939 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 provides a laser radar and gamma camera integrated detection system based on a shared SiPM array, and belongs to the field of detector equipment. The system comprises a laser emission module, a gamma camera, an optical module, an SiPM array detection module, a signal processing module and a control module. Wherein the optical module controls high-frequency pulse laser of the laser emission module to scan a target scene, respectively guides a reflected laser beam and a scintillation light signal emitted by the gamma camera to the SIPM array detection module for photoelectric conversion to generate an electric signal, and performs gain and time gate adjustment according to a sensor working mode to obtain a first electric signal; the signal processing module receives the first electric signal and carries out laser radar ranging calculation and gamma camera imaging processing to obtain three-dimensional point cloud data and a radioactivity distribution image of the target scene. According to the invention, efficient fusion of functions of the laser radar and the gamma camera is realized, the size and weight of the system are greatly reduced, and the manufacturing and maintenance cost is also reduced.

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 discloses a two-dimensional smart noise interference method based on a centralized MIMO radar, and belongs to the technical field of radar communication.The method comprises the steps that down-conversion processing is carried out on radar transmitting signals intercepted by a digital radio frequency memory through a jammer, and the radar transmitting signals are subjected to down-conversion processing; periodic sampling is carried out on each pulse of a signal transmitted by an enemy through intermittent sampling to form a plurality of slices, then smart noise interference modulation is carried out in a distance dimension and a speed dimension, and finally, up-conversion processing is carried out on a modulation signal, so that a forwarding type two-dimensional smart noise interference signal is formed. After an MIMO radar receives an interference signal, a result obtained by a conventional signal processing method is seriously influenced by the interference signal generated in the invention. According to the method, smart noise interference is applied to an enemy radar signal in the distance dimension and the speed dimension, and an intensive false target is successfully generated, so that the detection of the MIMO radar on a real target is interfered.

The invention provides an ultrasonic-based surface density measurement method and system and electronic equipment, and relates to the technical field of signal processing. According to the method, an integral value of voltage and time of an ultrasonic pulse signal is monitored in real time to serve as a reference value of the ultrasonic pulse signal; and then the duty ratio of the ultrasonic pulse signal is adjusted by using the adjustment strategy determined by the reference value, so that the output voltage of the ultrasonic pulse signal is adjusted by using the integral value, the stable output of the ultrasonic pulse signal is realized, and a data drift error caused by external factors can be effectively inhibited.

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 discloses a cloud and mist particle acquisition probe based on interference particle imaging, and the probe comprises a sheet-shaped laser emission unit which is used for emitting sheet-shaped pulse laser beams, expanding the laser beams, adjusting the incident position and the incident angle, and irradiating cloud and mist particles to generate scattered light signals; the scattered light signal acquisition unit is used for collecting scattered light signals and recording the scattered light signals on the camera; the mechanical unit comprises a first measuring arm used for installing the sheet-shaped laser unit and a second measuring arm used for installing the scattered light signal acquisition unit, and the first measuring arm and the second measuring arm are connected through a connecting section and are installed on the base; and the signal processing system is used for processing the scattered light interference signal recorded by the camera to obtain cloud and mist particle parameters. The acquisition probe provided by the invention ensures stable operation of a photoelectric system in a low-temperature complex and severe cloud environment, improves the accuracy of interference particle imaging measurement, and realizes real-time measurement of cloud particle parameters suitable for different industrial scenes.

The invention discloses a distributed optical fiber temperature measurement system, which comprises a light source device, a sensing optical fiber, an optical signal processing device, a data acquisition device, a signal processing and computing device, a display and alarm device, a communication and data processing device and a system control center, a plurality of light sources emit light pulses to enter the sensing optical fiber, the sensing optical fiber converts temperature changes into optical signals, the optical signals are converted into electric signals through the optical signal processing equipment, the electric signals are converted into digital signals through the data acquisition equipment, and then the digital signals are transmitted to the signal processing and calculating equipment to be processed to obtain temperature values. The temperature value is transmitted to the display and alarm device, sound-light alarm is triggered when the temperature is abnormal, and data is transmitted to a remote control center to be monitored and managed by means of the communication and data processing device. According to the invention, the sensitivity and the response speed of temperature measurement can be improved by setting a synchronous control technology and assisting cooperation of a plurality of light sources.

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 provides a signal processing method for radioactivity detection equipment and the radioactivity detection equipment, and the signal processing method for the radioactivity detection equipment comprises the steps: analyzing a collected nuclear pulse signal, and obtaining pulse amplitude information; performing spectrum stabilization according to the pulse amplitude information to obtain a spectrum-stabilized energy spectrum; and determining a nuclide identification result and a dose rate calculation result based on the spectrum-stabilized energy spectrum. According to the technical scheme, on one hand, the current environment dose rate level can be determined, it is ensured that the radiation dose received by workers is within the safety limit value, and therefore the radiation risk can be reduced, and the health and safety of the workers are guaranteed; and on the other hand, specific radionuclides can be identified, so that the pollution source can be determined.

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 provides a signal processing method for a partial discharge signal and a related device, and the method comprises the steps: carrying out the frequency band extraction of a first sound pulse signal, and obtaining a second sound pulse signal corresponding to an audible sound frequency band and a third sound pulse signal corresponding to an ultrasonic frequency band; determining a first time domain waveform of the second sound pulse signal, and determining a second time domain waveform of the third sound pulse signal; determining a first frequency domain waveform of the second sound pulse signal, and determining a second frequency domain waveform of the third sound pulse signal; inputting the first time domain waveform and the second time domain waveform into a first convolutional neural network model for feature extraction to obtain an image feature vector; inputting the first frequency domain waveform and the second frequency domain waveform into a second neural network model for feature extraction to obtain a voiceprint feature vector; splicing the image feature vector and the voiceprint feature vector to obtain a target feature vector; and inputting the target feature vector into a classification network to obtain a target classification result.

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.

The embodiment of the utility model provides a weather radar standard signal processor. The method is applied to radar technology. The signal processor comprises a signal processing unit, a signal control transmitting unit, an acquisition unit and a data storage and transmission unit; wherein the signal processing unit generates an intermediate frequency signal and sends the intermediate frequency signal to the signal control emission unit, the signal control emission unit generates an emission signal according to the received intermediate frequency signal, and the acquisition unit comprises five A / D converters, the four A / D converters are used for collecting high-gain / low-gain echo signals returned by transmitting signals in the horizontal channel / vertical channel and converting the high-gain / low-gain echo signals into digital signals, the remaining A / D converter is used for collecting transmitting pulses of the transmitting signals, generating transmitting sample signals and converting the transmitting sample signals into digital signals, and the collecting unit sends the generated digital signals to the signal processing unit. The signal processing unit carries out signal processing on the received digital signals and sends data after signal processing to the data storage and transmission unit, and the data storage and transmission unit stores the data after signal processing or sends the data to other systems / devices according to needs. In this way, data transmitted / received by radars of various models can be subjected to unified and normative standardized processing to realize functions of radar control, signal processing, calibration control and the like, so that the networking radar data quality has consistency, the networking radar data quality and the calibration precision of part of key parameters are improved, the calibration time interval is shortened, and the calibration efficiency is improved. In addition, the used standardized interface can transmit signals to radar transmitters / receivers of different models according to needs.

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 provides an automatic gain control method and circuit of an ultrasonic flow metering device, and aims to improve the accuracy and stability of flow metering. According to the method, the gain is automatically adjusted by measuring the pulse width of an echo signal and comparing the pulse width with an expected value. The circuit comprises a transmitting circuit, an ultrasonic transducer, a variable gain amplifier, a variable threshold comparator, a zero-crossing comparator, a flight time measuring unit, a pulse width measuring unit, a time-to-digital converter and a calculation and control unit. According to the scheme, independent gain configuration of uplink and downlink flight time and a fine gain adjustment strategy based on echo amplitude change can be realized. In addition, by setting the allowable maximum pulse width change value, whether the measurement error is within a reasonable range can be automatically judged, and re-measurement can be carried out when necessary. According to the integrated design scheme, the flexibility and the response speed of measurement are improved, the signal processing flow is optimized, and an innovative solution is provided for ultrasonic flow metering.

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.