692 results about "Peak detection" patented technology

The invention relates to the technical field of power equipment state detection, in particular to an ultrahigh-frequency partial discharge online detection system, method and device and a medium, and the system comprises the steps: collecting an initial discharge signal in real time through an ultrahigh-frequency sensor array, and carrying out the preprocessing of the initial discharge signal, so as to obtain an ultrahigh-frequency discharge signal; carrying out peak detection on the ultrahigh-frequency discharge signal, and triggering a high-speed analog-to-digital converter to collect an original waveform when the amplitude exceeds a preset threshold value; performing multi-dimensional feature extraction on the original waveform by using a digital signal processor to obtain multiple groups of dimensional features; identifying and classifying the multiple groups of dimension features based on a random forest algorithm, generating discharge type labels and confidence coefficients, and storing the discharge type labels and the confidence coefficients in a dynamic database; carrying out spatial position calculation on the ultrahigh-frequency discharge signal by adopting a time difference method, and determining a three-dimensional coordinate of a discharge source; the dynamic database and the three-dimensional coordinates of the discharge source are subjected to space-time correlation and multi-dimensional analysis, a defect analysis result is generated, and high-precision online detection of the partial discharge defect of the high-voltage equipment is achieved.

The invention relates to the technical field of valve leakage detection, and particularly discloses an ultrahigh pressure gas valve leakage detection method and system. According to the method, a unified leakage feature vector is obtained through multi-source acquisition and processing; capturing a time sequence dependency relationship, and determining a micro leakage mode; carrying out abnormal peak detection to obtain a preliminary leakage probability; combining the initial leakage probability with real-time environmental parameters, and dynamically adjusting a judgment standard; comparing the unified leakage feature vectors through a judgment standard, fusing position coordinate triangulation positioning, judging whether micro crack leakage occurs or not, and obtaining leakage position estimation; the historical data sequence is fused, the micro crack development trend is predicted, and the early warning level is determined; and generating a corresponding response signal according to the early warning level, and outputting micro crack leakage early warning. Multi-source data fusion, dynamic threshold adjustment and position prediction can be carried out, the accuracy and robustness of micro crack leakage detection are remarkably improved, and efficient guarantee is provided for safe operation of a pipeline.

The invention relates to the technical field of digital control switching power supplies, and particularly discloses a switching power supply dynamic response adjusting system based on digital control, which comprises a digital controller, a multi-channel analog-to-digital conversion module, a parameter identification module, a self-adaptive control law adjusting module, a pulse width modulation driving module and a stability monitoring module. On-line identification of key parameters of a system is realized by constructing a nonlinear state space model and combining an extended Kalman filtering algorithm, dynamic compensation is carried out for non-minimum phase characteristics such as a right half plane zero point, and a self-adaptive control law adjustment module optimizes a control strategy in real time according to an updated model. A Lyapunov stability criterion and a predictive control mechanism are introduced, the robustness and response speed of the system are improved, and a stability monitoring module identifies an abnormal state through sliding window variance analysis and peak detection and triggers a fault-tolerant mechanism to guarantee safe operation of the system.

The invention discloses an ion chromatography wave crest boundary extraction method based on fitting residual and tangent judgment, and belongs to the technical field of ion chromatography analysis. Comprising the following steps: S1, reading an original waveform data sequence, and executing frequency reduction sampling according to a set step length; s2, calculating the slope of the data after underclocking sampling by using a difference method, and searching positive and negative slope sections by performing first-order derivation on the waveform after underclocking sampling; s3, noise interference is eliminated, slope areas are grouped, then a chromatographic peak detection limit value is set, and an effective peak left section and an effective peak right section are screened out; s4, combining the effective wave crest left side section and the effective wave crest right side section to obtain an effective wave crest and a preliminary left boundary point and a preliminary right boundary point of the effective wave crest; s5, fitting a straight line through the preliminary left boundary point and the preliminary right boundary point to position an error integral region; and S6, updating the optimal boundary point by traversing the evaluation indexes of all points in the error integral region. The boundary search range is more accurate, and the calculation efficiency is higher.

There is described an artificial intelligence wearable ECG skin patch (400) to detect sudden cardiac arrest. The wearable ECG monitoring patch (400) with AI based predictive analytics and remote based cardiac monitoring (615) system that can detect cardiac arrhythmias automatically in real-time and make a diagnosis with AI models trained with acquired data. The wearable skin has a biocompatible polymer patch (400) which captures the electrical signal through a flexible printed electronic technology based conducting ink and a substrate. The microcontroller controls (201), store and transmit the data packets. The IoT connected signal transmission is capable of recording and transferring the data packets through wireless communication. The AI engine is capable of analysing, evaluating, testing and providing the data packets of sudden cardiac arrest through a peak detector algorithm. The ECG skin patch (400) to detect and measure the sudden cardiac arrest with the R-R interval time series to obtain heart rate variability.

The invention relates to the technical field of medical data processing, and provides a medical image data processing method based on deep learning, which comprises the following steps of: acquiring data according to an acquisition template, extracting a pulse time sequence by self-adaptive threshold peak detection, calculating an instantaneous phase according to linear interpolation, calculating a statistical magnitude, comparing a quantitative index with a preset threshold value, and calculating a pulse time sequence according to the statistical magnitude. Judging a steady state by combining a peak loss rate and an abrupt change detection rule, and calculating phase consistency between channels for verification; the method comprises the following steps of: splitting acquired data according to a concept entity to form a data relation model, implementing rapid global rigid estimation and applying affine transformation, estimating a pixel-level displacement field by adopting a pyramid dense optical flow network, applying the displacement field to an original pixel, and performing time domain fusion by taking optical flow confidence and a registration residual error as weights; and cutting the short-time image stabilization sequence after registration compensation, and outputting a pixel-level risk thermodynamic diagram, a candidate focus list and each output confidence interval by taking a hybrid network of a convolution front end and a space-time Transform backbone as a prediction model.

The invention discloses a channel-configurable liquid particle pulse amplitude detection method and a related device, and relates to the field of digital signal processing, and the method comprises the following steps: eliminating a background noise reference value of a digital pulse signal, presetting a dynamic threshold value, filtering a noise signal of which the amplitude value is lower than the dynamic threshold value in the digital pulse signal, and obtaining a channel-configurable liquid particle pulse amplitude detection result; obtaining a baseline correction digital pulse signal; when the amplitude of the baseline correction digital pulse signal exceeds a dynamic threshold for the first time, pulse counting is started, peak detection is carried out on the baseline correction digital pulse signal, and a pulse peak value and a peak value position corresponding to a pulse event are obtained; a channel threshold parameter is preset through an upper computer, a plurality of independent channels are divided, pulse events are loaded into the corresponding independent channels to be accumulated, a channel count value and corresponding particle size distribution data are obtained, and liquid particle pulse amplitude detection is completed. The problem that the number of channels and threshold parameters cannot be dynamically adjusted when a current hardware circuit is used for liquid particle pulse amplitude detection is solved.

The invention discloses a chip interface safety protection control circuit, which relates to the technical field of chip interface protection, and comprises a power supply control module which is used for carrying out rectification filtering and voltage stabilization processing on accessed electric energy, meeting power supply requirements, carrying out overcurrent detection, constant current regulation and overcurrent power-off protection control, and carrying out power-off protection on the power supply control module during power-off protection. The interface voltage of the chip module is lowered, the interface sampling module can carry out sampling and peak detection on pulse signals accessed or output by the chip module, the state detection module can judge the type of the pulse signals, namely square wave pulses or sine pulses, and the first sampling module and the second sampling module carry out peak sampling according to the type of the pulse signals. The micro-control module controls the threshold value setting module to set a comparison threshold value, then the abnormity detection module detects the peak value state of the pulse signal, and when the peak value state is larger than the normal peak value state, chip interface protection is carried out. The chip interface safety protection control circuit can automatically carry out interface signal detection and interface protection control.

The invention discloses a voice interactive chart dynamic generation method and system based on a large language model, and relates to the technical field of chart generation, and the method comprises the steps: collecting a user voice signal, carrying out the preliminary framing, calculating the short-time energy, and analyzing a mute segment set signal; frequency domain signals are extracted from the set signals, gain is calculated through a filter, noise reduction is carried out on the frequency domain signals, the zero-crossing rate and noise reduction short-time energy are calculated, effective voice frames are screened, peak detection is carried out, the average voice speed is calculated, voice speed normalization is carried out, and signal values of sampling points in the frames are extracted. According to the method, the noise power spectrum density is extracted through FFT on the mute section, a frequency domain model of background noise is effectively established, a follow-up filter can accurately act on an actually existing frequency band interference area, weakening of the voice main signal spectrum is avoided, the Mel filter bank is accessed after the power spectrum is calculated through the FFT after frame windowing, and the noise power spectrum density is calculated through the FFT after frame windowing. Energy can be redistributed on the logarithmic Mel scale according to human ear perception characteristics.

The invention discloses a digital gain adjustment control circuit which comprises a power detector, a digital peak detector, a gain control module and a digital gain adjustment module. The power detector calculates the power of an input signal by adopting a smooth root-mean-square algorithm, and rapidly adjusts a gain coefficient according to different step lengths adapted to regions; the digital peak value detector adopts a sliding window maximum value method to detect the peak value of an input signal, carries out statistical counting on the overload and underload states of the peak value based on a two-stage method, and judges and adjusts the gain according to a comparison result with a threshold value, so that the influence of frequent gain refreshing on the AGC loop state is avoided, and the loop stabilization time is shortened. Flexible algorithm upgrading and parameter configuration are supported by adopting a full-digital framework, different communication standards are adapted through firmware updating, the limitation of single index control is solved through a dual-detection cooperative working mode, peak overshoot is effectively restrained while the average power of the system is kept stable, the system is conveniently integrated to an SoC chip through modular design, and the reliability of the system is improved. And the power consumption and the size are greatly reduced.

The invention discloses an LC-MS peak detection method, device, equipment and medium, and the method comprises the steps: firstly obtaining an original data set of an environment sample collected by an LC-MS instrument, extracting and adjusting peak detection parameters, and determining a plurality of peak regions and characteristic parameters thereof; generating a synthetic peak region and synthetic characteristic parameters which are consistent with the real peak region in characteristic parameter distribution by using a conditional generative adversarial network, and then constructing an LC-MS peak detection model comprising a peak region classification model and a peak boundary defining model through a lightweight multi-task convolutional neural network based on the characteristic parameters and the synthetic characteristic parameters; and finally, inputting to-be-detected sample data into the model to obtain a detection result. According to the method, peak detection parameters are directly extracted from original data and dynamically adjusted, classification of peak regions and peak boundary integration are synchronously completed in combination with the improved lightweight multi-task convolutional network, the real-time detection requirement is met, and finally high-precision detection of real positive peaks is achieved and the noise amount is remarkably reduced.

The invention discloses a chromatographic data optimization processing method for a liquid chromatograph, and relates to the technical field, and the method comprises the following steps: collecting an original signal flow, carrying out preliminary peak detection, and generating an original peak list; extracting modal exclusive characteristics of each chromatographic peak; converting the modal exclusive features into a unified multi-dimensional semantic feature vector; calculating a time interval weight, and calculating a semantic relevancy weight based on the multi-dimensional semantic feature vector; correcting the time interval weight, generating a network edge weight, and constructing a peak correlation topology network by taking the multi-dimensional semantic feature vector as a node; identifying node clusters connected with high edge weights, and aggregating the node clusters into candidate compound entities; tracking a node signal intensity change track, and adding a conflict mark; conflict resolution arbitration is carried out on the candidate compound entities with the added conflict marks, dominant detector evidence is output, and an analysis report is generated. According to the method, the problems of poor data collaboration of multiple detectors, inaccurate peak identification and association and isolated data processing flow are effectively solved.

The invention provides a permanent magnet synchronous linear motor, a control system and a position resolving method thereof, and relates to the technical field of motor control. The method comprises the following steps of: firstly, equidistantly arranging at least two pairs of linear Hall sensors with an electrical angle difference of 90 degrees and overlapped detection intervals along a stator, and acquiring orthogonal voltage to calculate an instantaneous position angle; the sensor pairs are dynamically switched through peak judgment and spliced to obtain the full-stroke continuous absolute position, and the instant speed is obtained through difference; the position and the speed are respectively input into a position loop, a speed loop and a current loop, and vector closed-loop control is realized by driving an inverter through SVPWM, so that high-resolution position and speed feedback is provided in the whole stroke, and the dynamic response and positioning precision of the linear motor are remarkably improved.

The invention belongs to the field of high-precision time calibration and navigation positioning, and discloses a rubidium atomic clock calibration method based on a Rowland system and a related device. Spectral analysis is performed based on a Welch method and an adaptive peak detection method so as to accurately identify frequency, amplitude and phase parameters of periodic components, then a mixed time difference model including a secondary trend term, a multi-period term and a noise term is constructed, and the model is solved by adopting a least square method so as to obtain key performance parameters of the rubidium atomic clock. And finally completing time calibration of the Rowland system taming rubidium clock. By adopting the method, the parameter estimation precision of the rubidium clock is effectively improved, the problems of mode aliasing, noise sensitivity, non-unique result, low calculation efficiency and the like are solved, and reliable and real-time calibration of the rubidium atomic clock by the Roland system is realized.

The invention discloses a pulling and lifting cable frequency detection and cable force measurement method and system based on a millimeter wave radar, and belongs to the field of pulling and lifting cable force measurement. The method comprises the steps that vibration signals are collected through the millimeter wave radar to obtain complex data streams, time-frequency analysis is conducted on the complex data streams, and an interference model is established; the method comprises the following steps: reconstructing a noise-reduced vibration signal by adopting adaptive filtering, extracting candidate vibration frequencies through power spectral density estimation and spectral peak detection, calculating corresponding stability scores, and obtaining a first verification factor used for evaluating wind disturbance and a second verification factor used for evaluating vibration frequency deviation; according to the method, through multi-source sensing data fusion and self-adaptive signal processing, complex environment interference is effectively overcome, non-contact high-precision cable force measurement is achieved, and the method has the outstanding advantages of being high in anti-interference capacity, high in measurement reliability and the like.

The invention relates to a health index monitoring tooth socket and a monitoring method thereof, and the method comprises the steps: collecting an optical signal in an oral cavity in real time through a collection module, and extracting a DC component and an AC component from the optical signal; and evaluating the signal quality of the direct-current component and the alternating-current component according to the standard signal proportion, and obtaining a target direct-current component and a target alternating-current component which meet the standard signal quality. On the basis of the cross correlation between the target direct-current component and the target alternating-current component, the blood oxygen saturation health index is obtained through a piecewise function. Based on the target alternating component, the heart rate health index is obtained through peak value detection. The problem of low monitoring accuracy of a monitoring method for monitoring health indexes in related technologies is solved.

The utility model relates to the technical field of satellite navigation, in particular to a satellite navigation anti-interference signal intensifier, which comprises a receiving antenna, a prefilter, a fixed amplification module and an automatic gain module which are sequentially connected, the output end of the fixed amplification module is further connected with a control module, and the control module comprises a peak value detection unit and a switch control unit. Two output ends of the switch control unit are connected with a control end of the automatic gain module, the peak detection unit is used for detecting a signal peak value, and the switch control unit controls the amplification factor of the automatic gain module based on the signal peak value output by the peak detection unit. According to the utility model, the prefilter is used for filtering interference signals, then the peak value detection unit is used for judging the magnitude of the signals, and then the switch control unit is used for selecting different resistors, so that the amplification factor of the automatic gain module is changed, the signals are enhanced, the final signals are in a proper range, subsequent signal processing is facilitated, and the practicability is higher.

The invention discloses an underwater sound double-expansion channel parameter estimation method based on Newton orthogonal matching pursuit. The method comprises the following steps: firstly, realizing frame synchronization by using a cross-correlation peak of an LFM signal and a received signal; a coarse estimation value of a Doppler coefficient is obtained on a discrete time frequency grid through an ambiguity function method by utilizing the self-correlation characteristic of m-sequence pilot frequency, multipath time delay of a channel is detected by utilizing a matched filtering peak value of a signal after frequency offset compensation, and a coarse estimation result of the channel is obtained; executing Newton iteration optimization in a continuous parameter space by adopting a Newton orthogonal matching pursuit algorithm to realize super-resolution off-grid estimation of the Doppler coefficient of the first data block; and finally, proposing an iterative block tracking strategy, initializing the compensation of the rear block through the estimated value of the front block, and updating the time-varying Doppler coefficient by using the balanced signal feedback to realize the dynamic tracking of the time-varying Doppler coefficient. According to the invention, the Doppler estimation root-mean-square error is obviously reduced, and the calculation efficiency is high.

The invention relates to the technical field of medical equipment, in particular to a high-voltage electric field electrocardio synchronous pulse triggering method and a pulse electric field ablation system. The method comprises the following steps: in response to starting of target equipment, performing feature sampling on a target object to obtain a feature sampling signal; the feature sampling signals are processed based on a preset detection algorithm, waveform features in the electrocardiosignals are obtained, the detection algorithm is achieved based on a dynamic integral window length and a dynamic peak detection threshold value, and the dynamic integral window length and the dynamic peak detection threshold value are determined based on a basic threshold value in the associated updating period and historical feature sampling signals; determining target wave crest information in the electrocardiosignal based on the waveform characteristics, and generating a pulse driving time sequence signal matched with the target wave crest information; and driving target equipment based on the pulse driving time sequence signal to realize electrocardio synchronous pulse triggering. By adopting the method, the real-time performance, the accuracy and the stability of pulse triggering can be improved.

The invention discloses an ice layer thickness measuring method and device and relates to the field of radar technology and electromagnetism. According to an existing ice thickness detection technology, additional instruments need to be arranged on an ice cover, the complexity and cost of equipment are increased, the requirement for the environment is high, and in order to solve the technical defects existing in the prior art, the technical scheme provided by the invention is that the ice layer thickness measurement method comprises the steps of collecting a preset algorithm and algorithm parameters; a step of preprocessing the collected high-frequency electromagnetic wave echo signal according to the preset algorithm; carrying out peak detection on the preprocessed high-frequency electromagnetic wave echo signal; a step of obtaining a horizon detection result of the preprocessed high-frequency electromagnetic wave echo signal according to a peak value detection result; and obtaining the thickness of the ice layer according to the result of the layer position detection. The method can be applied to ice layer thickness measurement and ice cover bearing capacity calculation.

The invention discloses a wireless ranging method and system based on a programmable logic architecture, and belongs to the technical field of indoor positioning, and the method comprises the following steps: receiving an original data frame of a processing module, adding a synchronization frame header and a synchronization frame tail, then carrying out linear frequency modulation spread spectrum coding to form a ranging request frame, recording the sending time, and sending the ranging request frame to a target receiving end; after a ranging response frame is received, a decoded data frame is generated through decoding processing such as time domain filtering and peak detection, coherent accumulation is carried out by taking a first target code element as a reference, a target array is extracted, interpolation refining is carried out to obtain a fine time component, and the arrival time is obtained through multipath elimination. According to the method, main signal energy is enhanced through coherent accumulation, multi-path interference is suppressed in combination with interpolation refinement and time domain filtering, the time measurement precision is improved, and software and hardware cooperative efficient distance measurement is realized.

The invention discloses a carriage groove positioning and steel coil placement center determining method based on three-dimensional point clouds, and relates to the technical field of industrial automation, and the method comprises the steps: firstly carrying out the preprocessing of an original point cloud, and extracting a carriage main body point cloud through ground removal, outlier filtering and DBSCAN clustering; on the basis, the overall orientation of the carriage point cloud is determined through principal direction analysis, a central area point cloud is obtained through cutting in the principal direction, and after x and z coordinates of the central area point cloud are extracted, groove valley points are positioned through sliding window calculation, Gaussian smoothing and peak value detection. As the size of the compartment groove is generally larger than that of the steel coil, in order to guarantee the loading safety of the steel coil, sole timbers need to be arranged on the edge of the groove, so that the sudden drop point of the z value is detected forwards based on the valley point, and the edge position of the groove is determined. And calculating the center coordinate of the steel coil to be placed by combining the edge of the groove, the size of the sole timber and the radius of the steel coil, and finally mapping the two-dimensional detection point back to a three-dimensional space by using KD tree nearest neighbor search to obtain the three-dimensional coordinate of the steel coil placing center.

The invention discloses a cable elbow-shaped head ponding recognition method based on knocking peak alignment and wavelet scattering, and belongs to the technical field of voiceprint recognition. Comprising the following steps: receiving a cable elbow type terminal knocking sound signal, realizing a knocking signal peak alignment algorithm through knocking peak value detection, windowing processing and signal mirror image filling, and outputting an alignment sound signal; wavelet scattering coefficients are extracted from the aligned sound signals to serve as characteristic parameters, and a voiceprint characteristic parameter set under the corresponding ponding degree is obtained; inputting the voiceprint characteristic parameter set into an LSTM model for training, outputting a water level discrimination label, and obtaining a water level state recognition model through hyper-parameter optimization; and identifying the water accumulation state of the cable elbow-shaped head by using a water level state identification model. Safety risks caused by water inflow of the elbow-shaped connector can be avoided, manpower and material resource cost consumption caused by a traditional maintenance mode is remarkably reduced, and the elbow-shaped connector is of great significance in improving operation safety of an electric power system.

The invention discloses a multi-scale time sequence modeling video abstract generation method fusing semantic enhancement and boundary perception, and belongs to the technical field of computer vision. The method comprises the following steps: carrying out feature coding on an input video frame sequence, and extracting a corresponding time sequence feature representation; inputting the extracted time sequence features into a video abstract generation model, and outputting importance scores by the model; performing time sequence smoothing and peak value detection on the importance score, and determining a key frame candidate set; and generating a final video abstract fragment based on the key frame candidate set in combination with a non-maximum suppression and fragment combination strategy. Experimental results obtained on reference data sets SumMe and TVSum prove the advancement of the method. According to the video abstract generation method provided by the invention, the problems of fuzzy event boundary and insufficient multi-scale time sequence understanding in the existing video abstract generation method can be effectively solved.

The application discloses a radar plot and AIS track adaptive parallel matching method and system, and belongs to the technical field of radar and navigation information. In order to reduce the algorithm complexity and the dependence of AIS data, the application comprises the following steps: identifying the database arrival data, performing voting on the projected radar plot in a parameter space by a system error extraction module based on an error distribution function to obtain a plurality of counters and filtering the counters by a filter, finally accumulating the results of all the filters and performing peak value detection to extract the system error of the radar plot; performing speed correlation checking on the searched radar track point by a radar plot index module, and searching the radar track point with a speed parameter meeting the requirements; performing sum and optimization on an error function according to a PARZEN window based on the radar track point with the speed parameter meeting the requirements by an error function optimization module; and updating the membership ship number in the AIS table of the database by using the radar track point with the speed parameter meeting the requirements.

The invention discloses a magnetoelectric speed sensor signal acquisition circuit and a fault diagnosis method. The magnetoelectric speed sensor signal acquisition circuit comprises a low-pass filter circuit, an amplitude limiting circuit, a lifting and adjustable amplifying circuit, a self-adaptive peak detection circuit, a threshold adjusting circuit, an in-phase hysteresis comparison circuit, a fault detection circuit and a single chip microcomputer module. The lifting and adjustable amplifying circuit is used for lifting the peak value of the signal subjected to amplitude limiting in a bias manner and amplifying the signal by a certain multiple; the self-adaptive peak detection circuit is used for detecting and acquiring a peak voltage; the threshold adjusting circuit is used for dividing the peak voltage; the in-phase hysteresis comparison circuit is used for comparing two paths of input signals and outputting a square wave signal to the single chip microcomputer module to obtain a signal frequency value; the single-chip microcomputer module is used for controlling switching of amplification times based on the signal frequency value and controlling fault detection of the magnetoelectric speed sensor. The amplification factor is automatically switched based on the signal intensity, the threshold voltage of the comparator is dynamically adjusted according to the signal peak value, and the detection reliability is improved.

The invention discloses a resonant converter output overload and short circuit protection system and method without output current detection, and belongs to the technical field of power electronic converters. When a resonance tank current peak detection signal is equal to a ramp signal to trigger a comparator to output a high-level pulse, the edge triggers the microcontroller to interrupt, and the register value of the current ramp signal is captured immediately after interruption, so that a resonance current peak can be obtained. After an output overload and short circuit fault mark based on the value and the output voltage is triggered, the switching frequency is adjusted through the slope parameter self-adaptive controller to achieve output overload protection, and when the output overload is serious or short circuit occurs, rapid wave sealing protection can be achieved through a software code and a hardware comparator. And meanwhile, the soft start function of the resonant converter can be realized by gradually decreasing the initial value of the set slope descent rate cycle by cycle during starting. The control performance of the resonant converter is improved under the control of the peak current, and the output overload and short circuit protection function can be realized without adding an output current detection circuit.

The invention discloses a fundamental frequency detection method, device and equipment and a storage medium, and relates to the technical field of audio processing, and the fundamental frequency detection method comprises the steps that time domain preprocessing is carried out on a multi-frame splicing signal to obtain first time domain preprocessing data, and the time domain preprocessing comprises filtering processing, clipping processing and windowing processing; performing fast Fourier transform on the first time domain preprocessed data to obtain preprocessed frequency domain signal data; carrying out peak detection on the preprocessed frequency domain signal data to obtain candidate fundamental frequencies; and performing harmonic matching on the candidate fundamental frequency based on a preset frequency deviation range to obtain a support degree score of the candidate fundamental frequency, and determining a fundamental frequency detection result according to the support degree score. According to the scheme, the stability and the accuracy of the fundamental frequency detection algorithm applied to the real-time audio processing system can be balanced.

The invention relates to a method for realizing high-adaptability peak detection suitable for a blind signal spectrum. The method comprises the following steps: generating candidate peaks based on non-adjacent maximum search; and performing intelligent peak value screening based on clustering analysis and intensity hierarchical decision. By adopting the method and the device for realizing high-adaptability peak detection suitable for the blind signal spectrum, the processor and the computer readable storage medium, the dependence on manual setting of key parameters is thoroughly eliminated. According to a traditional method, an operator needs to repeatedly carry out trial and error type parameter adjustment based on prior knowledge, the process is tedious and time-consuming, and a result has strong subjectivity. According to the method, a parameter setting process is internalized into a self-adaptive decision driven by data characteristics through a two-stage framework of'fast non-adjacent search 'and'intelligent screening based on clustering', so that cross-device and cross-sample'zero parameter 'operation is realized, and the automation level, objectivity and result consistency of peak detection are greatly improved.

The invention discloses a heart rate detection method and device based on a ballistocardiogram signal and a storage medium, and the method comprises the steps: obtaining the ballistocardiogram signal, and carrying out the preprocessing of the ballistocardiogram signal; converting the preprocessed heart impact signal into a short-time average amplitude difference curve, and determining a first average JJ interval based on the short-time average amplitude difference curve; based on the first average JJ interval, carrying out filtering processing on the preprocessed ballistocardiogram signal to obtain an envelope signal; performing peak detection on the envelope signal to obtain a target J peak; and determining the heart rate and the heart rate variability based on the target J peak. According to the embodiment of the invention, the method effectively overcomes the defects of a conventional method, achieves the high-precision and high-stability heart rate and HRV detection with lower calculation complexity, can adapt to the BCG signal characteristics of different individuals, and improves the universality of an algorithm. A reliable basis can be provided for disease early warning, health management and the like, and the intelligent level of health monitoring is greatly improved.