721 results about "Signal parameter" patented technology

The invention provides a signal optimization transmission system and method based on HPLC and HRF dual-mode communication, a signal acquisition and processing module of the signal optimization transmission system based on HPLC and HRF dual-mode communication is used for acquiring signals of two communication modes of HPLC and HRF in real time, preprocessing the signals and extracting key signal parameters; the dual-mode switching module is used for dynamically switching an HPLC mode and an HRF mode based on channel quality; the access module is used for constructing a longitudinal backbone network and a transverse Mesh network, forming a hybrid topology, optimizing a routing path and coordinating resource allocation and conflict avoidance of HPLC and HRF; the intelligent decision module is used for predicting future interference intensity according to the historical interference data and adjusting channel parameters; the central coordinator module is used for network initialization and resource allocation; according to the system and the method, the HPLC mode and the HRF mode are automatically switched according to the channel quality, the longitudinal HPLC backbone network is combined with the transverse HRF Mesh network to form a four-dimensional communication network, and the robustness in a complex scene is remarkably improved.

Disclosed in the present invention is a non-autoregressive Transformer-based modeling method for a 4-level pulse amplitude modulation high-speed transmitter. The method involves establishing a deep learning model having an encoder-decoder architecture to predict the behavior of a 4-level pulse amplitude modulation transmitter. An encoder processes unordered non-sequential inputs, including an input signal parameter and link parameters, to generate a context vector and then transmit same to a decoder. The decoder uses both the context vector generated by the encoder and a transmitter output signal sequence to generate a categorical probability distribution for each point in the sequence one by one. The model is trained using a random masking strategy, and inference is performed by means of non-autoregressive decoding and filtering, so that the model can perform parallel prediction on an output sequence, and perform a filtering process to predict an output signal. Compared to traditional simulation methods, the present invention achieves a significant acceleration effect, particularly when processing multi-link systems.

The invention relates to the technical field of pipeline detection, and discloses a pipeline weld defect analysis method and device based on magnetic flux leakage detection.The method comprises the steps that a composite excitation signal is generated and optimized through a multi-frequency excitation source, a magnetic flux leakage attenuation coefficient and scattering characteristics are calculated in combination with pipeline parameters, and if the attenuation coefficient exceeds a preset attenuation threshold value, the pipeline weld defect is detected; if yes, adjusting the excitation signal for optimization, extracting high-frequency transient and low-frequency stable features of the optimized magnetic flux leakage signal, and generating a preliminary feature vector of the weld defect; mapping the preliminary feature vector to a three-dimensional defect space position, generating a space distribution diagram containing the defect position, optimizing the preliminary feature vector to make a fuzzy region clear, and obtaining the depth and direction of the defect; and according to the depth and direction of the defect, analyzing the spatial distribution characteristics of the preliminary feature vectors, determining the type of the defect, dynamically adjusting excitation signal parameters for optimization, recalculating the attenuation coefficient of the signal, extracting the optimized scattering features, and obtaining a high-precision weld defect positioning result.

The invention relates to the technical field of submarine cable fault positioning, in particular to a submarine cable fault positioning system based on underwater beacons. The method comprises the steps that an underwater acoustic beacon array unit monitors and collects submarine cable fault sound wave signals in real time based on underwater acoustic beacons; the fault signal processing analysis unit extracts submarine cable fault sound wave signal parameters based on a non-point source space sound source waveform analysis model, and generates multi-parameter fault sound source feature vectors; the sound source positioning analysis algorithm unit performs three-dimensional inversion positioning based on the multi-parameter fault sound source feature vector and the arrival time difference of the submarine cable fault sound wave signal to the underwater acoustic beacon, and obtains the spatial position information of the submarine cable fault point; and the data communication alarm management unit sends the spatial position information of the submarine cable fault point to a shore-based operation and maintenance system. The submarine cable fault positioning method is used for realizing a submarine cable fault positioning technology for quickly and accurately positioning and identifying spatial extension characteristics in a complex submarine environment.

The invention relates to the technical field of power management, in particular to a multi-source data fusion photovoltaic power scheduling control system, which comprises a sensing extraction module, a disturbance identification module, an offset trend analysis module, a path switching module and a frequency band suppression module. According to the method, a disturbance pre-judgment interval is identified by constructing a time derivative sequence and combining illumination and wind speed trend change in a continuous period, a disturbance time period is accurately discriminated, the disturbance interval is confirmed and disturbance characteristics are extracted through conjoint analysis of photovoltaic and energy storage current change trend and grid-connected point fluctuation amplitude, and the disturbance accuracy is improved. An offset trend curve is formed by calculating photovoltaic and energy storage current change differences, the energy supply offset degree is judged in real time to trigger scheduling conditions, dynamic suppression adjustment is performed on regulation and control signal parameters according to spectrum energy distribution, the accuracy and timeliness of disturbance recognition, energy supply offset judgment and frequency band regulation and control are improved from multiple levels, and the energy storage and energy supply efficiency is improved. And more stable and efficient optical storage combined scheduling control is realized.

The invention relates to the technical field of unmanned aerial vehicle monitoring and trajectory processing, and discloses a low-altitude unmanned aerial vehicle dynamic trajectory tracking and predicting method based on multi-base-station cooperation. The method comprises the steps that signal parameters are obtained through multi-base-station collaborative observation, and a multi-modal position prediction set is generated; and performing classification and scoring according to the spatial distribution characteristics of the candidate points and the historical track points, and screening out an optimal prediction position point. And inputting the optimal prediction point and the historical trajectory into a generative model, and dynamically adjusting the number of trajectory points by analyzing the point distribution probability to form a preliminary smooth trajectory. And performing physical feasibility verification and fine adjustment on the trajectory according to kinematics constraints to obtain a final smooth continuous trajectory. And matching degree calculation is carried out by fusing alternative trajectories generated by a multi-kinematic model, and the most probable target trajectory is identified. According to the method, the robustness of trajectory prediction and the structural rationality of the generated trajectory in a complex observation environment are improved.

The invention discloses a substation primary and secondary equipment communication prefabricated optical cable online monitoring method and system, and belongs to the technical field of communication prefabricated optical cable monitoring. The system comprises an optical cable parameter acquisition module, a communication quality evaluation module, a physical parameter analysis module, a first-aid repair path planning module and a fault database. The method comprises the following steps: optical cable parameter acquisition: acquiring data in real time, and converting high-dimensional data into low-dimensional data through a principal component analysis algorithm; communication quality evaluation: identifying communication characteristics in the low-dimensional signal parameter matrix based on a fuzzy comprehensive evaluation algorithm, and outputting a communication quality score; the physical parameter analysis module extracts physical deep features of the optical cable by using a deep belief network DBN, and inputs an improved Bayesian classifier to output a state classification result; according to the first-aid repair path planning, OTDR detection parameters are dynamically adjusted, and an optimal first-aid repair path is planned in combination with the position of the inspection robot; according to the invention, optical cable communication quality evaluation, accurate physical state classification and efficient fault repair planning 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 gravitational wave signal parameter search model training method and device and electronic equipment, relates to the technical field of data processing, in particular to the fields of astronomy and universe research, gravitational wave detection, signal processing and the like, and can be used for application scenes such as gravitational wave signal processing and the like. According to the specific implementation scheme, an initial gravitational wave parameter set is generated according to a prior range and a preset signal-to-noise ratio threshold value; according to a target gravitational wave parameter in the initial gravitational wave parameter set, generating a time domain gravitational wave signal based on a preset time parameter and a response parameter; performing normalization processing on the time domain gravitational wave signal to generate a gravitational wave signal; constructing a training sample according to the target gravitational wave parameter, the time parameter and the gravitational wave signal; and training the initial neural network by using the training sample to obtain a gravitational wave signal parameter search model. According to the scheme, the training sample is constructed and the model is trained, so that the gravitational wave signal parameter searching efficiency and accuracy can be improved.

The invention relates to the technical field of electrical variable measurement, in particular to a power distribution overhead line fault traveling wave positioning anti-electromagnetic interference method and system and a medium. According to the method, a broadband equivalent circuit model of a power distribution overhead line is constructed based on a vector matching method and is used for simulating transmission characteristics of fault traveling waves and switching operation overvoltage; performing multi-scale decomposition on the acquired signals by adopting a wavelet transform algorithm, extracting disturbance signal parameters, and calculating traveling wave propagation characteristics according to different fault types and switch working conditions; constructing an electromagnetic disturbance propagation coupling model, and performing time-frequency domain analysis by taking the traveling wave propagation characteristics, the disturbance signal parameters and the line environment parameters as input to obtain coupling characteristics of electromagnetic disturbance; carrying out numerical simulation by utilizing electromagnetic field simulation software, analyzing the influence of line environment parameters on coupling characteristics, and optimizing model parameters; and finally, analyzing the coupling characteristics of electromagnetic disturbance, eliminating the influence of electromagnetic interference on the traveling wave signal through a reverse decoupling algorithm, and achieving the accurate fault positioning of the power distribution overhead line.

The invention provides a high-stress rock mass disturbance catastrophe real-time early warning method based on a fracture comprehensive signal, which belongs to the technical field of geotechnical engineering, and constructs a comprehensive acoustic parameter ASCP by fusing various parameters such as amplitude, dominant frequency, energy distribution, crack fractal characteristics, rock mass fracture event density and the like in an acoustic emission signal. The calculation process is combined with contribution weights of different parameters to the destruction stage, and weight values are jointly calibrated through data analysis. On the basis of a large amount of engineering field monitoring and indoor true triaxial test data, the evolution law of the ASCP in the rock mass damage process is analyzed, multiple early warning thresholds of an ASCP evolution curve starting early warning threshold and an ASCP catastrophe early warning threshold are provided, and the early warning accuracy and timeliness are improved. According to the early warning method, various parameters of sound signals are integrated, a multi-threshold early warning method is established, the contribution degrees of various main sensitive parameters of high-stress rock mass disturbance damage sound emission are integrated, and the early warning accuracy, timeliness, high efficiency and economical efficiency are improved.

The invention provides a method for extracting complex electromagnetic interference sensitive parameters of a data link of an unmanned aerial vehicle and a related device, and the method comprises the steps: initializing an observation data set, observation data in the observation data set comprises an interference signal parameter group and a signal-to-interference ratio threshold which causes the unmanned aerial vehicle to lose lock of a data link under the electromagnetic interference of the interference signal parameter group; constructing a target function by taking the interference signal parameter group as an independent variable and taking signal-to-interference ratio threshold maximization as an optimization target, and constructing a proxy model of the target function by adopting a Gaussian process; inputting the interference signal parameter group in the current observation data set into the proxy model, and determining posterior characteristic parameters; constructing an acquisition function based on the posterior characteristic parameters, selecting an interference signal parameter group in the search space to carry out an electromagnetic interference experiment, determining a corresponding signal-to-interference ratio threshold value, and updating the current observation data set; the above process is repeated until the preset convergence condition is met, the electromagnetic sensitivity parameter combination can be obtained more quickly, and the manpower, material and time costs of the electromagnetic sensitivity test are reduced.

The invention discloses a lossless detection mold and method for a rammed earth wall, and relates to the technical field of civil engineering and cultural relic protection. In order to solve the problem that in a traditional rammed earth wall nondestructive detection method, it is difficult to establish an effective corresponding relation between signal features and physical and mechanical parameters, the rammed earth wall nondestructive detection mold and method comprise the steps that rammed earth materials are prepared with reference to the soil texture of an ancient wall, and the rammed earth materials are filled into the rammed earth mold in a layered mode to prepare a wall-like test piece; carrying out nondestructive detection on the city-wall-like test piece by adopting a geological radar to obtain an oscillogram and a grey-scale map, and extracting a detection signal; sampling the city-wall-like test piece, carrying out a physical and mechanical test, and establishing a parameter database in which detection signal parameters are associated with physical and mechanical parameters; and finally, carrying out field detection on the ancient city wall, carrying out geological radar detection to obtain an actual detection signal, and matching the actual detection signal with the parameter database to obtain physical and mechanical parameter information of the ancient city wall. The method can effectively improve the accuracy of lossless detection of the rammed earth structure, and provides a scientific basis for ancient city wall protection.

The invention belongs to the technical field of phased array radar intermediate frequency simulation, and discloses an intermediate frequency simulation method of a phased array radar, which comprises the following steps: carrying out time sequence anti-interference stabilization processing on beam scheduling information output by the phased array radar in real time to obtain a stable scheduling signal; performing domain division signal feature analysis of a beam pointing domain, a target trajectory domain and a resource allocation domain to obtain a sum path signal parameter, an azimuth difference path signal parameter and a pitch difference path signal parameter; performing coupling relevance verification according to the sum-path signal parameters and the actually measured echo data to obtain an operation abnormity judgment result; when the operation abnormity judgment result indicates that the intermediate frequency injection signal has a fault, performing signal track replacement compensation processing based on the azimuth difference path signal parameter and the pitch difference path signal parameter to obtain a target intermediate frequency simulation signal; performing radar tracking and search mode optimization, and outputting a phased array radar beam control instruction; and the tracking precision of the phased array radar on a complex tracking scene is improved.

The invention discloses a detection and recognition integrated waveform design method, device and equipment, a medium and a product. The method comprises the following steps: dividing the time length of a waveform according to a time element, a time frame and a time slot structure; for each time slot, a time slot waveform frame structure is set to be composed of a jitter segment, a synchronization segment and a data segment, and the data segment comprises a Gaussian minimum shift keying (GMSK) modulation data segment and a linear frequency modulation (LFM) modulation data segment; respectively setting a GMSK modulation signal parameter and an LFM modulation signal parameter according to communication system demand information; performing pseudo-random hopping design on the pulse frequencies of the synchronization segment and the GMSK modulation data segment to obtain a pseudo-random frequency hopping pattern; and generating a GMSK modulation section waveform and an LFM modulation section waveform according to the GMSK modulation signal parameter and the LFM modulation signal parameter so as to form an integrated waveform. According to the embodiment of the invention, the integrated waveform can realize communication, detection and identification functions at the same time, the waveform resource utilization rate is high, and the anti-interference capability is relatively high.

The invention discloses a multi-protocol automatic identification switching down lamp control method and related equipment, and relates to the technical field of intelligent lighting. According to the method, multi-protocol signal monitoring is started, and signal parameters are collected in real time to judge the protocol type; a single protocol is directly connected, and an optimal protocol is selected to establish connection in combination with a network environment according to priorities during multi-protocol; state information is recorded in real time, and connection is quickly recovered after the network is interrupted or restarted; and the OTA is supported to update a new protocol. According to the invention, multi-protocol automatic adaptation is realized, the control stability and the energy saving performance are improved, the product life cycle is prolonged, the user cost is reduced, and the intelligent control experience is optimized.

The invention relates to the technical field of indoor 5G network optimization, and discloses an indoor 5G network optimization system based on ray tracing, which is characterized in that a network signal state parameter set is dynamically acquired through a signal parameter acquisition module, a signal coverage risk is judged, and a collaborative analysis instruction is triggered to execute a ray tracing analysis module and an interference characteristic analysis module; and respectively acquiring a propagation stability index and an interference evaluation value. And the multi-source fusion judgment module receives the two values to carry out cooperative analysis on the network coverage adaptability, and generates antenna adjustment and power optimization signals. And the optimization parameter generation module is matched with the strategy to generate antenna angle adjustment and power correction parameters. The system further comprises a coverage coupling analysis module monitoring signal and building structure coordination and a dynamic feedback execution module to form a closed-loop control link, and intelligent optimization of an indoor 5G network is achieved.

The invention belongs to the technical field of power system protection, and discloses a circuit breaker fault diagnosis method and system, and the method comprises the steps: obtaining a real-time vibration signal parameter and a current signal parameter in the operation process of a circuit breaker; identifying an aging drift signal cluster according to amplitude fluctuation in the vibration signal parameters and phase deviation in the current signal parameters; acquiring the drift response level of the aging drift signal cluster at each moment according to the signal direction change and amplitude stability of the aging drift signal cluster; screening a high-priority diagnosis cluster based on the drift response level; according to the drift response level of the high-priority diagnosis cluster at each moment and the current signal parameter of the high-priority diagnosis cluster at the same moment, obtaining a diagnosis guidance index of the corresponding diagnosis cluster; and dynamically adjusting a health baseline threshold value based on the diagnosis guidance index so as to realize adaptive diagnosis of the circuit breaker fault. And the accuracy of fault diagnosis of the circuit breaker is greatly improved.

The invention relates to the technical field of distributed synthetic aperture radar (SAR) imaging detection and cluster guidance, in particular to a mobile platform bistatic SAR moving target imaging and positioning parameter estimation method and system, through the method provided by the invention, distance migration correction of a moving target is realized by adopting distance frequency inversion transformation, and the positioning accuracy of the moving target is improved. According to the method, an accelerated multi-component QFM signal parameter estimation method is optimized by adopting a genetic algorithm in azimuth, and finally, state parameter estimation on a maneuvering target with acceleration is realized by adopting a combined aperture method based on each order of estimated Doppler parameters, so that the condition of failure in the prior art is avoided. According to the method, imaging and positioning of the maneuvering target by the maneuvering platform bistatic SAR are achieved, the application range of the current bistatic SAR is expanded, and the method mainly relates to point multiplication and fast Fourier transform (FFT) and is high in operation efficiency, so that the method is suitable for the scene that terminal guidance application is conducted on the moving target by a cluster system.

The invention provides a biological characteristic closed-loop monitoring method, device and equipment based on terahertz signals, and the method comprises the steps: executing closed-loop regulation and control operation based on target biological characteristic information; wherein when the closed-loop regulation and control operation comprises environment self-adaptive regulation and control, the environment self-adaptive regulation and control comprises the steps of monitoring an environment parameter of an environment where the target organism is located, and dynamically adjusting a signal parameter used for transmitting a terahertz signal based on the environment parameter; when the closed-loop regulation and control operation comprises biological feedback regulation and control and it is judged that the target biological characteristic information meets a preset abnormal condition, the biological feedback regulation and control is used for dynamically adjusting communication network resources used for bearing terahertz signals. According to the method, the target biological characteristic information in the terahertz reflection signal and the auxiliary sensing signal is analyzed, traditional equipment does not need to be worn, and the accuracy and convenience of biological characteristic monitoring are improved; the robustness and intelligence of the whole biological characteristic monitoring system are improved through a double closed-loop mechanism of environment adaptive regulation and biological feedback regulation.

Provided is a downhole device, a well system, and a method. The downhole device, in one aspect, includes an electromagnetic assembly, as well as a magnetic target positioned proximate the electromagnetic assembly, wherein one of the magnetic target or the electromagnetic assembly is coupled with a movable feature of the downhole device, the movable feature configured to move to physically couple or physically decouple the electromagnetic assembly and the magnetic target. The downhole device, according to this aspect, further includes a sensor electrically coupled to the electromagnetic assembly, the sensor configured to sense for a change in an AC signal parameter impart upon the electromagnetic assembly as the electromagnetic assembly and magnetic target physically couple to or physically decouple from one another, the sensed change employable to estimate the status or health of the downhole device.

The invention discloses a rock stratum drilling in-situ identification method based on physical information machine learning and an application thereof, which are used for solving the technical problem of in-situ sensing of unknown rock mass properties in a drilling process. Multi-source signal parameters including drilling pressure, drilling rod torque, drilling rod rotating speed, drilling speed and drilling vibration and acoustic emission signals are collected in the drilling process, CEEMDAN-VMD combined denoising and feature extraction are carried out, and fused feature vectors are input into a physical information machine learning model; and outputting the strength prediction value of the drilled rock stratum and the prediction value of the rock mass category on line in real time. The method is applied to innovative combination of freeze-thaw environment simulation, rock drilling process test and lithology intelligent identification, an advanced means is provided for drillability evaluation of freeze-thaw rock mass, data support can be provided for blasting parameter intelligent design and slope stability early warning, and the method has good engineering applicability and popularization value.

The invention relates to the technical field of operational amplifier testing, and discloses a device and method for establishing time testing and a medium, and the device comprises a parameter measurement unit module which is used for transmitting a first step signal; the inverting module is used for receiving the first step signal, performing phase inversion on the first step signal based on an inverting operational amplifier, and outputting a first inverted signal; the parameter measurement unit module is also used for sending a second step signal after the first step signal is sent for a preset duration; the superposition module is respectively connected with the phase inversion module and the parameter measurement unit module, and the superposition module is used for receiving the first phase inversion signal and the second phase step signal, adding the first phase inversion signal and the second phase step signal and outputting a first superposition signal; and the parameter measurement unit module is also used for receiving the first superposed signal and obtaining the establishment time of the inverting operational amplifier based on the analysis result of the first superposed signal. Therefore, the test result is more accurate.

The application relates to the technical field of electromagnetic shielding test devices, and discloses a test device for electromagnetic shielding materials. The device comprises a signal emission module, a signal receiving module, a parameter calibration module and a shielding effectiveness calculation module. The signal emission module outputs electromagnetic signals of different frequencies from multiple signal sources, and forms a set of to-be-tested signals after pre-processing and amplitude adjustment; the signal receiving module collects residual signals passing through the shielding material and converts the residual signals into analyzable signals; the parameter calibration module extracts signal parameters to construct an electromagnetic signal parameter matrix, constructs a transmission correlation atlas through a channel correlation graph and a key signal parameter correlation degree; the shielding effectiveness calculation module combines signal channel entropy and the correlation atlas to calculate a shielding effectiveness core parameter sequence, and finally inputs the effectiveness detection model of a convolutional neural network model to generate a test report. The device can comprehensively process multiple-frequency signals, deeply analyze signal parameter correlation, accurately calculate shielding effectiveness, and is suitable for electromagnetic shielding material performance testing.

The invention relates to the technical field of natural gas transportation safety, in particular to a hydrogen embrittlement risk online monitoring system and method for a hydrogen-doped natural gas pipeline based on multi-parameter fusion, and the system comprises a sentry sensing unit which adopts a metal short pipe which is the same as a to-be-monitored hydrogen-doped natural gas main pipeline in property, material, process, wall thickness and service history, an internal circulating medium is kept consistent with the main pipeline; the risk sensor is provided with a multi-parameter sensor to obtain risk sensing parameters including hydrogen permeation current, pipe wall micro-strain and temperature signal parameters; the signal processing unit is connected with the sentry sensing unit, receives the risk sensing parameters and analyzes and generates hydrogen embrittlement risk indexes through a risk analysis model; and the risk warning unit is connected with the signal processing unit, and triggers a danger prompt signal when the hydrogen embrittlement risk index is greater than a preset safety index. The method has the effect of meeting the danger monitoring effectiveness of safe operation of the hydrogen-doped natural gas pipeline.

The invention provides a railway Beidou satellite signal simulation method and system based on artificial intelligence. The method comprises the steps of obtaining geographic data corresponding to a railway simulation line and ephemeris data corresponding to simulation time; through statistical analysis of geographic data, geographic features such as geometric features, terrain categories, geotechnical engineering parameters, geologic structure parameters, stratigraphic structure parameters and ground feature distribution features of the terrain are obtained; input of a pre-trained artificial intelligence model is obtained based on the geographic features and ephemeris data, so that multi-dimensional analog signal parameters are obtained; and performing navigation message filling by using the ephemeris data to generate a navigation message, and generating a Beidou satellite simulation signal based on the navigation message and the multi-dimensional simulation signal parameters. According to the invention, efficient, accurate and intelligent analog signals can be generated.

The invention relates to the field of rotor blade non-contact state monitoring, in particular to a blade tip timing vibration measurement signal parameter identification method and system under a time-varying rotating speed. Comprising the following steps: constructing a matrix Chirp signal model; performing initial frequency pre-analysis based on a block orthogonal matching pursuit method to obtain an estimated value; defining a range interval of initial frequency analysis and an analysis range of a frequency modulation slope by taking the estimated value as a center, and obtaining an orthogonal matching pursuit result based on a matrix Chirp signal model and a block orthogonal matching pursuit method; and according to a matching tracking result, calculating to obtain a vibration amplitude. According to the method, the frequency modulation slope is introduced to serve as an additional parameter, the change trend of the frequency along with time is reflected, the vibration rule of the blade under the centrifugal stiffening effect can be more truly described, and an accurate physical basis is provided for analysis of non-stationary signals.

The application belongs to the field of digital signal processing, and particularly relates to a linear frequency modulation signal parameter estimation method under a low signal-to-noise ratio condition, which comprises the following steps: collecting signals and discretizing the signals; dividing the discrete sequence into sub-signals by framing, performing an FFT operation after a windowing and zero padding operation, and obtaining a frame sequence vector; searching for a maximum spectral peak of the spectrum of each frame of signals, and correcting the maximum spectral peak by using a cubic spline interpolation method to obtain a corresponding frequency; performing an equal-step distance and successive rotation scanning of two groups of vectors in a plane; synchronously projecting frequency vectors at different rotation angles, dividing a frequency band, and recording a frequency quantity statistical result; eliminating a trend item by using a median filtering, obtaining a maximum value of a statistical quantity, and then obtaining a preliminary estimation value of a parameter; and obtaining a final estimation result of an initial frequency and a frequency modulation rate of the linear frequency modulation signal by using a least square method fitting. The application overcomes the problems of great difficulty, low precision and complex calculation of the linear frequency modulation signal parameter estimation under the low signal-to-noise ratio condition in the prior art, and has good engineering practicability.

Disclosed in the present application are a working scenario determination method and apparatus, and a wearable device and a computer-readable storage medium. The working scenario determination method comprises: acquiring an acoustic time-domain signal, which is detected by an acoustic perception sensor, and a vibration time-domain signal, which is detected by a vibration perception sensor; preprocessing the acoustic time-domain signal and the vibration time-domain signal to obtain a target acoustic signal and a target vibration signal, and comparing signal parameters of the target acoustic signal and the target vibration signal to obtain signal parameter deviation information; and if the signal parameter deviation information is within a preset parameter deviation range, starting a preset working module of a wearable device, and entering an operating state.