77 results about "Analytic signal" patented technology

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 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 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 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 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.

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 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.

The application relates to the technical field of motor diagnosis, and discloses a motor eccentric fault diagnosis method and system based on current harmonic analysis. The method comprises the following steps: extracting a power frequency component of a three-phase stator current signal to obtain a residual current signal, and performing complex analytic envelope transformation on the residual current signal to obtain an envelope analytic signal; performing synchronous interpolation resampling on the envelope analytic signal to obtain a complex envelope signal; performing spectrum estimation on the complex envelope signal to obtain a discrete spectrum of a modulus sequence; performing equalization processing on the order spectrum line amplitude in the discrete spectrum to obtain a whitened spectrum, and inversely transforming and reconstructing the whitened spectrum into an angular domain amplitude signal of a target motor; performing cyclic stationary analysis on the angular domain amplitude signal to obtain a third-order cyclic cumulative quantity of the angular domain amplitude signal at a specific cycle frequency; and determining the type and severity level of the eccentric fault according to the third-order cyclic cumulative quantity. The application can improve the accuracy of motor eccentric fault diagnosis.

The invention discloses a rolling bearing fault diagnosis method based on acoustic framing. The method comprises the following steps of: firstly, carrying out Hilbert transform on an acquired acoustic signal of the rolling bearing, and constructing a dual-channel analysis expression containing instantaneous amplitude and instantaneous phase information; then, the analysis signal is divided into short-time frame segments according to a preset frame length and a preset step length through an acoustic framing embedding module, and a frame-level embedding vector with a unified dimension is generated through linear mapping, so that local transient impact characteristics are highlighted, and the sequence length is effectively compressed; an improved lightweight Transformer encoder is adopted for time sequence feature extraction, the encoder is combined with a low-dimensional multi-head self-attention mechanism and a feedforward network based on SiLU activation and deep convolution so as to model cross-frame global dependency and a short-range local structure at the same time, and finally intelligent recognition of multiple types of faults of the rolling bearing is completed through global feature vectors of category tokens.

This invention discloses a real-time wavenumber spatial resampling method and system for SS-OCT, relating to the field of signal processing technology. The method involves simultaneously acquiring a K-clock signal and an OCT interferometer signal, and performing filtering preprocessing on each. The preprocessed K-clock signal is then subjected to a Hilbert transform to construct an analytical signal and extract the instantaneous phase, forming an instantaneous phase sequence. A preset ideal equal-wavenumber interval phase sequence is used as the target phase sequence. The target phase sequence is matched with the instantaneous phase sequence, and the position index of each target phase in the instantaneous phase sequence is calculated to obtain the remapped sampling point index. Based on the remapped sampling point index, the preprocessed OCT interferometer signal is processed using the SINC interpolation method to obtain a resampled, equal-wavenumber interval OCT signal. This application utilizes the SINC interpolation algorithm to perform real-time, high-precision resampling during the data acquisition stage, meeting the requirements of high-speed real-time imaging.

The application discloses a high-precision instantaneous frequency inversion method of continuous instantaneous phase, relates to the technical field of data processing, and comprises the following steps: S1, inputting a real signal, processing, and acquiring a frequency spectrum; S2, acquiring an analytic signal based on the frequency spectrum; and S3, using high-precision instantaneous frequency inversion based on polynomial fitting based on the analytic signal to obtain a final polynomial fitting high-precision instantaneous frequency. The application can remove periodic jumps in the instantaneous phase obtained by Hilbert transform and arctangent function, thereby obtaining a continuous instantaneous phase in which the phase periodic jump is eliminated and a monotone increasing continuous instantaneous phase used for high-precision instantaneous frequency inversion.

The application relates to a low-altitude aircraft information identification and monitoring method, system, device and medium, and belongs to the technical field of airspace management. The method comprises the following steps: configuring a radio frequency receiving module to capture aircraft broadcast signals of a preset frequency band; performing a low-pass filtering operation on the aircraft broadcast signals, 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 a frame header identifier, calling a corresponding decryption algorithm, and outputting flight data; matching the identity code with a pre-stored record database to generate a legality verification result of the aircraft; constructing a space-time identification data packet and processing the same through an airspace state analysis engine to generate 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. The application realizes accurate grasping of the real state of low-altitude aircraft, and improves the efficiency of airspace traffic management.

This application discloses a frequency setting method, apparatus, device, and storage medium for an FM terminal. The method includes: triggering a timeout when receiving a broadcast signal at the default frequency stops; if the FM broadcast terminal does not receive the broadcast signal at the default frequency within a first signal timeout period, then switching to a pre-switching frequency after the timeout period; and when an RDS signal transmitted by a handheld transmitter is received, parsing the target RDS protocol in the RDS signal to obtain the requested setting frequency, and switching the pre-switching frequency to the requested setting frequency. Therefore, when the FM broadcast terminal does not receive a broadcast signal at the default frequency, there is a need to switch the FM frequency. In this case, there is no need to use a host computer connected to a serial port for setting; simply receiving the RDS signal transmitted by a remote handheld transmitter is sufficient to complete the FM frequency switching, reducing the difficulty of switching the FM broadcast terminal's frequency and improving the FM broadcast terminal's frequency modulation efficiency.

The invention discloses a feature extraction and identification method for a radio frequency signal of an unmanned aerial vehicle, and belongs to the technical field of radio signal monitoring and signal identification. The method comprises the following steps: constructing a cyclic autocorrelation function for an original radio frequency signal, and extracting a characteristic cyclic frequency; enhancing the original radio frequency signal based on the characteristic cycle frequency, and obtaining a preliminary effective signal in combination with a cycle autocorrelation function; extracting an instantaneous phase of the initial effective signal, and obtaining a direct path effective signal according to a phase second-order variable quantity; phase and amplitude of the analytic signal of the effective signal of the direct path are extracted, modulation intensity of the two signals is obtained, and a modulation coupling function is constructed; extracting modulation instability from the modulation coupling function, extracting cyclic rigidity through cyclic mapping, and calculating cyclic instability; and finally, weighting the modulation instability and the cyclic instability to obtain an interference confidence coefficient, and when the interference confidence coefficient is smaller than a preset confidence coefficient threshold value, determining that the signal is an unmanned aerial vehicle signal. The identification precision of the radio frequency signal of the unmanned aerial vehicle is improved.

This invention provides an intelligent supply chain scheduling method and system that integrates a large-scale model, belonging to the field of intelligent supply chain scheduling technology. The method includes first collecting production line sensor signals, supplier engineering change notifications, and market commentary text. Implicit quality characteristics of component batches are extracted by analyzing the signals, and a technology transmission network with the impact of changes as weights is constructed based on this. User sentiment in the market commentary is quantified as tolerance constraints on specific technical parameters and injected back into the network to form a constraint network. Supply chain disturbance events are simulated on this constraint network, and the strength of their transmission path's impact on performance constraint boundaries is evaluated, thereby generating preventative scheduling plans. Finally, with the goal of minimizing inter-stage switching costs, a full-cycle, staged scheduling instruction sequence is optimized. This invention achieves a closed loop from market perception to preventative mobilization, enhancing the supply chain's proactive immunity and overall resilience to internal and external uncertainties.

The invention relates to the technical field of electrical engineering and intelligent detection, and discloses a flame-retardant low-smoke halogen-free coaxial cable detection method based on edge calculation. According to the scheme, an excitation end and a response end are set under one-dimensional coordinates, and constant-amplitude single-frequency reference excitation is output; the response end acquires voltage according to given sampling frequency, interval and point number and performs range cutting; screening samples by using a null drift threshold value, if the set is empty, marking the set as invalid, and if the set is non-empty, calculating a standing-wave ratio and obtaining a standing-wave deviation with a reference difference; performing Hilbert transformation on the cutting sequence to generate an analysis signal and an instantaneous phase; carrying out cycle-crossing expansion on the point-by-point phase difference, averaging, and comparing with a theoretical step length to obtain a phase deviation; normalizing the phase deviation and synthesizing the phase deviation and the standing wave deviation into a joint index; counting a mean value and a maximum value of the health reference sample and setting a threshold value; and performing judgment, recording and graded reporting according to the joint index and the threshold value in each period.

The invention discloses a non-stationary signal time-frequency analysis method based on an adaptive offset window. The method comprises the following steps: preprocessing an input signal to obtain an analysis signal; calculating instantaneous frequency and identifying trend characteristics of the instantaneous frequency; constructing a self-adaptive offset window according to the instantaneous frequency trend characteristics; the method comprises the following steps: constructing self-adaptive bias Chirplet transformation by fusing a self-adaptive bias window and generalized linear Chirplet transformation; and a corresponding time-frequency spectrum is obtained by using adaptive bias Chirplet transformation. According to the method, the energy diffusion phenomenon under dense frequency components can be effectively inhibited, the aggregation and resolution of time-frequency representation are remarkably improved, accurate description of instantaneous characteristics is realized, and excellent anti-noise performance is shown.

The present application relates to the technical field of geophysical exploration of oil and gas resources, and more particularly to a gather amplitude-preserved frequency-raised detuning correction method based on complex domain Wiener filtering. The gather amplitude-preserved frequency-raised detuning correction method based on complex domain Wiener filtering comprises the following steps: constructing an analytical signal of a pre-stack gather complex domain and obtaining a maximum instantaneous amplitude of the pre-stack gather; selecting a target trace from the pre-stack gather; performing Wiener filtering on the remaining traces in the pre-stack gather except the target trace according to the target trace and by obtaining a Wiener filter operator of the analytical signal; obtaining a maximum instantaneous amplitude of the pre-stack gather after Wiener filtering, and determining a proportional coefficient of the maximum instantaneous amplitude before Wiener filtering and the maximum instantaneous amplitude after Wiener filtering; and obtaining a required pre-stack gather by performing AVO amplitude compensation on the pre-stack gather after Wiener filtering. The present application overcomes the problem of missing seismic data when processing the pre-stack gather.

This invention relates to the field of bridge inspection technology, specifically to a bridge displacement detection method and system based on phase information. The method includes: acquiring acceleration vibration response signals from at least two measuring points on the bridge; filtering out noise and drift using a bandpass filter; performing a Hilbert transform on the filtered signals to obtain an analytical signal and extracting the instantaneous phase sequence; calculating the cross-correlation function of the instantaneous phase sequences of adjacent measuring points and determining the phase difference time sequence through the maximum value; correlating the phase difference time sequence with the distance between measuring points to convert it into a relative displacement time sequence; integrating the relative displacement time sequence twice to obtain a cumulative relative displacement value; using this cumulative value as a benchmark, and combining it with the absolute displacement calculation results of each measuring point to infer the overall bridge displacement; and performing wavelet noise reduction on the overall displacement to obtain the final detection result. This method can improve the accuracy and stability of displacement detection and is suitable for displacement monitoring of bridge structures.