745 results about "Pulse (signal processing)" patented technology

The invention relates to the technical field of partial discharge detection, in particular to a leak detection and partial discharge detection method and system based on artificial intelligence, and the method comprises the following steps: obtaining a partial discharge pulse signal, extracting a phase mutation coordinate, analyzing an incremental feature, reconstructing a propagation waveform, constructing an amplitude gradient matrix, and screening a direction vector; and a backtracking path calculates a change rate to generate a time track, and track mapping and space positioning are completed in combination with image data. According to the method, the accuracy and the response speed of partial discharge detection are improved through multi-stage signal processing, extreme points and phase abrupt change are analyzed, more accurate discharge feature capture and equipment defect positioning are achieved, phase and amplitude data are combined, the discharge mode is recognized, a signal propagation path is reconstructed, the fault source positioning accuracy is improved, and the fault source positioning accuracy is improved. Through dynamic rendering, the intuition of a detection result is enhanced, real-time decision is supported, the method is more intelligent and efficient, the equipment fault risk is greatly reduced, and the safe operation level of power equipment is improved.

The invention discloses a high-speed multi-photon detection system and method. The system comprises a detector and a signal processing circuit, wherein the detector is composed of a window plated with a photoelectric cathode, a micro-channel plate stack and an anode; a plurality of incident photons are converted into a plurality of photoelectrons by the photoelectric cathode, and the photoelectrons are converted into electron cloud by the micro-channel plate stack; the incident electron cloud is divided into multiple paths by three layers of staggered metal strip electrodes of the anode, and charge collection is carried out to obtain charge short pulses of each layer of electrode; the signal processing circuit converts the charge short pulses transmitted by the three layers of electrodes into digital pulse signals, obtains the centroid coordinates of the electron cloud from the digital pulse signals as the abscissa value, the ordinate value and the verification value of the incident photon position, combines the abscissa value, the ordinate value and the verification value based on the screening condition to obtain the target two-dimensional coordinates, and finally obtains the target two-dimensional coordinates. And transmitting to a terminal for imaging display. According to the invention, a plurality of synchronous photons can be detected, the overall counting rate of the detector is greatly improved, and the detection efficiency is improved.

The invention is applied to the field of mechanical fault diagnosis signal processing, and particularly provides a pulse neural network mechanical fault diagnosis method based on STFT dimension transformation, and the method comprises the steps: collecting a one-dimensional mechanical vibration signal, carrying out the wavelet decomposition, carrying out the wavelet reconstruction of a low-frequency component and a denoised high-frequency component, and carrying out the wavelet reconstruction of the low-frequency component and the denoised high-frequency component; obtaining a denoised one-dimensional vibration signal; performing short-time Fourier transform, and converting the time-frequency two-dimensional matrix into a time-frequency two-dimensional matrix; inputting the time-frequency two-dimensional matrix into an improved HH threshold neuron model, carrying out Poisson sparse coding on the time-frequency two-dimensional matrix, and only carrying out pulse response on signal significant features; constructing a suprathreshold coding convolutional network with residual connection, inputting a sparse coding matrix, training by adopting an unsupervised learning rule based on STDP, and adaptively adjusting a network synaptic weight; and inputting to a trained above-threshold coding convolutional network, and obtaining pulse emission activity of neurons of an output layer through network forward propagation to determine a fault diagnosis result.

The invention relates to the technical field of radio frequency transmit-receive control, in particular to a radio frequency transmit-receive control system for radar height measurement, which comprises a pulse adaptation control module, a time resolution partition module, an echo structure identification module, a multi-frequency channel screening module and a transmit-receive control decision module. According to the method, by dynamically extracting the echo amplitude jump point and compressing the pulse width, the time domain separation capability can be improved, the recognition precision of an adjacent target can be enhanced, the interval distribution characteristics are constructed based on the jump time difference, the sparse time period is screened for evaluating the resolution feasibility, and the adaptability to different echo densities is enhanced; a structure identification window is established around the maximum value of a main lobe, the overrun number of side lobe samples is counted, the accuracy of signal morphological structure identification is improved, the ratio of the main lobe samples to the side lobe samples is combined with a signal-to-noise ratio threshold to perform frequency band screening, a channel priority sequence is formed, and the flexibility and accuracy of signal processing and the spectrum utilization efficiency in the radar height measurement process are enhanced.

The invention discloses an intelligent identification system and method based on time-frequency feature fusion and adaptive classification, and relates to the technical field of power equipment state monitoring. Comprising an ultrahigh frequency signal processing unit, a filter amplification unit, an analog-to-digital conversion unit, a digital signal preprocessing unit, a multi-dimensional feature extraction unit, a discharge phase analysis unit, a classification model optimization unit, an interference elimination unit, a defect type identification and diagnosis unit and a discharge source positioning unit. The ultrahigh frequency signal processing unit is used for collecting and transmitting partial discharge weak electromagnetic signals, and the filtering and amplifying unit is used for filtering, eliminating interference and amplifying signal amplitude. Through the ultrahigh frequency signal processing unit, the filtering and amplifying unit and the analog-to-digital conversion unit, weak electromagnetic signals are accurately collected, interference is efficiently filtered out, the signals are amplified and converted, the accuracy and effectiveness of the detection process are improved, and the misjudgment risk is reduced through pulse segmentation and normalization, multi-dimensional feature extraction and classification model establishment and optimization.

The invention provides an endangered animal monitoring method based on a multi-mode floating gate type photoelectric synapse transistor, realizes multi-mode fusion of images (optical signals) and sounds (electric signals) by utilizing the light absorption capability of quantum dots and the high carrier mobility of a two-dimensional channel material, and belongs to the technical field of sensing, storage and calculation integration and endangered animal identification and monitoring. According to the method, a photoelectric synapse device is used as a reservoir, and input time sequence signals are respectively applied to a multi-mode fused photoelectric synapse transistor in the form of light and electric pulse. And along with the co-stimulation of light and electric pulse, the change response of source-drain current is generated, and the fusion processing of the multi-mode signal is realized. By adopting the method, a human multi-sensory fusion signal processing mode is successfully simulated, and accurate recognition under complex and changeable conditions can be realized by utilizing a mode of complementation of visual signals and auditory signals. Under an extreme environment or a high noise condition, edge processing and identification can be carried out on pictures and sounds of endangered animals, and a high-accuracy monitoring result can be obtained without a large amount of data return, so that the energy consumption is reduced and the monitoring efficiency is enhanced.

The invention discloses a multi-parameter ultrahigh frequency sensor performance comprehensive evaluation method, which belongs to the technical field of sensor performance evaluation, and effectively breaks through the limitation of the traditional static test on a transient interference response blind area through a dynamic interference field simulation test and an original fidelity-false triggering joint evaluation model. The adaptive adjustment mechanism of the multi-source interference field can vividly simulate the space-time non-uniform characteristic of electromagnetic noise in an industrial field, and in combination with a time-frequency domain composite evaluation algorithm, not only is the signal distortion degree of the sensor in typical interference modes such as frequency sweeping and pulse train quantified, but also the error action acceleration rule caused by high-frequency-band noise coupling is disclosed. The dynamic immunity evaluation capability enables a designer to accurately position the electromagnetic shielding weakness of the sensor, optimizes a front-end filter circuit or a signal processing algorithm in a targeted manner, and remarkably improves the reliability of a product in strong interference scenes such as radar detection and wireless communication.

The invention discloses a multi-target transcranial electrical stimulation device based on cross-regional phase-locked stimulation, and the device comprises a light electroencephalogram cap which is integrated with at least one pair of electroencephalogram signal collection electrodes located in a first brain region and used for monitoring specific neural oscillation, and is provided with electrode holes used for placing stimulation electrodes in a second brain region; a plurality of stimulating electrodes; a controller, a multi-channel stimulation module, an electroencephalogram signal processing and feedback regulation and control module and a communication module are arranged in the control box; the electroencephalogram signal module is configured to detect the phase of specific neural oscillation of a first brain region in real time; the controller is configured to accurately control the time or phase of stimulation (such as transcranial alternating current stimulation or pulse stimulation) output by the multi-channel stimulation module in the second brain region based on the detected real-time phase information, and cross-region phase-locked stimulation is achieved. The device is suitable for personalized nerve regulation and control application in a family environment while remarkably simplifying user operation, reducing cost and improving comfort and portability.

The invention discloses a wearable cardiovascular pressure early warning system, which relates to the technical field of wearable medical health monitoring and comprises wearable equipment, and a signal acquisition module, a signal processing module, a posture self-adaptive module and a communication module which are integrated in the wearable equipment. The signal acquisition module comprises a photoelectric volume pulse wave sensor and an inertial measurement unit and is used for acquiring physiological signals and motion data of a user; the signal processing module is used for extracting pulse wave characteristics based on the signals and judging the motion state and the body position state of the user in combination with data of the inertial measurement unit so as to realize pulse-by-pulse blood pressure estimation and cardiovascular pressure trend analysis; the posture self-adaption module identifies user postures through deep learning and dynamically selects a compensation algorithm according to different postures, so that the signal accuracy is improved. According to the invention, continuous, non-invasive and dynamic monitoring of cardiovascular pressure is realized, and long-term and convenient health state monitoring and risk early warning service can be provided for users.

The invention relates to the technical field of optical signal processing and analysis, and particularly provides a seabed crustal activity monitoring method based on a differential phase sensitive optical time domain reflectometer, which comprises the following steps: carrying out differential processing on an echo optical pulse signal to obtain a first differential echo matrix; and setting a dynamic window constraint to obtain a second differential echo matrix. The second differential echo matrix includes a low rank term, a sparse term, and a noise term. And constructing a global optimization problem according to the second differential echo matrix, and solving a sparse item estimation matrix corresponding to the sparse item. And separating irrelevant activities in the sparse item estimation matrix to obtain a target activity matrix, and then obtaining a monitoring result. According to the method, non-low-rank trend features such as slow-varying interference are converted into low-rank features through differential processing, periodic and regular components in received signals are clearer, periodic events and sudden events can be separated through a low-rank sparse decomposition model, human-related activities are further separated, and the accuracy of the received signals is improved. Accurate monitoring of the sudden movement of the seabed crust is realized.

In order to solve the problem that quick response and distortionless recording of ultrahigh-frequency partial discharge signals are difficult to realize when accidental pulses are generated in the prior art, the invention relates to a dual-channel parallel processing architecture for ultrahigh-frequency partial discharge signals, which comprises a signal cloning circuit and a signal processing circuit, the ultrahigh-frequency partial discharge module is used for receiving ultrahigh-frequency partial discharge signals and synchronously outputting the ultrahigh-frequency partial discharge signals as first target signals and second target signals after lossless copying; the low-gain channel circuit is used for performing buffer transmission for maintaining an original bandwidth and a dynamic range on the first target signal to generate a first gain signal; the high-gain channel circuit is used for performing gain amplification on the second target signal to generate a second gain signal; the digital signal processing unit is used for performing synchronous clock control on the low-gain channel circuit and the high-gain channel circuit; and the FPGA chip is integrated in the digital signal processing unit and is used for performing fusion splicing processing on the first gain signal and the second gain signal based on a waveform fusion splicing algorithm and generating a fusion signal.

The invention relates to the technical field of signal processing, and discloses a power equipment partial discharge signal denoising method and system, and the method comprises the steps: S1, generating an exponential decay type pulse signal simulating partial discharge, and superposing white noise and narrow-band interference into the exponential decay type pulse signal to generate a noisy signal; s2, decomposing the noisy signal into a plurality of intrinsic mode components through an ensemble empirical mode decomposition method, calculating a correlation coefficient and a kurtosis index of each intrinsic mode component, and identifying a noise component and a signal component based on the correlation coefficient and the kurtosis index; s3, wavelet threshold denoising is carried out on the noise components, and a wavelet threshold is dynamically adjusted for each noise component through a particle swarm optimization algorithm; and S4, reconstructing the de-noised noise component and the reserved signal component into a final de-noised signal, and evaluating the de-noising performance based on the signal-to-noise ratio, the root mean square error, the peak signal-to-noise ratio and the correlation coefficient.

The invention relates to the technical field of three-dimensional real-time wind speed measurement, and discloses a large-span roof three-dimensional ultrasonic anemometer and a measurement method thereof, and the method comprises the steps: building a three-dimensional coordinate system through laser ranging, and analyzing and compensating installation errors; an initial calibration coefficient is generated through a self-inspection and optimization algorithm, and the initial calibration coefficient is compared and analyzed with a standard instrument for initial calibration; ultrasonic pulse emission is controlled, full-path scanning and redundancy measurement of all axes are completed, signal quality is improved through multi-modal signal processing detection, and abnormal values are eliminated through weighted median values; the sound velocity is corrected based on real-time temperature data, the influence of humidity and air pressure on the sound velocity is adjusted through a nonlinear regression model, and a Reynolds stress correction term is introduced to compensate for sound wave path bending in an eddy current field; a three-dimensional turbulence intensity distribution diagram is constructed by fusing ultrasonic and LiDAR data, meteorological parameters are calculated, an extreme weather event is early warned by using a machine learning model, a visual three-dimensional wind speed field is provided through a cloud platform, and a potential risk area is identified.

The invention relates to a naked eye 3D binocular image acquisition and real-time processing system based on hardware synchronous triggering, and belongs to the technical field of image processing and three-dimensional display. According to the system, a hardware synchronous triggering mechanism is adopted, a time sequence synchronous control unit is used for sending a synchronous pulse signal to a binocular image sensor, and strict synchronization of left and right viewpoint image acquisition is ensured. The image signal processing unit processes collected original data, the stereo parallax correction module performs epipolar correction, and the sub-pixel interleaving module generates a composite view frame according to grating parameters of the display terminal. The system realizes high-speed data transmission through a double-buffer direct memory access DMA mechanism. The problems of visual tearing and weak stereoscopic impression caused by asynchronous binocular image acquisition in the prior art are solved, nanosecond-level synchronization precision is realized, optical crosstalk is reduced, and smoothness and comfort of stereoscopic display are ensured.

The invention discloses a peak code modulation circuit based on a dynamic memristor, which comprises the dynamic memristor and a signal conversion module, and is characterized in that the signal conversion module comprises a signal isolation module, a feature extraction module and a pulse conversion module which are connected in sequence. The dynamic memristor generates a voltage signal with a slow-rising and steep-falling characteristic under constant current input. The signal isolation module comprises a high-impedance input buffer circuit; the feature extraction module comprises an asymmetric time constant signal processing circuit used for performing enhanced extraction on the steep drop feature of the memristor output signal; and the pulse conversion module comprises a dual-threshold positive feedback hysteresis comparison circuit and is used for converting the output signal of the feature extraction module into a rectangular digital pulse. The circuit is specially designed according to the characteristics of the memristor, is simple in structure, is easy to integrate, can achieve the efficient conversion from an analog signal to a standard digital pulse, and is suitable for the fields of neuromorphic calculation and low-power-consumption signal processing.

The invention discloses a full-localization ultra-high-speed multi-channel ADC (Analog to Digital Converter) acquisition and processing platform, and relates to the technical field of signal processing. The platform comprises a high-stability clock distribution calibration module, a synchronous acquisition and pulse injection module, a pulse detection and integer deviation module, a coarse-grained translation alignment module, a sub-sampling phase extraction module, a fractional delay interpolation alignment module, a hierarchical storage and flow control module and a high-speed interface synchronous output module. Multi-channel sampling clock synchronization is realized through FPGA dynamic phase adjustment; performing coarse-grained translation by injecting calibration pulses to detect integer deviation, extracting a sub-sampling phase difference, and adopting fractional delay filtering to realize sub-sampling precision alignment; hierarchical storage and intelligent flow control are carried out according to priorities, and synchronous data flow is output through a domestic high-speed interface; through a full-flow domestic chip and a synchronous correction technology, sub-sampling precision alignment and hierarchical flow control output of a multi-channel ADC at an ultrahigh sampling rate are realized.

The invention discloses an unmanned aerial vehicle countering method and countering device for radio detection, and relates to the field of signal processing, and the method comprises the steps: scanning and capturing a transient radio frequency pulse signal through a radio frequency receiving array, carrying out the time-frequency domain conjoint analysis, constructing a signal intensity space distribution matrix, and extracting a parameter set; matching with a protocol feature library, identifying an unmanned aerial vehicle remote control link protocol type, and calculating an unmanned aerial vehicle position and a threat level in combination with a signal time difference of arrival and a frequency difference; generating adaptive interference signal parameters according to the protocol type and the threat level; the method comprises the following steps: generating a directional beam through a two-dimensional phased-array antenna, focusing the position of an unmanned aerial vehicle to transmit an interference signal, monitoring signal intensity change and protocol response delay in real time, calculating a communication suppression ratio, and iteratively optimizing an interference strategy until a suppression threshold is reached. The method has the advantages that efficient and accurate signal capture and interference are realized through multi-channel radio frequency detection, accurate positioning and adaptive interference technologies, and the countering efficiency and adaptability are remarkably improved.

The invention relates to the technical field of signal processing, and provides a time domain waveform reproduction signal smooth processing method, which is used for detecting the fatigue durability of automobile parts in a vehicle vibration acquisition system, and comprises the following steps: S1, obtaining the initial impedance of the automobile parts and multiple frames of to-be-reproduced signals; s2, calculating a first frame first driving signal, and smoothing the first driving signal to form a target driving signal; s3, calculating and generating a first driving signal of a corresponding frame based on the to-be-reproduced signal of each subsequent frame and the updated impedance corresponding to the previous stage in sequence, and forming a target driving signal; and S4, performing stress analysis on the multi-frame response signals, quantifying the damage accumulation process of the automobile part under the simulated working condition, and evaluating the fatigue durability of the automobile part. According to the invention, the generation of response pulses can be avoided, and the signal waveform reproduction precision is improved, so that the accuracy of fatigue durability detection of automobile parts is improved.

The application discloses an improved radar two-dimensional ambiguity resolution method for multi-targets, comprising the following steps: arranging point trail data after radar signal processing according to pulse repetition period from small to large; constructing a reference lookup table for resolving range ambiguity based on the arranged data; constructing a reference lookup table for resolving velocity ambiguity based on the arranged data; traversing all the frequency combinations of radar transmission, selecting N groups from M groups of frequency for multi-target pairing; obtaining a range pairing table based on the reference lookup table for resolving range ambiguity, calculating the standard deviation between rows of the range pairing table, and solving the real range of targets; obtaining a velocity pairing table based on the reference lookup table for resolving velocity ambiguity, calculating the standard deviation between rows of the velocity pairing table, and solving the real velocity of targets; and merging and processing output target data. The application can solve the problem that the traditional one-dimensional set method cannot meet the real-time requirement when the number of targets is large and the ambiguity is large.

An endoscopic imaging system for use in a light deficient environment includes an imaging device having a tube, one or more image sensors, and a lens assembly including at least one optical elements that corresponds to the one or more image sensors. The endoscopic system includes a display for a user to visualize a scene and an image signal processing controller. The endoscopic system includes a light engine having an illumination source generating one or more pulses of electromagnetic radiation and a lumen transmitting one or more pulses of electromagnetic radiation to a distal tip of an endoscope.

The invention relates to the field of sleep medicine, in particular to a wearable monitoring system for sleep-awakening rhythm disorder and a method thereof. Comprising a monitoring module, a signal processing module, a signal analysis module and an intervention scheme execution module. The monitoring module is used for acquiring collective acceleration, PPG signals and emotional state data; the signal processing module is used for filtering and down-sampling; the signal analysis module extracts time-domain and non-time-domain features by using a pulse neural network; and the intervention scheme execution module selects a personalized phototherapy and vibration intervention scheme by adopting a Q-learning algorithm according to the feature data. According to the system, through technical innovation and ingenious design, high intelligence and individuation are achieved, the sleep quality and the daytime function of the user are effectively improved, and a new tool and method are provided for sleep medical research.

The invention discloses a digital electroencephalograph, and belongs to the technical field of brain-computer interface signal processing. An electroencephalogram signal processor of the digital electroencephalograph acquires digital neural signals of a plurality of channels for a target object, wherein the digital neural signals comprise LFP signals and pulse signals; performing feature extraction on the two signals based on a unified time window and a sliding step length, and integrating a time-aligned feature matrix into a first fusion feature tensor; performing dynamic normalization processing on the first fusion feature tensor, wherein the statistical magnitude is updated along with the change of the input data; and n parallel LSTM networks are used to decode the normalized second fusion feature tensor to obtain n decoding results of different dimensions, the n LSTM networks are mutually independent, and each LSTM network has an independent optimizer and an independent parameter. According to the method, multi-modal features can be aligned in time, signal drift is compensated, decoding robustness is improved, and inter-task optimization decoupling and personalized training are achieved through independent parameters and an optimizer.

The application relates to the technical field of signal processing, data representation and classification, and discloses a radar signal spectrum clustering sorting method based on SOM anchor point extraction and graph fusion, which comprises the following steps: configuring a radar signal sorting cluster number and a radar pulse parameter, obtaining a normalized radar pulse data set, taking each normalized radar pulse in the radar pulse data set as a node, and constructing a KNN graph of the radar pulse; extracting an anchor point of the normalized radar pulse data set based on SOM, calculating the similarity between the extracted SOM anchor point and all nodes, obtaining a similarity matrix, and constructing an anchor graph adjacency matrix based on the similarity matrix, namely an adaptive anchor graph; weightedly fusing the KNN graph and the adaptive anchor graph to obtain a fusion graph; and performing spectrum clustering sorting based on the radar signal sorting cluster number and the fusion graph to obtain a sorting result. The application breaks through the limitation that a classical radar sorting clustering algorithm can only utilize distance information and density information, and improves the sorting performance under complex radar pulse distribution conditions.

The invention discloses an embedded domestic signal processing board, which relates to the technical field of signal processing circuits and comprises a power supply management module used for filtering ship electric interference through transient voltage suppression and digital ground and analog ground physical isolation and providing multi-path voltage stabilization output for wide voltage conversion; the intelligent control module is used for executing double-CAN channel dynamic switching based on physical layer monitoring and multi-mode fusion relay life prediction, and communication redundancy management and intelligent early warning are achieved; the signal processing module is used for executing high-precision current acquisition by adopting a temperature dynamic compensation algorithm and realizing pulse interference harmonic identification through real-time spectrum analysis; and the driving execution module is used for driving and controlling multiple paths of equipment through time division multiplexing and generating hierarchical light coding indication in combination with the life early warning model. According to the invention, 100% homemade replacement of ship key equipment is realized through full-link autonomous design, the reliability of the system is remarkably improved, and communication redundancy guarantee and accurate early warning of the equipment state are realized.

The invention discloses an indoor navigation positioning precision improving method and system based on a filtering algorithm, and relates to the technical field of signal processing. The method comprises the following steps: suppressing signal fluctuation and multipath interference by adopting a Bluetooth positioning technology in combination with a segmented power law regression model and Kalman filtering; ultrasonic-assisted positioning is introduced, the distance is calculated through the time difference between pulses and Bluetooth, and the anti-interference capability is improved in cooperation with temperature correction and spectral analysis; multi-mode dynamic fusion is carried out, when shielding is little, Bluetooth positioning is corrected through high-precision ultrasonic waves, when shielding is serious, Bluetooth data is smoothed through moving average, and positioning coordinates are optimized in combination with a least square method; a base station and a reference object are marked through a vector map, the position of a terminal is dynamically displayed, and positioning reliability is visually presented through an error semitransparent circle; a positioning base station array, a mobile terminal and a rear-end processing module are integrated, and low-power-consumption multi-mode fusion positioning is achieved. The method reduces the positioning error in a complex indoor environment, and is suitable for scenes such as personnel / equipment real-time tracking.

The invention discloses an echo signal processing method and device, a laser radar system and a readable storage medium, and belongs to the technical field of laser radars. The method comprises the following steps: acquiring amplitude data and receiving time data of a to-be-processed echo signal; based on the amplitude data and the receiving time data of the to-be-processed echo signal, determining a ranging value, an amplitude pulse width characteristic and an echo signal characteristic of the to-be-processed echo signal; comparing the ranging value and the amplitude pulse width characteristic with a non-target judgment threshold to obtain a first comparison result, and judging whether the echo signal to be processed is a non-target echo signal based on the first comparison result; under the condition that the to-be-processed echo signal is a non-target echo signal, determining an abnormal type of the to-be-processed echo signal according to the echo signal characteristics; and processing the to-be-processed echo signal based on the abnormal type of the to-be-processed echo signal. According to the method, the accuracy of point cloud display can be improved.

The invention discloses an analog signal pulse encoding device based on event driving and an analog signal processing method, and the device comprises a signal conditioning module which comprises at least one conditioning unit, and the conditioning unit is used for receiving an analog signal, carrying out the front-end analog conditioning of the signal, and outputting an analog conditioning signal; the threshold comparison module is connected with the signal conditioning module and is used for carrying out threshold detection on the analog conditioning signal according to a set threshold and then outputting a threshold comparison signal; the event triggering module is connected with the threshold comparison module and is used for triggering a pulse event signal corresponding to the analog conditioning signal according to the threshold comparison signal; and the pulse coding module is connected with the event triggering module and is used for converting the pulse event signal into a pulse coding signal by adopting a pulse coding mode. According to the invention, by introducing the threshold comparison module and the event trigger module at the front end of the device, invalid sampling can be effectively avoided, a large amount of redundant data can be reduced, and power consumption, communication and storage pressure and burden can be reduced.

The invention provides a direct-current support capacitor capacitance online identification method based on multi-frequency-point collaborative analysis, and relates to the technical field of direct-current support capacitors, and the method comprises the steps: collecting a ripple voltage signal and a ripple current signal; determining a delay step length, and constructing a pulse weight sequence based on the delay step length; performing discrete convolution operation on the pulse weight sequence, the ripple voltage signal and the ripple current signal, and extracting a periodic signal; performing signal processing on the periodic signal, and extracting a signal amplitude; determining an optimal parameter combination; an optimized amplitude value is obtained; calculating a first capacitance value and a second capacitance value according to the amplitude relation; and performing multi-frequency-point collaborative analysis based on the first capacitance value and the second capacitance value, and determining an actual capacitance value of the DC support capacitor. According to the method, high-precision extraction is carried out on signals of different frequency points through adaptive time slot pulse weighting, synchronous demodulation and integral filtering processing, and rapid and accurate identification of capacitance parameters of the direct-current support capacitor is realized in combination with a multi-frequency-point collaborative analysis mechanism.

The invention provides a non-cooperative measurement and control signal carrier recovery method and device based on pseudo code jump edge detection, and belongs to the technical field of radar signal processing, and the specific process is as follows: setting the stepping amount of a local timing synchronization pulse accumulator, and when the accumulated value of the timing synchronization pulse accumulator is greater than a set threshold value, stopping the stepping amount of the local timing synchronization pulse accumulator; the accumulator outputs a timing synchronization pulse signal; controlling a sliding accumulator by using a synchronization pulse signal to perform sliding accumulation on a constellation module value # imgabs2 # calculated by the # imgabs0 # baseband signal and the # imgabs1 # baseband signal, and further obtaining a synchronization pulse capture offset for coarse synchronization of a timing synchronization pulse; obtaining a correlation value of a # imgabs3 path baseband signal and a # imgabs4 path baseband signal under the control of a timing synchronization pulse after coarse synchronization, obtaining a timing error by using a timing error discriminator, and further obtaining a stepping amount of a synchronization pulse accumulator; and realizing carrier recovery by using the stepping amount of the synchronization pulse accumulator.

The invention discloses a navigation signal blind separation method, system and equipment in an alpha pulse interference environment based on Gaussian kernel filtering, and a medium, and aims to improve the signal processing performance in a complex interference environment. According to the method, alpha pulse interference in aliasing signals is suppressed by adopting a Gaussian kernel filtering technology, and effective suppression of the alpha pulse interference is realized by reasonably designing filtering parameters; two correlation matrixes are subjected to joint diagonalization, and a joint diagonal matrix is used as an initial value of a left aliasing matrix and a right aliasing matrix in a blind separation algorithm, so that the convergence speed of aliasing matrix estimation is effectively improved; then, separating the signals after the pulse interference is suppressed by using a blind separation algorithm of joint diagonalization and an initial value of a left and right aliasing matrix; experimental results show that the method has excellent performance in the aspects of suppressing impulse noise influence and signal separation, and the problems that a traditional method is insufficient in alpha impulse interference suppression and poor in signal separation performance are effectively solved; systems, devices, and media are used to implement the methods.