51 results about "Frequency dispersion" patented technology

The invention relates to the technical field of underwater detection, and discloses an underwater comprehensive detection system. The system collects multi-dimensional acoustic data including sound wave reflection intensity, propagation time delay and frequency dispersion characteristics of a target water area through an underwater sonar array; dividing the detection area into a plurality of layered units according to a water attenuation coefficient and a substrate reflection characteristic of the acoustic data, and extracting an environment intrinsic parameter of each layered unit; constructing an acoustic propagation path model based on the environmental intrinsic parameters, and generating adaptive filtering parameters in combination with a preset noise suppression strategy; calling sonar array hardware configuration data, matching filtering parameters with an array beam forming mode, and calculating a detection sensitivity threshold value of each layered unit; and integrating the sensitivity threshold and the acoustic data, generating a three-dimensional acoustic characteristic spectrum of the target water area, and marking the space coordinates and confidence level of the abnormal area. The system can improve the comprehensiveness and accuracy of underwater detection, and meets the requirement of high-precision detection.

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 relates to the technical field of oil and gas geophysical exploration, and particularly discloses a tight sandstone gas reservoir fluid mobility gradient attribute prediction method and system.The method comprises the steps that a reflection coefficient expression containing a fluid mobility item is constructed, and a formula for calculating fluid mobility through frequency dispersion attributes is deduced; constructing a fluid mobility gradient attribute related to the frequency and the incident angle of the seismic wave; the method comprises the following steps: establishing a double-pore rock physical model, generating a synthetic seismic record, applying frequency variation AVO inversion to the synthetic seismic record, and extracting a bulk modulus dispersion attribute and a shear modulus dispersion attribute; and calculating the fluid fluidity changing along with the frequency and the incident angle, and calculating the gradient attribute of the fluid fluidity based on a gradient attribute calculation formula and the fluid fluidity. According to the method, seismic wave frequency dispersion and attenuation response caused by permeability and gas saturation are fully utilized, the seismic gradient attribute of the fluid fluidity and the calculation method are constructed, and high-precision prediction of the fluid fluidity by applying seismic signal elasticity and frequency dispersion rock physical information is realized.

The invention relates to the field of power system state monitoring, and discloses a power equipment fault diagnosis system suitable for a complex power grid environment, and the system comprises a propagation medium model building unit which is used for dynamically correcting a model through benign transient waves; the transient traveling wave synchronous acquisition unit is used for synchronously acquiring traveling wave data at high precision; the fault positioning unit is used for determining a fault position based on a time difference residual minimization principle; and the fault property and equipment state analysis unit is used for carrying out deep analysis by comparing actually measured and theoretical reflected wave path spectrums and frequency dispersion characteristics. The method comprises the following steps: constructing and dynamically correcting a transient wave propagation medium model; synchronously acquiring transient traveling waves excited by an electrical event; calculating a fault physical position; the propagation characteristics of the transient waves are analyzed to determine fault properties and device states. According to the invention, the electrical asymmetry hidden danger can be identified and positioned by actively injecting the pure-sequence traveling wave probe, and the combination of passive diagnosis and active early warning is realized.

The invention discloses a fire-fighting pipeline water leakage identification method and system based on multi-modal data processing, and relates to the field of pipeline water leakage identification, and the method comprises the steps: firstly, carrying out the fusion of sound and vibration waveforms and geographic coordinate data, and carrying out the decoupling of a complex broadband water leakage signal into a series of narrowband intrinsic mode components through employing a variational mode decomposition technology; on this basis, a spatial topology construction technology based on a GPS is introduced, and an accurate physical path provided by geographic coordinates is used as a spatial constraint vector to construct a closed-loop feedback mechanism of acoustics and geographic information. Spatial constraint is applied to adaptive group velocity matching under a frequency dispersion effect, and actual group velocities of different frequency bands propagating in a tube are dynamically calculated. And finally, combining a multi-modal weighted fusion strategy, and integrating the corrected distance difference of each frequency band to obtain an accurate positioning result, thereby realizing effective compensation and correction of the frequency dispersion error in the inhomogeneous medium by using multi-modal data.

The invention discloses a zero-dispersion nonlinear MEMS accelerometer for monitoring construction stress of a floating fan platform, and belongs to the technical field of ocean engineering structure monitoring. The zero-frequency-dispersion nonlinear MEMS accelerometer comprises a mass block, an amplification beam pair assembly, an electrode system and resonant beams arranged on the two sides of the mass block in a bilateral symmetry mode, and the mass block is connected with the resonant beams through the amplification beam pair assembly. According to the invention, adjustable static nonlinearity is introduced in the capacitance excitation process of the double-end clamped resonant beam, and the adjustable static nonlinearity is matched and counteracted with the geometric nonlinearity of the resonant beam, so that the resonator enters a zero-frequency dispersion working area within a preset excitation range, and therefore, under the working conditions of construction load disturbance, structural vibration amplitude fluctuation and the like, the resonance efficiency of the resonator is improved. Frequency response information related to structural dynamic characteristics can still be stably output, and a high-stability perception basis is provided for inversion analysis of welding residual stress and structural health states.

The application discloses a component fatigue micro-damage early identification method based on a nonlinear static component, and particularly relates to the technical field of material nondestructive testing and structural health monitoring, which comprises the following steps: arranging an excitation probe and a receiving probe on the surface of a component to be measured; selecting an excitation frequency based on a frequency dispersion curve and generating a Hanning window modulated wave; collecting a propagation response signal; extracting a static component amplitude A and a fundamental wave amplitude A through time-frequency processing; calculating a nonlinear static parameter beta=A / A²; further calculating a first derivative S(N) and a second derivative ΔS(N) of beta with respect to a fatigue loading cycle N; and identifying a dislocation dominant stage, a dislocation saturation or rearrangement stage, a micro-crack initiation stage and a macro-crack formation stage according to the first derivative S(N) and the second derivative ΔS(N). The application can be used for early stage identification of the evolution process of component fatigue micro-damage.

The present application relates to the technical field of machining tools, and proposes a tool life real-time monitoring and early warning method and system. First, the original acoustic emission signal of the tool working site is obtained, adaptive cavitation noise cancellation processing is performed, and comparison index calculation is performed based on the processed signal, including entropy change and kurtosis calculation, frequency dispersion-attenuation coupling analysis is performed in combination with short-time Fourier transform, and frequency dispersion slope change rate and energy attenuation ratio are extracted. Subsequently, the current tool individualized threshold vector identified by the deep learning model is obtained from the cloud, compared with the comparison index, the life remaining proportion is determined, and early warning is implemented. Through millisecond acoustic emission signal analysis, microscopic secondary detection and cloud model self-learning, the present application realizes millisecond response, extremely low false alarm rate and seamless system integration under the premise of no shutdown and unattended, and breaks through the traditional fixed tool changing period, and approaches the real service life limit of the tool.

The application discloses a coal seam roof sandstone aquifer water enrichment evaluation method based on three-dimensional seismic, which comprises the following steps: S10, collecting drilling data, well logging data and high-precision three-dimensional seismic data of a research area; S20, inverting pre-stack seismic data to obtain a P-S wave velocity ratio of the roof sandstone aquifer; S30, performing time-frequency analysis on post-stack seismic data and performing spectral equalization on frequency domain seismic data; S40, inverting a longitudinal wave frequency dispersion attribute of a target layer according to a reflection coefficient approximate formula and the time-frequency spectrum of the post-stack seismic data after the spectral equalization; S50, using an entropy weight method to calculate weight values of the P-S wave velocity ratio and the longitudinal wave frequency dispersion attribute; and S60, constructing a water enrichment indication factor calculation formula and evaluating water enrichment of the sandstone aquifer according to the water enrichment indication factor. The method is based on the theoretical basis of seismic rock physics, has low cost, high operability, more statistical significance, can quickly and accurately evaluate water enrichment of the coal seam roof sandstone aquifer, and provides technical support for development and utilization of coal resources.

The invention relates to the technical field of roadbed cavity detection, in particular to a roadbed cavity intelligent detection method based on multi-feature fusion and deep learning and related equipment. The method comprises the following steps: acquiring road-base pulse signal data and preprocessing to form a preprocessed signal sequence; multi-dimensional features such as amplitude attenuation and frequency dispersion change are extracted based on a cavity physical effect model, and a high-discrimination fusion feature vector is generated through feature fusion and dimension reduction; and training a deep learning cavity recognition model by using the fusion features to realize automatic recognition of the cavity existence probability of the to-be-detected road section. And finally, spatial positioning and risk assessment are performed by combining cross-correlation analysis and frequency dispersion curve inversion, so that high-precision detection and reliable judgment of the roadbed cavity are realized. According to the invention, the accuracy, efficiency and intelligent degree of roadbed cavity detection are improved.

The invention relates to the technical field of image processing and deep learning, in particular to an automatic surface wave inversion method and system, and the method comprises the steps: receiving original seismic information, sequentially carrying out the mean value removal, trend removal and spectrum whitening preprocessing of surface wave information, calculating a single-component noise cross-correlation function and a nine-component noise cross-correlation function based on the preprocessed data, and obtaining a single-component noise cross-correlation function and a nine-component noise cross-correlation function; and based on a time-frequency analysis method, calculating a surface wave group velocity and a velocity frequency dispersion energy diagram through the cross-correlation function, automatically extracting a frequency dispersion curve from the velocity frequency dispersion energy diagram by using an artificial intelligence frequency dispersion extraction method, screening frequency dispersion files of which effective frequency dispersion points and signal-to-noise ratios meet a preset standard, and calculating the surface wave group velocity and the velocity frequency dispersion energy diagram through the cross-correlation function. And inverting the parameters of the three-dimensional shear wave velocity model based on the underground interface constraint three-dimensional shear wave velocity inversion method to obtain a three-dimensional shear wave velocity model. The problems that in the prior art, efficiency is low, the operation process is complex, and the professional threshold is high are solved.

The invention provides a radar sea surface target detection method and system. The method comprises the following steps: removing the influence of noise in a radar echo signal by adopting an improved wavelet threshold denoising method; according to the method, sea clutters are preprocessed in combination with a TQWT algorithm based on clutter reconstruction and a TQWT parameter adaptive calculation process, time-frequency analysis is carried out on preprocessed signals, two time-frequency features including the maximum singular value proportion and the frequency dispersion are proposed, and a support vector machine is used for classifying sea clutter units and target units; and optimizing the optimal transformation order in the SVD-FRFT algorithm by adopting an improved Raccoon longnose optimization algorithm to further process the target unit. The method is suitable for a low-speed small target scene in the sea surface, the influence of the radar on sea clutters in sea surface target detection is overcome, and the target detection performance is improved.

The invention discloses a surface wave frequency dispersion image generation method, a medium, equipment and a product, and relates to the field of surface wave exploration, and the method comprises the steps: obtaining time domain surface wave signals received by a geophone, and arranging the time domain surface wave signals according to spatial positions to form a gather; performing S transformation on the time domain surface wave signal of each seismic channel to obtain a complex value time-frequency spectrum; based on the time-frequency spectrum, extracting a complex frequency spectrum corresponding to main energy on each frequency point of each seismic channel, and performing normalization processing to obtain a phase spectrum; selecting a plurality of heuristic phase velocities in a preset phase velocity scanning range, performing coherent superposition on phase spectrums corresponding to all seismic traces for each frequency and the heuristic phase velocity, and constructing an energy function of a frequency-phase velocity domain; and when the tentative phase velocity is consistent with the actual surface wave phase velocity, obtaining a surface wave phase velocity frequency dispersion energy image based on an energy function of a frequency-phase velocity domain. According to the invention, the anti-interference capability and stability of surface wave frequency dispersion imaging under complex geology or noise conditions can be improved.

This invention belongs to the field of applied geophysical logging technology, specifically relating to a method for identifying low-resistivity oil layers based on time-frequency joint analysis. The method comprises the following steps: constructing a frequency-varying invasion factor based on multi-frequency array induced resistivity data at different times during drilling and after completion; constructing a time-varying dynamic index based on the frequency-varying invasion factor at different times during drilling and after completion; constructing a weighted dispersion index based on the time-varying dynamic index; calculating the average value of the time-varying dynamic index and the average value of the weighted dispersion index within the layer to be identified, comparing them with preset thresholds, and identifying the fluid properties based on the comparison results. This invention establishes a dual-verification identification mechanism for low-resistivity oil layers by integrating time-series evolution information and multi-frequency dispersion characteristics, and sets dual thresholds to improve the corresponding logging interpretation accuracy.

A microwave photon beam forming network architecture based on switch switching type optical adjustable true delay line and its phased array radar system. The architecture realizes delay difference adjustment of multiple optical signals by modulating microwave signals in the optical domain and utilizing the characteristics of multiple adjustable delay paths in a single channel switch switching type delay line, thereby supporting high precision, wideband beam forming without beam oblique view while greatly reducing the number of delay lines and delay units; through two or more levels of delay configuration, the network can flexibly meet the wideband delay compensation requirements of different array antenna units, has relatively low complexity and strong dynamic reconfigurable ability, is suitable for implementation of large-scale photon integrated chips, the number of delay lines of the application is reduced by about 50%, and no frequency dispersion is generated, which can significantly reduce the system complexity, cost and power consumption, and is especially suitable for wideband phased array systems such as millimeter wave, satellite communication and radar detection.

The invention discloses a seismic service system for micro-motion exploration and a data processing method, and relates to the technical field of geophysical exploration, and the system comprises the steps: deploying a distributed sensor array, and achieving the high-precision time synchronization through a self-organizing wireless network; continuously collecting environment vibration data and preprocessing the environment vibration data; calculating a cross-correlation function based on a phase weighted stacking algorithm to extract an empirical Green function; acquiring a high-precision Rayleigh wave phase velocity frequency dispersion curve by adopting a time-frequency domain phase matching pursuit technology; constructing a three-dimensional shear wave velocity model by combining a Markov chain Monte Carlo inversion algorithm of Bayesian reasoning, and introducing transverse constraint and prior geological information; and establishing a quality feedback control mechanism to optimize acquisition and processing parameters. According to the method, the stability of micro-motion signal processing and the resolution of underground structure imaging in a low signal-to-noise ratio environment are remarkably improved, full-process automation is realized by relying on a cloud service platform, and a single exploration processing period is shortened to be within 48 hours.

The present application belongs to the technical field of rock physics, and is especially a longitudinal wave velocity calculation method under a gas-water system. The method comprises the following steps: S1: obtaining longitudinal and transverse wave velocities of a sample under normal pressure and under a limit high pressure through experiments; S2: calculating a skeleton bulk modulus and a clay water relaxation time according to a sample XRD mineral analysis result; S3: converting the wave velocities into moduli; S4: calculating saturated volcanic lava longitudinal wave velocities considering frequency dispersion according to a Gurevich formula; S5: measuring a nuclear magnetic T2 spectrum of the sample under a saturated state; S6: calculating bulk moduli under different saturation degrees; and S7: converting to obtain longitudinal wave velocities under different saturation degrees. The present application explains the reason why the volcanic lava saturation degree-longitudinal wave velocity rule presents a "convex" shape from a mechanism, and effectively calculates volcanic lava longitudinal wave velocities under different saturation degrees.

The invention discloses a method for dynamically judging a perimeter alarm threshold value of a detection cable based on double-cable coupling, which relates to the technical field of perimeter alarm of the detection cable, and comprises the following steps of: on the basis of a frequency spectrum jump criterion set, calculating a consistency curvature of a main frequency scatter point track of a double-cable coupling signal, analyzing a ratio of periodic repetition term density to energy return, and calculating a threshold value of the perimeter alarm threshold value of the detection cable; judging whether the detection cable passes through the electromagnetic reflection structure or not; and under the condition that the detection cable passes through the electromagnetic reflection structure, relative slippage distribution of signal channels corresponding to the first cable and the second cable in the double-cable coupling signal on a frequency axis is extracted, and a feature vector set for describing spectrum dislocation features of the double-cable coupling signal is generated. According to the invention, the problem of alarm determination misalignment caused by frequency spectrum dislocation when a double-cable coupling detection cable passes through an electromagnetic reflection structure is solved, and accurate determination and adaptive dynamic regulation and control of a perimeter alarm threshold in a complex structure environment are realized.

An active and passive source combined geological detection method for a shield tunnel. The method comprises: acquiring an active-source seismic-wave reflected signal and a passive-source acoustic-wave reflected signal; on the basis of the active-source seismic-wave reflected signal, obtaining an active-source geological detection imaging result by using a longitudinal and transverse wave combined imaging principle; on the basis of the passive-source acoustic-wave reflected signal, obtaining a passive-source geological detection imaging result by using a frequency dispersion extraction-transverse wave velocity inversion method that fuses spatial autocorrelation and a half-wavelength model; and by using the active-source geological detection imaging result as a main part and the passive-source geological detection imaging result as an auxiliary part, and in view of an adaptive adjustment coefficient therebetween, obtaining an adverse geological risk level of a region to be detected.

The invention provides a formation parameter determination method and device, equipment, a storage medium and a program product. Relates to the technical field of oil exploration seismic data acquisition and processing. The method comprises the steps of obtaining an initial stratum model; a target stratum inversion function and an iterative residual vector are determined based on the initial stratum model and the seismic exploration data, the target stratum inversion function is determined by a Scholte wave frequency dispersion curve, and the iterative residual vector is determined by a Scholte wave partial pilot frequency dispersion curve; determining a stratum parameter updating formula based on the target stratum inversion function and the iterative residual vector; performing updating iteration on the initial stratum model based on a stratum parameter updating formula and a preset horizon layering rule to determine a target stratum model; and determining formation parameters based on the target formation model, wherein the formation parameters comprise the longitudinal wave velocity, the transverse wave velocity and the formation medium density. According to the method provided by the invention, the accuracy and reliability of the Schlte wave technology in seismic exploration are effectively improved.

The invention relates to a micro-motion frequency dispersion curve inversion method and device, electronic equipment and a storage medium. The micro-motion frequency dispersion curve inversion method comprises the following steps: acquiring micro-motion waveform data and an actually measured frequency dispersion curve under different frequencies; frequency dispersion curve extraction is carried out on the micro-motion waveform data through a high-resolution frequency-wave number method, an initial Rayleigh wave frequency dispersion curve is obtained, and an inversion model is constructed according to the initial Rayleigh wave frequency dispersion curve; performing recursive calculation and forward calculation on the initial Rayleigh wave frequency dispersion curve to obtain a recursive theoretical curve; correcting the initial Rayleigh wave frequency dispersion curve according to a difference value between the recursive theory curve and the actually measured frequency dispersion curve to obtain a target Rayleigh wave frequency dispersion curve; performing iterative screening on the target Rayleigh wave frequency dispersion curve according to the inversion model to obtain an inversion result; the technical defects that a traditional method depends on the quality of a frequency dispersion curve and is prone to falling into a local optimal solution are effectively overcome by constructing an inversion model in combination with a recursive correction and iterative screening mechanism, and the method has the advantages of improving the inversion precision, avoiding the local optimal solution and improving the calculation efficiency.

The invention relates to the technical field of seismic data processing, and particularly discloses an offset superposition data frequency division method and device, and the method comprises the steps: mapping a frequency to a wave number through employing a frequency dispersion relation in imaging; converting the wave number into a frequency operator; performing frequency division on the offset superposition data based on a frequency operator to obtain a frequency division result of the current frequency band; and repeating the steps to obtain frequency division results of all frequency bands. According to the method, a set of offset superposition data frequency division algorithm with low calculation amount is researched and developed by utilizing a wave equation frequency dispersion relation, the time-consuming step of prestack depth offset is not carried out, and the frequency division is directly carried out by utilizing an offset superposition data body, so that the effect close to prestack frequency division is achieved on the premise of keeping high efficiency, the high efficiency of calculation is ensured, and the calculation efficiency is improved. The problem of huge calculation amount of pre-stack frequency division and the problem of unidirectional wavenumber approximation of post-stack frequency division are solved.

The invention discloses a method for determining guided wave frequency dispersion characteristics of a liquid-filled steel riser, which is characterized in that three-dimensional guided wave propagation is equivalent to a radial one-dimensional intrinsic problem under an axial symmetry condition, a relation between a complex wave number and frequency dispersion can be obtained only by dispersing the radial direction, and high degree of freedom of three-dimensional modeling is avoided. Internal fluid is not coupled through additional boundary terms, and is merged into the overall system by adopting a section contribution matrix, so that fluid-solid consistent assembly in the same system is realized, and error sources of coupling inconsistency are reduced. An external infinite water area does not use an absorption layer for approximation, and external water is equivalent to a wavenumber-related damping boundary by using radiation impedance meeting an infinite radiation condition; and the self-consistent complex wave number is solved through linearization and inverse iteration, so that the radiation modeling accuracy and solvability are improved.

The invention relates to the technical field of nondestructive testing, and discloses a multi-mode mechanical wave optimal mode selection method, system, equipment and medium for buried component detection, and the method comprises the steps: building a buried component cylindrical waveguide model based on an elastodynamic theory, solving the frequency dispersion characteristic of a multi-mode mechanical wave, and calculating the optimal mode of the buried component; calculating to obtain a frequency dispersion curve and a modal feature vector of the mechanical wave propagating in the waveguide; setting a defect boundary and obtaining defect parameters, and calculating to obtain a boundary reflection coefficient; analyzing the distribution proportion of the energy of each mode in the axial direction and the radial direction, and analyzing the vibration energy distribution of each mode; and based on the boundary reflection coefficient and the vibration energy distribution, screening the optimal mode of the mechanical wave. According to the method, the boundary reflection coefficient for quantitatively evaluating the modal sensitivity is provided, blindness of traditional experience selection is avoided, and the signal-to-noise ratio of a detection signal and the intensity of defect echoes are remarkably improved by selecting the optimal modal with the high boundary reflection coefficient and low attenuation.

The invention relates to the field of ocean geophysical exploration, and provides a near-seabed transverse wave exploration method and system based on an active source earthquake, and the method comprises the steps: collecting seismic data based on an active source earthquake system; interface waves recorded by the vertical component detector and the hydrophone component detector are separated; frequency dispersion curve energy spectrums of the interface waves recorded by the vertical component detector and the interface waves recorded by the hydrophone component detector are calculated respectively; obtaining an optimal weighting coefficient; obtaining a superposed frequency dispersion curve energy spectrum; and based on a half-wavelength method of Poisson's ratio constraint, carrying out inversion by using fundamental frequency information in the superposed frequency dispersion curve energy spectrum, and obtaining a transverse wave velocity structure of a near-seabed area below the measuring line. According to the method, the frequency dispersion curve is extracted by preferably selecting the data of the vertical component geophone and the data of the hydrophone component geophone with prominent fundamental frequency energy, and the transverse wave velocity inversion is carried out, so that a high-quality data basis is provided; the Poisson's ratio is introduced into inversion, and system errors caused by model simplification are effectively reduced.

The application relates to the field of power system state monitoring, and discloses a power equipment fault diagnosis system suitable for a complex power grid environment, which comprises a propagation medium model construction unit, a transient traveling wave synchronous acquisition unit, a fault positioning unit and a fault property and equipment state analysis unit. The propagation medium model construction unit is used for dynamic correction of a benign transient wave. The transient traveling wave synchronous acquisition unit is used for high-precision synchronous acquisition of traveling wave data. The fault positioning unit is used for determining a fault position based on a time difference residual minimization principle. The fault property and equipment state analysis unit is used for deep analysis by comparing a measured reflection wave path spectrum and a theoretical reflection wave path spectrum and by comparing frequency dispersion characteristics. The method comprises the following steps: constructing and dynamically correcting a transient wave propagation medium model; synchronously acquiring transient traveling waves excited by electrical events; calculating a fault physical position; and analyzing propagation characteristics of the transient traveling waves to determine a fault property and an equipment state. The application can also identify and position electrical asymmetry hidden dangers by actively injecting a pure positive sequence traveling wave probe, and realizes the combination of passive diagnosis and active early warning.

The present application relates to the technical field of geophysical exploration, and discloses a kind of active source seismic surface wave's common station pair coherent stack enhancement methods for low signal-to-noise ratio.It includes: generating Green function according to the relative relationship of seismic source position and station pair: when station pair is located on the same side of seismic source, the cross-correlation of the seismic record of two stations in station pair is calculated, and cross-correlation Green function is generated;when station pair is located on the opposite side of seismic source, the cross-correlation of the seismic record of two stations in station pair and the seismic record of reference station at seismic source is calculated respectively, and then convolution calculation is carried out, and convolution Green function is generated;Based on the cross-correlation Green function and convolution Green function after stacking, frequency dispersion energy diagram is calculated respectively;Stack two kinds of frequency dispersion energy diagram to generate final frequency dispersion diagram, which is used to extract frequency dispersion curve.The active source seismic surface wave signal common station pair coherent stack enhancement method proposed in the present application effectively improves the surface wave signal-to-noise ratio and frequency dispersion diagram quality without increasing the cost of data acquisition.

The invention discloses an urban underground medium ultra-short time imaging method and system based on traffic noise tail waves, and relates to the technical field of geophysical exploration, and the method comprises the steps: obtaining traffic noise data, and carrying out the segmentation; performing mutual dry interference processing on each data segment to generate a virtual shot gather; according to the signal-to-noise ratio feature, the time-frequency energy distribution feature and the polarization feature of the virtual shot gather, a tail wave data segment is screened out from all the data segments; performing phase weighted stacking on the tail wave data segments; performing frequency dispersion imaging on the comprehensive data segment obtained by superposition to obtain a surface wave frequency dispersion curve; and performing inversion according to the surface wave dispersion curve to obtain an underground shear wave velocity structure image. The signal quality of the selected tail wave part is ensured through the signal-to-noise ratio, time frequency and polarization triple characteristics, high-precision and high-efficiency urban underground medium imaging is completed in an ultra-short time, the anti-interference capability is high, and the exploration cost is low.

The application 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, which comprises the following steps: collecting stator current, rotating speed and load signals; generating alpha beta current components through Clark transformation, constructing analytical signals, extracting instantaneous phases, and calculating instantaneous frequencies; combining the rotating speed to establish a mapping relationship, resampling the current signals to eliminate frequency dispersion; adopting multi-scale synchronous compression wavelet transformation to obtain a high-resolution harmonic energy distribution diagram; extracting the energy concentration degree, peak value offset and bandwidth expansion coefficient in a characteristic frequency band, inputting a pre-trained multilayer perception classifier, and outputting a fault type. Through high-precision time-frequency focusing and multi-dimensional feature fusion, the application significantly improves fault recognition accuracy and robustness, and can realize online diagnosis of various typical faults only by using current signals.