zone, dividing a segmented compensation interval according to the critical point, and obtaining the temperature frequency data of the preset temperature zone of the target SOI chip; the method comprises the following steps: calculating frequency drift amounts under different voltages to construct a full-automatic test framework, acquiring an environment temperature parameter and an instantaneous temperature value by using the framework, analyzing a temperature compensation vector of a segmented compensation interval, further monitoring a signal frequency interval output by a chip, extracting a phase noise parameter, calculating a frequency offset error amount with a preset value, and calculating the frequency offset error amount. And analyzing an error source, optimizing a polynomial compensation order, and collecting temperature drift suppression data to generate a full temperature region compensation report. According to the invention, the performance stability of the chip in a complex environment can be improved.

The invention relates to the technical field of carrier communication, in particular to a multimode power line carrier communication method and a carrier communication module, and the method comprises the steps: determining a frequency coincidence degree through analyzing the coincidence degree of a frequency corresponding to a positive number amplitude value on a spectrogram of each modal component in a carrier signal and a signal frequency range of the carrier signal, and determining a difference index by analyzing the difference between each characteristic modal component and all modal components of the noise reference signal in frequency, analyzing the centralized distribution condition of the carrier signal in energy, and determining a step length adjustment value in combination with the signal interference degree. And carrying out noise reduction processing on the carrier signal in the power line carrier communication process at the current moment. The invention aims to eliminate noise interference in carrier signals and improve the reliability of power line carrier communication.

According to the 5G portable WiFi signal enhancement method and system provided by the invention, surrounding environment data are collected through an environment sensing sensor, and a device placement scheme is optimized in combination with a deep learning algorithm, so that the signal coverage range is expanded; the strategy of dynamically adjusting the transmitting power, the signal frequency and the modulation mode can optimize the signal strength according to the environmental change; interference signals are analyzed through quantum calculation, null is formed through the beam forming technology, interference signal receiving is effectively restrained, and the signal strength in the target direction is enhanced. In combination with the Internet of Things technology, uploading equipment state data to an edge server in real time for big data analysis, and pushing a personalized signal enhancement scheme according to different user use environments; through precise placement guidance and a dynamic frequency band switching strategy, a user can enjoy smoother network connection in a use process, and good signal quality is ensured to be kept in a complex environment. According to the invention, not only can the signal quality of 5G portable WiFi be improved, but also more intelligent and personalized network experience can be provided for users.

The invention relates to the technical field of nondestructive testing, in particular to a multi-modal fusion metal microcrack ultrasonic detection system and method, and the system comprises an ultrasonic signal acquisition module, a signal preprocessing module, a feature alignment network module, an image segmentation module, a time-frequency analysis module and a segmentation result fusion module. According to the system, three modes of electromagnetic ultrasound, laser ultrasound and phased array ultrasound are utilized to detect a metal sample, and real-time nondestructive signal data acquisition and pretreatment are realized. The feature alignment network aligns and fuses the three modal signal features, and the U-Net segmentation neural network performs submillimeter crack segmentation on the fused features. And the time-frequency analysis module extracts signal frequency and amplitude information, and evaluates the breaking strength in combination with the crack label. Finally, a segmentation result fusion module integrates crack labels and time sequence features, and whether cracks exist or not is classified through a weighted convolutional neural network. According to the system, the detection performance, the practicability and the adaptability are remarkably improved, and a new scheme is provided for precise detection of metal microcracks.

The invention provides a multi-band radio frequency power amplifier dynamic range adaptive test method and a system thereof. The method comprises the following steps: acquiring an output signal frequency spectrum of a tested radio frequency power amplifier, extracting characteristic frequency points including a center frequency and a bandwidth, matching the characteristic frequency points with a preset frequency band database, and automatically loading a test scheme of a corresponding frequency band. According to the method, the frequency bands are automatically matched through spectrum sensing, the test scheme is loaded, the multi-frequency-band characteristics can be rapidly adapted without manual parameter configuration, index missing test is avoided, and the switching efficiency is improved; dynamically optimizing test parameters by using a genetic algorithm, and accurately capturing a nonlinear distortion critical point while balancing coverage and efficiency; by combining multi-dimensional signal analysis and a deep learning model, the problem of missing detection of traditional single-domain analysis is solved, and the abnormal signal recognition capability is remarkably enhanced; through linear model correction, impedance dynamic matching and index threshold iteration, full automation and high precision of the test are realized, the environmental interference influence is effectively reduced, and a self-adaptive test system is constructed.

The invention discloses a system and method for classifying and recognizing epilepsy in electroencephalogram signals based on a time sequence. The system comprises a cross-domain mixed self-supervised learning module, a multi-scale electroencephalogram feature learning module, an epileptic seizure guided self-attention learning module and a classifier. The cross-domain hybrid self-supervised learning module comprises a time domain context prediction task unit, a channel information reconstruction task unit and a frequency spectrum masking identification task unit; the cross-domain hybrid self-supervised learning module reconstructs an input electroencephalogram signal according to a time domain, a space domain and a frequency domain to obtain an electroencephalogram representation model; the time domain context prediction task unit is used for capturing dynamic change characteristics before and after epileptic seizure by learning a time domain evolution rule of electroencephalogram signals; the channel information reconstruction task unit is used for reconstructing missing electroencephalogram signal channel data and enhancing spatial information representation of an electroencephalogram representation model; the frequency spectrum masking identification task unit trains the electroencephalogram characterization model to characterize epilepsy nerve oscillation through a random masking part electroencephalogram signal frequency component in a frequency domain; the multi-scale electroencephalogram feature learning module captures local and global level epilepsy features of an electroencephalogram representation model through different resolutions to obtain a first epilepsy electroencephalogram feature model; the epileptic seizure guided self-attention learning module optimizes the first epileptic electroencephalogram feature model by fusing time sequence and spatial features to obtain a second epileptic electroencephalogram feature model; and the classifier classifies and outputs the electroencephalogram features of the second epileptic electroencephalogram feature model based on the long short-term memory network to determine whether the epileptic seizure occurs. The invention provides an efficient, accurate and robust solution for automatic detection and clinical auxiliary diagnosis of the epileptic seizure.

The invention relates to the technical field of data monitoring analysis, and discloses a centrifugal machine data remote monitoring analysis method and system based on a cloud computer, and the method comprises the following steps: collecting centrifugal machine operation index data, carrying out time stamp synchronization, carrying out the recognition and elimination of abnormal values in the data, and carrying out the data integration through data normalization processing, and generating synchronous monitoring data. According to the invention, the data frequency domain analysis of the centrifugal machine is implemented on the cloud platform, the vibration signal frequency spectrum and energy distribution are accurately identified, the efficient marking and trend analysis of abnormal data are realized, the detailed degree and response speed of abnormal detection are enhanced, and the monitoring of the running state of the centrifugal machine is more accurate; by combining real-time trend analysis and historical fault data, the accuracy of fault prediction is improved, the classification of fault modes is more scientific, the situations of false alarm and missing alarm are effectively reduced, the timeliness and pertinence of preventive maintenance measures are enhanced, and the running efficiency and safety of the centrifugal machine are remarkably improved.

This disclosure is directed to shared antenna tuning. An electronic device may receive a global navigation satellite system (GNSS) tune request to tune a shared antenna to a GNSS signal frequency. The electronic device may then tune the antenna to the GNSS signal frequency and enable a GNSS receiver. The electronic device may also receive a cellular tune request to tune the antenna to a cellular frequency. The electronic device may tune the antenna to a cellular frequency and may deactivate the GNSS receiver or blank the GNSS receiver. In some embodiments, the electronic device may also communicate with a Low Earth Orbit (LEO) satellite. During LEO satellite communication, the electronic device may transmit a signal to blank a GNSS L1 receiver to avoid signal interference with the LEO satellite communication, and activate a GNSS L5 receiver to receive GNSS signals.

The invention relates to a digital lock-in amplifier based on a frequency adaptive technology and a weak signal acquisition system and method, and the system comprises a front-end signal processing module which is used for obtaining a weak signal to be detected; the frequency self-adaptive tracking module is used for performing fast Fourier transform on the frequency of the weak signal to be measured to obtain the position of the maximum spectral line so as to synthesize a frequency control word, further generate a local reference signal and simultaneously adjust the coefficients of a low-pass filter and a loop filter and the series adjustment mode of a carrier synchronization ring; the multi-rate narrow-band low-pass filter module is used for multiplying the digital signal by a local reference signal and then carrying out filtering and down-sampling on a high-frequency signal to obtain a plurality of mutually orthogonal difference frequency components; the vector operation module is used for carrying out vector operation on the plurality of mutually orthogonal difference frequency components to obtain the phase and the amplitude in the weak signal to be measured; and the man-machine interaction module is used for displaying and storing the phase and the amplitude in the weak signal to be detected.

The invention discloses a distributed photovoltaic access power distribution network relay protection analysis method and system, and belongs to the technical field of photovoltaic grid connection, and the method specifically comprises the steps: injecting a dynamic resonance detection signal at the AC side of a current converter of a photovoltaic grid-connected system, and enabling the frequency to be matched with the natural resonance frequency of a target section; analyzing the energy focusing effect of the dynamic resonance detection signal in the power distribution network, and generating a resonance energy distribution map; when the energy density of a certain section in the resonance energy distribution map exceeds a preset threshold value, the photovoltaic output current waveform is adjusted to be a discontinuous waveform containing periodic intermittent cutoff; based on the reflection delay difference of the waveform in the fault section, constructing a space-time mapping model of a fault point, and analyzing and determining a fault position; according to an output result of the space-time mapping model, controlling a photovoltaic side circuit breaker and a power grid side relay to execute a selective tripping action based on waveform phase synchronization; according to the invention, the sensitivity and reliability of distributed photovoltaic access power distribution network relay protection are improved.

The invention discloses a sparse cloth double-array element multi-frequency ambiguity resolution interference angle measurement method and system, relates to the technical field of radar measurement, realizes design of a multi-frequency signal frequency selection criterion, and further realizes non-ambiguity and high-precision angle measurement of all angles in an angle range required by engineering. According to the technical scheme, a physical baseline length and a reference frequency are set according to a layout space; deriving a plurality of signal carrier frequency design criteria according to the Chinese remainder theorem; calculating the carrier phase difference of the double-array-element receiving signals under different signal carrier frequencies; and reconstructing the congruence equation set, and solving the congruence equation set to solve ambiguity so as to obtain a target angle estimation value.

In a power conversion device that converts a DC voltage to an AC voltage by turning a semiconductor switching element (Q) on and off, a drive controller (10) that generates a gate signal for driving the semiconductor switching element (Q) on and off is configured to generate a first command which is a voltage command for a target voltage of the AC voltage, generate a triangular wave carrier signal whose frequency is an even multiple of a fundamental wave component of the first command, and generate the gate signal from the carrier signal and a second command composed of a harmonic signal including at least one odd-multiple harmonic signal whose frequency is an odd-multiple and one even-multiple harmonic signal whose frequency is an even multiple of the fundamental wave component of the first command, and the first command.

The invention belongs to the technical field of unmanned aerial vehicle full-aviation electromagnetic detection, and particularly relates to a full-aviation frequency domain electromagnetic emission system and a control method. A broadband frequency mixing and matching circuit is connected in series between an H-bridge power inverter and an emission coil of an unmanned aerial vehicle electromagnetic emission system; the broadband mixing and matching circuit comprises a first resonance unit formed by connecting a fixed capacitor and an adjustable inductor in parallel and a second resonance unit formed by connecting a fixed capacitor and an adjustable inductor in parallel, and the first resonance unit and the second resonance unit are connected in series. The adjustable inductor is matched with the dynamic impedance of the inductive load by adjusting the inductance value, and the broadband frequency mixing and matching circuit can adjust the impedance in real time, so that the matching of different resonant frequencies is realized, and the frequency range of a matching signal can be obviously widened.

The invention provides an electroencephalogram model training method and device and a storage medium, and the method comprises the steps: segmenting a first original EEG data sample into a first original EEG fragment set, and covering a part of original EEG fragments in the first original EEG fragment set to obtain a corresponding visible EEG fragment subset and a covered EEG fragment subset; corresponding visible EEG simulation frequency domain coding features are determined through coding; extracting original signal frequency domain features, and reconstructing each visible EEG fragment according to visible EEG simulation frequency domain coding features to calculate frequency domain reconstruction loss; decoding the visible EEG simulation frequency domain coding features to predict a codebook basic class corresponding to each masked EEG fragment, and calculating classification loss by combining a codebook basic class label of each masked EEG fragment; and performing training optimization on the electroencephalogram model according to the frequency domain reconstruction loss and the classification loss. Therefore, double optimization of the frequency domain reconstruction task and the classification task of the electroencephalogram model is realized.

A data and clock recovery circuit, a receiving apparatus, a circuit system, a vehicle-mounted device, a vehicle, and a data and clock recovery method are provided. The data and clock recovery circuit includes a sampler, a phase detector, a multi-order filter, a frequency change detection circuit, and a selector. The sampler is configured to sample an input signal based on a multi-order filtered signal to generate a sampled signal. The phase detector is configured to determine a phase difference in the sampled signal based on the sampled signal. The multi-order filter is configured to generate the multi-order filtered signal based on the phase difference. The frequency change detection circuit is configured to determine a frequency change direction of a spread spectrum clock in the input signal by using the phase difference.

The invention discloses an adaptive equalization method for combined compensation of carrier frequency offset and channel linear damage. The adaptive equalization method specifically comprises the following steps: taking data subjected to matched filtering, clock synchronization, orthogonality and normalization as input signals; for an input signal, using the filter linear damage compensation weight vector and the frequency offset compensation weight coefficient to obtain output data of the filter; obtaining an expected value of filter output data, and calculating to obtain a theoretical error value of adaptive equalization; and obtaining a filter weight vector used for next adaptive equalization according to the theoretical error value. The adaptive equalization method for combined compensation of carrier frequency offset and channel linear impairment is suitable for a coherent optical transmission system, uses an adaptive equalizer to compensate signal frequency offset and channel linear impairment at the same time, does not need an additional frequency offset estimation algorithm, meets the advantages of multiple rates and multiple modulation formats, and is high in convergence speed and high in robustness. And the calculation complexity is low.

The invention discloses a water supply pipeline leakage identification method based on active low-frequency sound wave excitation, and the method comprises the steps: obtaining a sound signal in a pipeline through a low-frequency sound emission transducer and a hydrophone which are disposed at two ends of the pipeline, and generating a corresponding leakage point position based on a pre-constructed sound wave equation; processing the sound signal to obtain a corresponding time-frequency image, labeling the time-frequency image by judging whether the sound signal is a leakage signal or not, and forming a data set by a signal frequency spectrum, a leakage point position and a label; constructing an identification network; training an identification network by using the data set to obtain a water supply pipeline leakage identification model for identifying whether the pipeline is leaked or not; and inputting the sound signal in the to-be-identified pipeline into the water supply pipeline leakage identification model so as to output an identification result about whether the pipeline is leaked or not and an identification result about the position of a leakage point. The invention further provides a water supply pipeline leakage identification device. The method provided by the invention can effectively improve the accuracy of leakage identification.

The invention relates to the technical field of spectral analysis, and discloses a visible spectrum noise reduction and heavy metal ion detection method, which comprises the following steps: reacting a water sample to be detected with a color developing agent to generate a color developing system, obtaining a gray spectrum signal through optical imaging equipment, carrying out variational mode decomposition, optimizing the signal by adopting singular value decomposition, and calculating the noise of the heavy metal ions. And determining an optimal reconstruction order by using a particle swarm optimization algorithm and reconstructing a signal, finally extracting a feature value from the denoised spectral signal, and predicting the type and concentration of metal ions through a neural network model. Spectral global / local features are modeled through cooperation of multi-head self-attention and learnable position coding, signal frequency-time domain cross-modal fusion is realized in combination with variational mode decomposition and cross attention, training parameters are dynamically optimized by innovatively adopting a reinforcement learning strategy, classification and regression tasks are self-adaptively balanced based on a gradient diversity reward mechanism, and frequency-time domain cross-modal fusion is realized. And finally, dual precision improvement of ion type identification and concentration prediction and model robustness enhancement are realized in a complex noise scene.

The invention relates to a power line network unknown port and branch discovery method and device and computer equipment. The method comprises the following steps: determining the number of unknown ports on a target line and the corresponding branch length according to the frequency response of a sweep frequency signal between a transformer substation and a target communication node; according to the frequency response of the sweep frequency signal, determining multipath parameters from the transformer station to the self-transmitting and self-receiving and from the transformer station to the target communication node; determining a first port closest to the substation according to the multipath parameter and the branch length, and determining a multipath channel response caused by the first port; and updating the frequency response of the sweep frequency signal according to the multipath channel response, and re-determining a first port closest to the transformer substation according to the updated frequency response of the sweep frequency signal until the number of unknown ports on the target line is zero. By adopting the method, the power line network topology can be accurately constructed.

The invention discloses a tunnel outburst prevention rock mass fracture extension continuous monitoring method based on micro-seismic infield positioning, which comprises the following steps: S1, according to the distance L between a disaster-causing structure and a tunnel face, drilling an advanced drill hole in the tunnel face, acquiring lithology and water inflow information of surrounding rock, and preliminarily determining an outburst prevention rock mass hydraulic communication area range; s2, micro-seismic sensors are arranged on the arch crown, the left wall foot and the right wall foot within the range of L / 2-2 m to L / 2 + 2 m in front of the tunnel face in the drilled advance drill hole correspondingly; s3, recording seismic source microseismic signal frequency, duration and waveform of explosive blasting, mechanical vibration and vehicle traveling, and screening microseismic signals of crack extension in the rock mass; s4, performing rock mass internal fracture extension seismic source positioning by adopting a simplex method; and S5, drawing a micro-seismic event three-dimensional model, and determining the expansion and evolution characteristics and range of the fractures in the hydraulic communication area. According to the invention, the monitoring continuity of the outburst prevention rock mass fracture evolution process of the tunnel and the positioning precision of the water inrush channel can be improved.

The embodiment of the invention provides a method for realizing long-distance signal transmission under the condition of a porous medium in a goaf. The method comprises the following steps: selecting a proper signal frequency range based on the physical characteristics of the porous medium in the goaf; designing a corresponding signal modulation mode according to the selected signal frequency range; the stability of a signal propagation path is enhanced through a relay node deployed in the goaf; modulation parameters are dynamically adjusted based on the signal quality fed back by the relay node to optimize the transmission effect. Through the scheme of the embodiment of the invention, the problem of how to optimize and select the signal frequency so as to solve the problem of too fast signal attenuation in the porous medium can be solved, and meanwhile, the problem of how to regulate and control the dielectric property of the transmission path so as to solve the delay problem caused by signal refraction and reflection can be solved; and the problem of bit error rate increase in long-distance transmission can be solved by adjusting the signal coding mode.

The invention relates to the technical field of mechanical vibration and fluid excitation coupling effect analysis, in particular to a runner crown modification pressure pulsation amplitude measurement method, which comprises the following steps of: extracting pressure gradient distribution and cavitation phase change characteristic parameters of a runner surface through fluid dynamics simulation; targeted arrangement of a high-frequency pressure sensor array in a vortex core area, a boundary layer separation critical position and a modification structure mutation area is guided, and the signal acquisition precision is improved by adopting an annular encryption and axial equal-interval arrangement strategy. And establishing a dynamic error feedback mechanism of actual measurement and simulation. And verifying an abnormal frequency band proportion through frequency domain kurtosis and analyzing envelope spectrum harmonic waves, and screening a modification parameter combination with the pressure pulsation amplitude decreasing to reach the standard and stable frequency band distribution. According to the method, the problem of measurement errors caused by multi-source high-frequency noise and effective signal frequency domain aliasing is solved, a high-precision quantification basis is provided for runner modification optimization, and the method is suitable for the field of mechanical system dynamic characteristic testing.

The invention discloses an InSAR (Interferometric Synthetic Aperture Radar) phase filtering method based on a plurality of interferograms, which comprises the following steps of: preprocessing acquired main and auxiliary SAR images to obtain the plurality of InSAR interferograms; dividing the plurality of InSAR interferograms into square interferogram patches along the azimuth direction and the distance direction; converting each interferogram patch from a spatial domain into a frequency domain signal, and constructing a corresponding frequency spectrum amplitude diagram; using a K-means clustering method to cluster and extract an initial low-pass filter in the spectrum amplitude diagram, and constructing a phase filter together with a Kaiser window function; the frequency domain signals of the interferogram plaques pass through a phase filter, the signal frequency band power is reserved, the noise at the high-frequency position is filtered out, meanwhile, the noise at the low-frequency position is filtered out through smoothing operation, and the filtered frequency domain signals are obtained; and the filtered frequency domain signals are converted to a spatial domain, filtered interferogram patches are obtained and spliced, and a filtered InSAR interferogram is obtained. The method is beneficial to popularization and promotion of the development of the current time sequence InSAR interferometry technology and the application in engineering.

The invention relates to the technical field of integrated circuits, in particular to a charge pump phase-locked loop circuit, a radar and a charge pump phase-locked loop locking control method.The circuit comprises a charge pump, the charge pump comprises a first branch circuit, a second branch circuit, a third branch circuit and a fourth branch circuit, the frequency sweeping state refers to the state when the frequency of the signal output by the phase-locked loop is linearly changed; the at least one second branch is connected to the first branch under the condition that the hopping amplitude of the frequency of the signal output by the phase-locked loop is greater than or equal to a preset amplitude threshold value so as to increase the magnitude of the current output by the charge pump, and is disconnected with the first branch when the phase-locked loop enters a frequency sweeping state; the circuit can effectively shorten the locking time of the phase-locked loop when the phase-locked loop has relatively large frequency hopping, and is beneficial to improving the response speed and performance of a system.

The invention relates to the technical field of data communication, in particular to a WiFi (Wireless Fidelity)-based data communication method and system. The method comprises the following steps: acquiring a routing WiFi (Wireless Fidelity) 6 networking control authority, acquiring a signal frequency band state and identifying a frequency band load state; then, the load state is converted into a spectrogram, and throughput attenuation simulation and adjacent channel interference risk quantification are carried out; then, fitting a network congestion increment index according to the data packet loss risk and throughput attenuation data, and performing channel frequency band planning and OFDMA subcarrier allocation optimization according to the network congestion increment index; and finally, designing a WiFi (Wireless Fidelity) data communication strategy, and sending the WiFi data communication strategy to a control center to implement the optimized data communication method. According to the invention, the data communication technology is optimized, so that the data communication technology is more perfect.

The invention relates to the technical field of pump unit anomaly detection, and discloses a pump unit anomaly detection method and system based on voiceprint recognition, and the method comprises the steps: building a voiceprint signal set, and extracting a high-frequency signal; determining a time window, and splitting the high-frequency signal to obtain sub high-frequency signals; determining the signal frequency of the sub-high-frequency signal, determining the characterization frequency, comparing the characterization frequency with a standard frequency range, and determining a primary detection result; when it is determined that the abnormality is suspected, the signal intensity is obtained, the comprehensive frequency value of the voiceprint signal is obtained, and whether the circulating water pump is abnormal or not is judged; and when the abnormal circulating water pumps exist in the to-be-detected pump unit, determining the abnormal type of each abnormal circulating water pump by adopting a pre-trained curled neural model, and determining an early warning level according to the abnormal types and the number of the abnormal water pumps. According to the method, the equipment abnormity is recognized in the early stage, early warning is carried out in time, the equipment shutdown time and maintenance cost are reduced, and the stability and operation efficiency of the pump unit are improved.

The invention belongs to the technical field of optical communication, and particularly relates to a low-complexity digital pre-equalizer based on frequency domain comb pilot channel estimation. The device comprises a data sending module, a channel response test module and a digital signal pre-equalization module, the data sending module comprises an initial comb signal generation part and a frequency component phase rotation part; the channel response test module comprises a signal frequency difference estimation and recovery part and a channel amplitude-frequency and phase-frequency response test part; the digital signal pre-equalization module comprises a filtering coefficient generation part and a sending signal convolution pre-equalization part; according to the invention, a frequency domain comb pilot signal is sent to analyze channel amplitude-frequency and phase-frequency response, so that a pre-equalizer for pre-compensating channel response at a sending end is generated; the method has the characteristics of high granularity, high precision, robust transmission signal system and the like, and can be applied to various scenes such as polarization multiplexing long-distance single-carrier coherent optical transmission, mode multiplexing short-distance intensity modulation direct detection systems and the like.

The invention particularly relates to a miniaturized broadband instantaneous frequency measurement receiver and a corresponding data processing method. The miniaturized broadband instantaneous frequency measurement receiver comprises a signal input port used for receiving an original radio frequency signal; the amplifying and filtering module is used for amplifying and filtering the original radio frequency signal and then outputting a first radio frequency signal; the first power divider is used for splitting the first radio frequency signal and outputting the first radio frequency signal to the multi-channel power division phase discrimination assembly; the multi-channel power division and phase discrimination assembly comprises a plurality of power division and phase discrimination modules and is used for carrying out instantaneous measurement on the signal frequency of the first radio frequency signal and outputting multi-channel video signals; the frequency measurement coding module is used for performing frequency measurement processing on the video signal and outputting a frequency code; wherein the signal input port is connected with the amplification filtering module and the power division phase discrimination module through microstrip lines; the power division phase discrimination module is connected with the frequency measurement coding module through a glass insulator. The size, the volume and the weight of the device all meet the requirement for miniaturization.

The invention relates to the technical field of partial discharge detection, in particular to a partial discharge detection method and system for a high-low voltage switch cabinet, and the method comprises the steps: obtaining electromagnetic wave signals and power system voltage data of each sensor position in real time; acquiring a partial discharge period in each detection window according to the electromagnetic wave maximum value of all the sensors in each power frequency period in each detection window, the distance between the electromagnetic wave maximum value and the voltage wave crest and the voltage wave trough of the power system, and the electromagnetic wave signal difference between the sensors; and according to the dispersion degree of the electromagnetic wave maximum values of all the sensors under each partial discharge period in each detection window, the electromagnetic wave signal frequency domain energy of each partial discharge period and the proportion of the partial discharge period in each detection window, obtaining the existence confidence of each detection window, and judging whether partial discharge exists under the current detection window or not. According to the invention, by analyzing the distinguishing characteristics of the partial discharge and the electromagnetic interference in the electromagnetic wave signals at multiple positions, the detection precision of the partial discharge is improved.