123 results about "Analytic signal" patented technology

The invention discloses a multi-signal quality monitoring system and method in the numerical control machining process, and belongs to the technical field of numerical control machining. The method comprises the following steps: step 1, synchronously acquiring multi-source signals in a microscopic level, a mesoscopic level and a macroscopic level in a processing process; 2, screening to form an optimal feature subset, and constructing a multi-dimensional feature representation space; 3, constructing a same-scale transverse incidence matrix, a cross-scale longitudinal incidence matrix and an interaction incidence matrix based on a bidirectional attention mechanism, and forming an incidence network structure for describing feature coupling and dependency relationships among signals of different levels; step 4, calculating deviation metric values of various signal features, identifying an abnormal diffusion path in combination with a topological structure of the association network, and analyzing a causal relationship chain between the signals; and step 5, matching the identified abnormal mode with a pre-constructed process knowledge graph, automatically generating a targeted process parameter optimization suggestion, and performing real-time evaluation to realize closed-loop adaptive control for quality abnormity.

The invention relates to the technical field of trapping equipment control, and discloses a trapping equipment cooperative control system based on multi-sensor fusion, which comprises a multi-source data acquisition module, a target identification module, a risk assessment module, a cooperative relationship modeling module, a path optimization module, a decision fusion module and an execution control module. The multi-source data acquisition module generates an environment perception map containing temperature, humidity and illumination; the target recognition module analyzes the signals and generates data containing the target size and the motion category in a classified mode; the risk assessment module divides risk areas and inverts threats to generate a risk distribution map; the collaborative relation modeling module extracts collaborative parameters such as communication delay; the path optimization module dynamically plans a path; the decision fusion module performs weighted fusion on the data generation indexes; and the execution control module matches actions and adjusts parameters. The system realizes multi-dimensional perception, accurate identification and cooperative control, improves the trapping efficiency, and is suitable for pest control and other scenes.

The invention belongs to the technical field of power equipment state monitoring and fault diagnosis, and discloses a high-voltage circuit breaker state quantity feature extraction method and system, and the method comprises the steps: extracting a local maximum value point and a local minimum value point from a denoised original monitoring signal; feature vectors are constructed and input into the trained neural network model, six-dimensional vectors are output in a Softmax output layer, and the six-dimensional vectors correspond to prediction probabilities of six orders in the optimal B-spline interpolation orders; based on the constructed envelope, adopting empirical mode decomposition to obtain a plurality of intrinsic mode function IMF components, performing Hilbert transform on each IMF component, constructing a state quantity feature set according to the instantaneous frequency and amplitude change of the analysis signal, and judging whether the high-voltage circuit breaker is in an abnormal state or not. According to the method, the vibration signals collected by the circuit breaker are subjected to multi-stage intelligent processing, high-precision and low-noise feature extraction is achieved, and fault diagnosis and state recognition of the circuit breaker can be effectively supported.

The invention relates to the technical field of electrical engineering and intelligent fault diagnosis, and discloses a water pump motor fault diagnosis method and system based on current harmonic characteristics, and the method comprises the steps: collecting stator current, rotating speed and load signals; generating an alpha-beta current component through Clark transformation, constructing an analytic signal, extracting an instantaneous phase, and calculating an instantaneous frequency; a mapping relation is established in combination with the rotating speed, and the current signals are resampled to eliminate frequency dispersion; obtaining a high-resolution harmonic energy distribution diagram by adopting multi-scale synchronous compression wavelet transform; and extracting an energy concentration ratio, a peak offset and a bandwidth expansion coefficient in the characteristic frequency band, inputting the energy concentration ratio, the peak offset and the bandwidth expansion coefficient into the pre-trained multi-layer perceptron classifier, and outputting a fault type. According to the method, through high-precision time-frequency focusing and multi-dimensional feature fusion, the fault recognition accuracy and robustness are remarkably improved, and online diagnosis of multiple typical faults can be achieved only through current signals.

The invention discloses an underwater sound environment sensing method based on multi-array-element sparse channel estimation. An underwater sound receiving end receives signals transmitted through an underwater sound multipath channel through a multi-array-element array; performing Hilbert transform on the receiving signal of each array element to obtain an analysis signal, and calculating a cross-correlation function of the analysis signal and the transmitting signal; based on the cross-correlation function, sparse channel parameters, including path amplitude and time delay, of each array element are estimated by adopting an orthogonal matching pursuit algorithm combined with a constant false alarm detection dynamic threshold value; the method comprises the following steps: constructing an array response vector by using sparse channel parameters of a multi-array element array, and searching and estimating angles of arrival, including a direction angle and a pitch angle, of a multipath signal through a spatial spectrum peak value; and based on the arrival angles, amplitudes and time delays of the direct path and the reflection path, inverting an underwater environment structure through a ray acoustic theory, including a reflection point distance and a reflection surface normal vector, so as to realize three-dimensional perception of the underwater reflector. According to the invention, multipath resolution can be improved, and false alarm and missing detection can be effectively reduced.

The invention discloses a real-time wave number space resampling method and system for SS-OCT, and relates to the technical field of signal processing, and the method comprises the steps: synchronously collecting a K clock signal and an OCT interference signal, and carrying out the filtering preprocessing of the signals; carrying out Hilbert transformation on the preprocessed K clock signal, constructing an analysis signal, extracting an instantaneous phase, and forming an instantaneous phase sequence; using a preset ideal equal wave number interval phase sequence as a target phase sequence, matching the target phase sequence with the instantaneous phase sequence, calculating a corresponding position index of each target phase in the instantaneous phase sequence, and obtaining a remapping sampling point index; and processing the preprocessed OCT interference signal by using an SINC interpolation method according to the remapping sampling point index to obtain an OCT signal which is subjected to resampling and has equal wave number intervals. According to the invention, the SINC interpolation algorithm is utilized to complete resampling in real time and with high precision in the data acquisition stage, and the requirement of high-speed real-time imaging is met.

The invention discloses a magnetic target boundary recognition method and system based on a magnetic gradient tensor, and relates to the technical field of geophysical exploration and industrial nondestructive testing, and the method comprises the following steps: collecting spatial magnetic gradient tensor data through a magnetic gradient sensor array, and obtaining nine components of the magnetic gradient tensor; calculating the vertical guide modulus of the vertical component of the magnetic gradient tensor; calculating a Z-direction analysis signal ASAz and a vertical guide thereof; a boundary recognition amount is generated by a ratio operation, and a boundary position of the magnetic target is determined based on a maximum value position of the boundary recognition amount. According to the method, a vertical component derivative and analytic signal derivative dual-derivative coupling mechanism is combined for the first time, the limitation that a traditional method depends on a single parameter is overcome, the vertical component derivative accurately captures the change rate of the boundary in the vertical direction, and the analytic signal derivative effectively suppresses background noise.

The invention discloses a power equipment anomaly detection method and system and a medium. The method comprises the following steps: acquiring event data and a frame image; frequency domain conversion is carried out on the event data, a complex frequency spectrum of the event is obtained, and the complex frequency spectrum comprises the amplitude and phase information of the event signal on each frequency component; frame images are obtained, analysis signal conversion is carried out on the frame images, a plurality of frame images are obtained, and each pixel of the images in the plurality of frame images has amplitude and phase representation; fusing the plurality of frequency spectrums and the plurality of frame images based on adaptive attention to obtain initial multi-domain fusion features; performing time deviation correction on the initial multi-domain fusion features to obtain synchronous multi-domain fusion features; and carrying out multi-scale processing on the synchronous multi-domain fusion features to obtain a fusion image which is used for a fault identification model to carry out power equipment anomaly detection. Complete frequency spectrum information such as amplitude and phase of the event signal can be reserved in the fusion process, and the accuracy of anomaly detection can be improved.

The invention discloses a multi-protocol dynamic adaptive industrial equipment data integration system and method, and relates to the field of industrial equipment data processing, and the system comprises an identification module which is used for receiving a protocol signal sent by industrial equipment, analyzing a protocol type identifier carried in the signal, and synchronously creating a data connection channel between the equipment and the system; the generation module is used for automatically generating corresponding data interaction adaptation logic based on the signal analysis result in the identification module; according to the method, optimized interaction adaptation logic is generated by combining equipment protocol parameters and historical interaction data, reliability and real-time performance of data interaction are improved, invalid fragments are filtered during data collection, collection frequency is dynamically adjusted, data quality and equipment load balance are considered, different protocol data are processed in a standardized mode according to a unified model so as to achieve format unification, and data interaction efficiency is improved. Storage resources are dynamically allocated according to the data generation frequency and the key degree, the associated index is established, and the storage utilization rate and the data retrieval efficiency are improved.

The invention discloses a literature diffraction pattern quality evaluation and intelligent repair system and method, and belongs to the technical field of computers. The method comprises the following steps of: 1, inputting and processing data; step 2, image-text consistency alignment and consistency inspection are carried out; step 3, calculating quality parameters, constructing a quality evaluation system, and performing grading and report output on atlas data; step 4, repairing and warehousing the atlas; the system adopts a modular architecture design, is composed of an image processing module, a text analysis module, a signal analysis module, a quality evaluation module, a report generation and output module, a grading feedback module, an atlas restoration module and the like, and can flexibly adapt to different types of diffraction atlas quality evaluation tasks. According to the technical scheme, aiming at the limitation of literature image type XRD atlas quality evaluation, the evaluation system and method with intelligent repair, knowledge reasoning and self-learning capabilities are constructed, and the availability, credibility and structured processing efficiency of literature XRD atlas data are remarkably improved.

The invention relates to the technical field of motor diagnosis, and discloses a motor eccentricity fault diagnosis method and system based on current harmonic analysis, and the method comprises the steps: carrying out the power frequency component extraction of a three-phase stator current signal, obtaining a residual current signal, carrying out the complex analysis envelope transformation of the residual current signal, and obtaining an envelope analysis signal; performing synchronous interpolation resampling on the envelope analysis signal to obtain a complex envelope signal; performing frequency spectrum estimation on the complex envelope signal to obtain a discrete frequency spectrum of a module value sequence; performing equalization processing on the order spectral line amplitude in the discrete spectrum to obtain a whitened spectrum, and performing inverse transformation on the whitened spectrum to reconstruct an angular domain amplitude signal of the target motor; performing cyclostationary analysis on the angular domain amplitude signal to obtain a third-order cyclic cumulant of the angular domain amplitude signal at a specific cyclic frequency; according to the third-order cycle cumulant, the type and severity level of the eccentric fault are judged; the accuracy of motor eccentricity fault diagnosis can be improved.

The invention relates to the field of railway data analysis and processing, in particular to a railway irregularity data processing method based on cEEMDAN-Hilbert. The method comprises the following steps: acquiring and preprocessing track irregularity original signals to obtain a target track irregularity signal sequence; performing CEEMDAN (adaptive noise complete ensemble empirical mode decomposition) on the target track irregularity signal sequence, and performing iterative decomposition on the signal added with Gaussian white noise to obtain a plurality of IMF (intrinsic mode function) components and a residual component; performing Hilbert transformation on each IMF component, calculating an instantaneous frequency and an instantaneous amplitude, constructing an analysis signal in a complex form, and extracting time and frequency joint distribution information; according to the instantaneous frequency and the energy result, false wavelength components are removed, signal reconstruction is carried out, and reconstructed track irregularity signals are generated. According to the invention, the identification capability of local structure disturbance can be enhanced.

The present invention discloses a method and device for laser self-mixing interference displacement reconstruction based on a single-sided time-frequency spectrum. The method comprises the following steps: S1: collecting a self-mixing interference signal from a target object, performing a time-frequency transformation based on the self-mixing interference signal to obtain a double-sided time-frequency spectrum; S2: selecting and retaining a single-sided time-frequency spectrum from the double-sided time-frequency spectrum for analysis; S3: performing an inverse transformation on the single-sided time-frequency spectrum to obtain an analytical signal; S4: extracting the real and imaginary parts of the analytical signal and dividing them to obtain a tangent signal; S5: performing an inverse tangent operation on the tangent signal to obtain a motion phase; and S6: calculating the relationship between phase and distance based on the motion phase to obtain a displacement curve of the target object. The present invention eliminates the need for additional complex optical components to obtain orthogonal signals, simplifies the composition of the measurement system, and provides a novel, efficient, and economical solution for the field of displacement measurement.

The application discloses a rolling bearing fault diagnosis method based on acoustic framing. Firstly, the collected acoustic signal of the rolling bearing is subjected to Hilbert transform to construct a double-channel analytic representation containing instantaneous amplitude and instantaneous phase information. Then, the analytic signal is divided into short-time frame segments by the acoustic framing embedding module according to a preset frame length and step, and a uniform dimension frame-level embedding vector is generated by linear mapping, so as to highlight the local transient impact feature and effectively compress the sequence length. An improved lightweight Transformer encoder is adopted for timing feature extraction, the encoder combines a low-dimensional multi-head self-attention mechanism and a feedforward network based on SiLU activation and deep convolution, so as to simultaneously model the cross-frame global dependence and the short-range local structure, and finally, the intelligent identification of the multi-class faults of the rolling bearing is completed through the global feature vector of the class token.

The invention relates to the technical field of anti-interference signal processing, in particular to an anti-interference signal processing method of an FPC (flexible printed circuit) sensing module, which comprises the following steps of: performing multilayer discrete wavelet transform decomposition on an original sensor data stream from the FPC sensing module, separating an approximation coefficient and a detail coefficient of each layer, and establishing a signal time-frequency component matrix representing signal time-frequency distribution; according to the method, multi-layer discrete wavelet transform decomposition is carried out on the original sensor data stream, signals can be analyzed in the time domain and the frequency domain at the same time, then low-frequency noise components introduced by mechanical deformation of the flexible substrate are stripped through zero setting operation on the deepest layer approximation coefficient, accidental damage to effective low-frequency components of the signals is avoided, and the accuracy and the reliability of the sensor are improved. The original form and details of the signal are reserved, and meanwhile, a surprising fraction spectrum representing the abnormal degree of data points is established, so that local sudden interference or sensor single-point failure still existing even after time-frequency domain purification can be positioned.

This invention discloses an infrasound localization method for minor pipeline leaks, comprising: acquiring the original infrasound signal of the pipeline leak; performing variational mode decomposition on the original infrasound signal to obtain IMF components; based on the IMF components, using an improved generalized cross-correlation function to obtain the time difference between the infrasound reflection to the upstream and downstream ends of the pipeline; calculating the wave velocity of the infrasound according to the pipeline characteristics; and determining the location of the pipeline leak point based on the time difference and wave velocity. The improved generalized cross-correlation function method involves: constructing an analytical signal based on the IMF components; using an improved linear adaptive weighted local approximation algorithm to obtain the local optimal solution of the IMF components; and performing inverse attenuation dispersion compensation analysis based on the generalized cross-correlation function to obtain the time difference between the infrasound reflection to the upstream and downstream ends of the pipeline. This invention can accurately locate the pipeline leak point.

This invention discloses a method and system for visual enhancement of underwater robots in turbid waters, relating to the fields of machine vision and image restoration technology. The method includes: acquiring a sequence of original color images collected in real-time by the underwater robot; mapping the pixel intensity of the original color image sequence to a complex space to construct a complex domain analytic signal; extracting the multi-directional spatial gradient tensor of the original color image, and calculating pseudo-polarization information and environmental characterization parameters accordingly; constructing a virtual phase compensation operator using the pseudo-polarization information and the environmental characterization parameters; wherein the pseudo-polarization information drives the compensation intensity of the virtual phase compensation operator, and the environmental characterization parameters are used to locally weight the compensation intensity. Its beneficial effects include: correcting edge blurring and texture obfuscation caused by wavefront phase disturbances, and significantly improving the edge steepness of structural contours in the image.

The application relates to the field of artificial intelligence, and discloses a brain-computer computing driven visual information instant analysis method and system, which comprises the following steps: acquiring real-time sensing data and neural pulse signals, analyzing a signal sensing curve to construct a brain-computer computing network, identifying visual information features through the network, analyzing a preset model computing architecture, optimizing a neuron mapping relationship to obtain an optimized mapping network, analyzing a path based on the analysis information, determining a target data time sequence distribution state, calculating an analysis efficiency value, determining an analysis optimization direction, generating an instant analysis strategy, calculating an analysis attenuation rate, determining an analysis state based on the attenuation rate, analyzing an analysis dimension, and finally constructing an optimized analysis scheme. The application can improve the intelligent analysis efficiency of visual information.

This invention relates to the field of coordinated control of energy storage in new energy collection stations, and particularly to a coordinated control method for reactive power compensation of energy storage in new energy collection stations based on impedance reshaping. Based on the acquired three-phase AC signal, an analytical signal representation is obtained. Based on the analytical signal representation, a complex spectrum is obtained, and the impedance frequency response is determined. After processing with an exponentially weighted cumulative average filter, the actual impedance is obtained. Combined with the target impedance determined by the target impedance response model, the impedance error is determined. Based on the impedance error, a frequency-sensitive adjustment driving function is determined, and a new energy collection station adjustment residual loss function is constructed. The optimal complex impedance weighted path scheduling matrix is ​​determined. Simultaneously, a frequency segmentation objective function mechanism and a suppression function are introduced to construct a global optimization objective function, obtaining the optimal virtual impedance configuration. This solves the technical problems of resonance and stability issues, as well as reactive power response conflicts and low control efficiency caused by independent control strategies and a lack of coordinated adjustment.

The invention relates to a motor fault diagnosis method based on sparse Bayesian and a one-dimensional neural network. The method comprises the following steps: S1, collecting a motor stator current signal, and carrying out filtering and preprocessing; s2, performing Hilbert transformation on the current signal to obtain an analysis signal; s3, constructing a sparse signal model in the truncated frequency domain and performing frequency grid division; s4, solving the sparse model based on sparse Bayesian learning, and correcting the deviation between the fault frequency and the grid by adopting an off-grid model to obtain an envelope spectrum; and S5, inputting the envelope spectrum into a one-dimensional convolutional neural network to output a motor fault diagnosis result. The method has higher frequency recovery precision, stronger robustness and fault recognition accuracy exceeding 98% in a complex environment.

The present application relates to the field of biological signal processing, in particular to a frequency estimation method based on rootMUSIC and signal dimension conversion, a storage medium and equipment. The method comprises the following steps: chest displacement signals extracted from radar echoes are modeled as the sum of sine waves with integer multiple frequencies of basic respiration and heart rate, and corresponding single-channel analytic signals are generated through Hilbert transform; the single-channel analytic signals are converted into multi-channel data through a signal rearrangement method, the chest wall signal model is equivalent to a uniform linear array multi-shot receiving signal model, so that the vital sign frequency and the signal source direction of arrival establish a one-to-one correspondence; the received data of the multi-shot receiving signal model is processed through an alternating direction multiplier method framework, and a denoised signal matrix is solved; the rootMUSIC algorithm is used for the denoised signal matrix to solve the frequency estimation. The present application converts the signal model, makes the frequency estimation range equivalent to the angle estimation range, and improves the frequency estimation accuracy.

The application provides a speech separation post-filtering method and system based on sub-band envelope characteristics, which comprises the following steps: designing an m times frequency band pass filter set, performing sub-band decomposition on the separated estimated sound source signal and the original mixed signal to obtain the frequency band division representation thereof; performing Hilbert transform on each sub-band of the estimated sound source signal and the original mixed signal to construct an analytic signal, calculating the instantaneous amplitude thereof and removing the high frequency component through low pass filtering to obtain the corresponding sub-band envelope; calculating an initial masking value, limiting the initial masking value by setting a lower threshold, performing nonlinear mapping on the initial masking value through a sine function to obtain an envelope masking coefficient; applying the envelope masking coefficient to the corresponding sub-band signal of the estimated sound source; and performing full-band reconstruction on each sub-band signal subjected to the masking processing to obtain an enhanced target sound source signal. The application has the advantage that the performance of a speech separation system in a complex acoustic environment is effectively improved.

The invention relates to a low-altitude aircraft information identification and monitoring method, system and device and a medium, and belongs to the technical field of airspace management, and the method comprises the steps: configuring a radio frequency receiving module to capture an aircraft broadcast signal of a preset frequency band; performing a low-pass filtering operation on the aircraft broadcast signal, and detecting a frame synchronization byte to extract a signal frame; analyzing the frame structure of the signal frame, determining an encryption mode according to the frame header identifier, calling a corresponding decryption algorithm, and outputting flight data; matching the identity code with a pre-stored filing database to generate a validity verification result of the aircraft; constructing a space-time identification data packet, processing the space-time identification data packet through an airspace state analysis engine, and generating a conflict early warning mark and an airspace compliance state; and according to the airspace compliance state and the legality verification result, triggering a multi-level risk alarm instruction and returning a target tracking signal to the radio frequency receiving module. According to the invention, the real state of the low-altitude aircraft can be accurately mastered, and the efficiency of airspace traffic management is improved.

The invention discloses a method for achieving LED synchronous control based on an HDMI signal analysis algorithm, and the method comprises the following steps: S1, receiving an HDMI signal, and receiving an HDMI signal from a source device through an HDMI receiver; s2, analyzing the HDMI signal, analyzing the received HDMI signal, and efficiently extracting video data in the HDMI signal by using a large model control algorithm; s3, converting the video data into an LED control signal, and converting the analyzed video data into a signal format suitable for controlling an LED; s4, synchronously controlling the LED, and sending the converted LED control signal to the LED display screen to realize the synchronous control of the LED; and S5, adjusting the control parameters, and adjusting the LED according to needs. The method has the advantages that the system is simplified, HDMI signals are directly analyzed and converted into LED control signals through a trained large model algorithm, the use of intermediate links and equipment is reduced, the system structure and connection are simplified, and the complexity and cost of the system are reduced.

This application discloses an automatic signal generation method, system, electronic device, and storage medium, relating to the field of automotive electronic software development. Based on text parsing, the automatic signal generation method includes: Step T1, parsing the signal information from the requirement side to form a first signal set; Step T2, parsing the signal information from the code side to form a second signal set; Step T3, performing set operations on the first signal set and the second signal set to determine a difference set; Step T4, automatically generating code based on the difference set and securely writing the generated code into a target file; Step T5, generating a report based on the writing result. This solution completely replaces manual signal code writing, significantly improving development efficiency and reducing human error; it achieves automatic synchronization of requirement documents and code signals, ensuring consistent and standardized signal definitions throughout the process; and it automatically identifies missing / conflicting signals through set operations, achieving accurate updates without redundancy or omissions.

The invention relates to the related technical field of signal processing, in particular to a signal processing method and system for a radar life detector, and the method comprises the steps: collecting a radar detection signal, and configuring a parameter judgment reference; evaluating the analysis feasibility of the pulse Doppler radar signal, and determining a local detection sub-region under the echo signal intensity distribution mark; and adjusting the sampling frequency and the detection coverage of the signal processing unit, and generating a detection report. The technical problems that signals are processed at a fixed sampling frequency and a detection range, blind analysis is still performed when the effective analysis probability of the signals is low, local signals are easily ignored under a complex terrain, and the detection reliability is difficult to guarantee are solved, an effective analysis probability evaluation mechanism is introduced, only high-probability analyzable signals are deeply processed, local detection sub-regions are locked, and the detection reliability is ensured. The technical effects of synchronously adjusting the sampling frequency and the detection coverage range, eliminating a detection blind area under a complex terrain, performing registration correction on radar scanning surface data and discrete point data, and ensuring the detection reliability are achieved.

The application discloses a kind of based on multi-array sparse channel estimation underwater acoustic environment perception method, underwater acoustic receiving end is received through multi-array array signal that is propagated through underwater acoustic multipath channel;The received signal of each array element is subjected to Hilbert transform, and analytic signal is obtained, and the cross-correlation function of analytic signal and transmitting signal is calculated;Based on cross-correlation function, using the orthogonal matching pursuit algorithm of combining constant false alarm detection dynamic threshold, the sparse channel parameters of each array element are estimated, including path amplitude and time delay;Utilize the sparse channel parameters of multi-array array, construct array response vector, estimate the angle of arrival of multipath signal, including direction angle and pitch angle by space spectrum peak value search;Based on the angle of arrival, amplitude and time delay of direct path and reflected path, the underwater environment structure is inverted by ray acoustics theory, including reflection point distance and reflection surface normal vector, realize the three-dimensional perception of underwater reflector.The application can improve multipath resolution, effectively reduce false alarm and miss detection.

Exemplary embodiments relate to an automated sample processing system that includes a cartridge having an upper member and a lower member, where the upper member and the lower member have a sufficient difference in opacity detectable by a sensor. The transmitter is configured to transmit a signal, wherein the signal passes through (or is diffused by) one member of the cartridge in a transverse direction and is configured to be received by the sensor. The sensor is configured to transmit signal processing logic configured to parse the signal and indicate an orientation of the cartridge. A method of detecting an orientation of a cartridge in an automated sample processing system is also disclosed.

The application discloses a kind of embankment quality elastic wave tomography detection methods, comprising: synchronous acquisition compactor vibration source at source end reference signal and the ground surface response signal of measured region surface, establish the unified time base of both;Correlation function of source end reference signal and ground surface response signal is calculated, and the coarse estimation time is determined based on peak value.Extract feature frequency component from signal and obtain analytic signal phase information, calculate the phase difference of ground surface response signal at coarse estimation time relative to source end reference signal, and use the phase difference to determine fine time correction amount.Use fine time correction amount to correct coarse estimation time, obtain final elastic wave time and generate elastic wave velocity distribution image by inversion.The application breaks through the limitation of sampling rate on measurement accuracy by collecting real source end waveform and combining phase refinement technology, and improves the resolution and reliability of compaction quality detection.

The invention discloses a subspace joint parameter estimation algorithm for constructing an analytic signal based on Hilbert transform in high-precision multi-surface phase-shift interference, belongs to the technical field of high-precision optical interference measurement, and aims to solve the problems of inaccurate frequency estimation caused by spectrum leakage and a fence effect in a traditional algorithm. And the problem that a modern spectrum estimation algorithm cannot directly process real-value light intensity signals is solved. The method comprises the following steps: firstly, performing Hilbert transform on a real-value light intensity sequence to construct an analysis signal; then, a Hankel matrix is constructed based on the analysis signal, and subspace decomposition is carried out; further, taking the obtained high-precision frequency as prior information, and performing joint correction on the amplitude and the phase by using a double-section phase difference correction method; and finally, reconstructing the surface topography according to the corrected phase. According to the invention, the limitation of spectrum leakage and the like is overcome, the joint fine positioning of frequency, amplitude and phase is realized, and the precision, robustness and measurement repeatability of interference parameter demodulation are obviously improved.