842 results about "Wave velocity" patented technology

The invention discloses a power distribution network three-core cable fault distance measurement analysis method and system, and relates to the technical field of fault distance measurement, and the key points of the technical scheme are that the method comprises the steps: carrying out the empirical mode decomposition of three-phase voltage and current signals; generating a dynamic correction wave velocity based on the cable type, the environment temperature and the soil humidity parameter; determining the first arrival time of the wave head of the initial traveling wave according to the instantaneous frequency abrupt change point of the alpha-mode component, screening the second arrival time of the first reflected wave by using the amplitude gradient of the zero-mode component, and calculating the arrival time difference; and calculating an initial fault distance, and calling the impedance matrix to iteratively correct the initial fault distance. According to the method, the dynamic wave velocity is coupled with multiple factors, the limitation of single parameter correction is broken through, and the problem of transient drift of the wave velocity is solved; and the STFT high-frequency resolution and the wavelet low-frequency stability are fused, and the ridge continuity is optimized in combination with dynamic programming, so that the traveling wave head detection precision can be improved.

The invention relates to the technical field of dynamic weighing, and discloses a dynamic weighing error self-correction system based on multi-modal edge coordination, which comprises a multi-modal data acquisition module, a space-time alignment module, a dynamic error propagation modeling module and a coordination calibration and suppression module. According to the system, accurate positioning of an error source and whole-course tracking of a propagation path are realized through real-time construction of a vibration energy transfer topological graph and dynamic judgment of path priority, error diffusion is directly blocked by combining a piezoelectric ceramic reverse vibration wave neutralization technology, and the industrial problems of fuzzy error traceability and compensation lag in a traditional scheme are solved; through collaborative design of vibration wave velocity correction and temperature signal dynamic interpolation, space-time consistency compensation of cross-modal data is realized, and compensation logic conflicts are avoided in a cold-chain logistics temperature sudden change scene; based on an edge node intelligent dormancy and hidden fault self-sensing mechanism, the long-term stable operation of the system under the conditions of highway continuous weighing and industrial high load is ensured.

The invention discloses a data center seismic isolation performance detection method based on AI intelligence, and particularly relates to the technical field of seismic isolation performance detection. Earthquake vibration characteristic data are collected in real time on a data center building and equipment, earthquake input characteristics are extracted in combination with a historical earthquake wave database, a seismic isolation performance prediction model is constructed and trained, a foundation shear wave velocity gradient abnormal value and a seismic isolation layer dynamic displacement response deviation ratio are further extracted, a deviation index is comprehensively calculated, and a seismic isolation performance prediction model is constructed and trained. And classification processing is carried out according to the deviation level, especially under the condition of a middle deviation level, foundation physical parameters are dynamically updated, and the model is optimized, so that the accuracy of the prediction model and the self-adaptive capability of the system are remarkably improved, and the shock isolation safety and the continuous operation capability of the data center in a strong shock environment are effectively guaranteed.

The invention relates to an anisotropic elastic medium Rayleigh surface wave frequency dispersion curve inversion method, which comprises the steps of collecting near-earth surface wave exploration seismic data, obtaining a Rayleigh surface wave frequency dispersion energy diagram based on a phase shift method, and extracting a frequency dispersion curve from the frequency dispersion energy diagram based on a convolutional neural network artificial intelligence method; constructing a near-surface anisotropic elastic parameter initial model; calculating to obtain a theoretical Rayleigh surface wave dispersion curve by using a Rayleigh surface wave dispersion curve forward modeling method according to the current elastic parameter model; designing a loss function according to the observed Rayleigh surface wave dispersion curve and the theoretically calculated Rayleigh surface wave dispersion curve, and calculating and judging whether the loss function reaches a set threshold value or converges to a minimum value; if yes, outputting a current near-surface shear wave velocity model; if the conditions are not met, updating the shear wave velocity model by adopting a quasi-Newton method; and outputting the near-surface shear wave velocity model and the sensitive function of the Rayleigh surface wave frequency dispersion curve to the anisotropic elastic parameter after the loss function meets the condition.

The invention relates to a multi-branch power distribution network double-end traveling wave fault positioning method and system, and the method comprises the steps: deploying a plurality of measurement points based on the head and tail ends of a radial power distribution network and branch terminals, collecting topological information, and calculating the linear mode wave velocity; using the three-phase voltage data after the fault to extract traveling wave line mode and zero mode components through modulus decoupling; a line mode component with the strongest global mutation is selected as a reference, and a wave head time sequence table is generated through wavelet decomposition and mutation detection; and correcting the zero-mode wave velocity by combining the topology, the time sequence table and the line-mode wave velocity, and determining a fault interval and outputting a fault position after compensation and correction by using the line-mode and zero-mode wave head time difference. According to the invention, through a wave head time sequence analysis and time difference compensation mechanism based on cooperation of multiple measuring points, positioning errors caused by clock asynchronization and parameter disturbance are effectively overcome, accurate distance measurement which is not influenced by clock errors is realized, and the distance measurement precision is significantly improved; and meanwhile, the point distribution requirement is simplified, accurate judgment and positioning of a fault interval can be realized only by a branch single measuring point, and high economy and deployment flexibility are both achieved.

The invention relates to the technical field of data processing, and discloses an environment detection analysis method and system based on a simulation micro-motion signal excitation generator. The method comprises the following steps: generating a vertical vibration signal through an integrated structure of a constant-resistance vibration exciter and a special coupling base; performing multi-band signal excitation and station arrangement according to the frequency parameter combination; filtering and normalizing the original signal, and calculating a spatial autocorrelation coefficient; a frequency dispersion curve is extracted through an SPAC method; inverting an underground S-wave velocity structure by using a divergence genetic algorithm; and analyzing the speed abnormal region by adopting an edge detection algorithm, and determining the position and state of the box culvert body. According to the invention, high-precision non-destructive detection of the buried power pipeline box culvert body is realized in an urban complex underground environment.

The invention discloses a bridge engineering-oriented foundation pile quality detection system, which relates to the technical field of engineering quality detection, and comprises a data acquisition module configured to acquire detection data including foundation pile construction parameters, geological environment data, stress wave signals and geometric dimension parameters, the wave velocity correction module is configured to correct a standard wave velocity through a dynamic coupling algorithm, the defect depth calculation module is configured to calculate the defect depth of a foundation pile defect, and the credibility evaluation module is configured to output a credibility correction coefficient and feed back the credibility correction coefficient to the wave velocity correction module by quantifying errors of detection data; according to the method, through multi-physical field wave velocity correction, pile diameter-defect depth double correction and credibility quantitative iteration, a high-precision, objective and traceable integrated solution is systematically provided for bridge engineering foundation pile quality detection.

The invention discloses a rock damage assessment method fusing wave velocity and microscopic fracture, and belongs to the technical field of rock damage assessment, and the rock damage assessment method comprises the following steps: arranging a wave velocity testing device on a rock sample, and respectively making an unloaded rock sample and a damaged snapshot rock sample under different stress loading; microcosmic fracture information of the damaged snapshot rock sample is identified, a three-dimensional wave velocity model of the damaged rock sample under different stress loads based on a wave velocity test is constructed, and then a macro-micro scale fusion multi-dimensional data set is constructed; based on the macro-micro scale fusion multi-dimensional data set, constructing and training a rock damage identification model; and inputting the characteristic parameters of the rock sample to be evaluated into the rock damage identification model, identifying the damage distribution characteristics of the rock sample on the spatial scale, and evaluating the rock damage degree. According to the method, accurate prediction and evolution process evaluation of the rock damage degree and spatial distribution can be realized, and a reliable technical means is provided for disaster early warning, stability evaluation and risk prevention and control in complex rock mass projects such as deep mines and tunnels.

A concrete damage real-time positioning method based on laser induction and dynamic wave velocity correction comprises the following steps: constructing a damage induction platform integrated with a high-energy pulse laser, combining with a three-dimensional mobile platform to realize accurate positioning of a laser focus, and arranging a phase demodulation type optical fiber acoustic emission sensor array to construct a full-coverage monitoring network; synchronous acquisition of high-frequency acoustic emission signals is realized by adopting a multi-channel coupling phase demodulation system, and noise suppression is completed in combination with a self-adaptive wavelet threshold algorithm; a dynamic wave velocity attenuation model is established based on space-time reference information, a propagation path is optimized through a Basic Theta * path planning algorithm, a wave velocity field is reconstructed by applying an ART algebraic iteration algorithm, and a thermodynamic diagram is generated; and finally, constructing a convolution-graph neural joint network model, and realizing accurate monitoring and positioning analysis of the concrete structure damage through a damage probability distribution generation and multi-scale verification module by using a multi-modal data fusion and transfer learning technology.

The invention relates to the technical field of mine safety and geological environment evaluation, in particular to a mine goaf geological environment dynamic evaluation method based on digital twinning. The method comprises the following steps: constructing a digital twinborn model of a mine goaf, designing a data structure and a virtual-real mapping rule, collecting multi-source heterogeneous data, and performing spatio-temporal data indexing processing to form a spatio-temporal associated data stream; microseismic travel time data are extracted from the space-time associated data stream; performing parallel ray tracing and rapid inversion on the microseismic travel time data to obtain a wave velocity distribution initial value; carrying out wave velocity field self-adaptive grid refinement on the micro-seismic travel time data by utilizing the wave velocity distribution initial value to obtain a multi-resolution wave velocity field; and carrying out wave velocity change rate analysis on the multi-resolution wave velocity field to obtain a wave velocity variability tensor. According to the method, the abstract energy transfer process is concrete into a data field capable of being quantitatively analyzed, so that the geological environment of the goaf is accurately and dynamically evaluated.

The invention relates to the technical field, in particular to a power grid overhead line traveling wave recording fusion fault positioning system, which comprises signal acquisition, traveling wave event stamp capturing, zero-sequence current data flow generation, fault triggering, zero-sequence integral comparison based on time reference to generate an activation instruction, and fault recording. The characteristic topology associates and fuses the traveling wave amplitude and the zero-sequence peak value, calculates a node attenuation rate and marks a breakpoint, and the positioning solution links a double-end timestamp and a wave velocity library according to the position of the breakpoint to output a fault coordinate. According to the invention, accurate locking of the fault moment is realized through synchronous acquisition of multi-source signals; a transient window defined by traveling wave triggering ensures complete capture of features; branch identification precision is improved through current vector fusion; parameters are automatically adjusted through dynamic wave velocity matching to improve positioning accuracy; time synchronization and wave velocity compensation eliminate the influence of line parameters.

The invention belongs to the technical field of geotechnical engineering testing and site investigation, and provides a shear wave velocity estimation method based on a piezocone penetration test, which can accurately and conveniently estimate the shear wave velocity. The method specifically comprises the following steps of S1, carrying out a pore pressure static sounding test on a plurality of drill holes in a site, and obtaining pore pressure static sounding basic parameters and shear wave velocity of each drill hole tested in the depth direction, S2, interpreting derived parameters according to the pore pressure static sounding basic parameters, S3, carrying out soil layer division, soil type identification and soil body type judgment, and S4, carrying out soil layer classification, soil type identification and soil body type judgment. S4, selecting data tested by the same soil body type as an analysis object, performing fitting analysis on the scatter diagrams of the cone tip resistance and the shear wave velocity of the piezocone penetration test to obtain a fitting formula, and S5, obtaining normalized cone tip resistance and normalized shear wave velocity based on the cone tip resistance and the shear wave velocity, substituting the normalized cone tip resistance and the normalized shear wave velocity into the fitting formula in the step S4, and introducing a soil classification index to obtain a soil classification result. And obtaining a calculation expression of the optimal estimation shear wave.

The invention relates to the technical field of tunnel engineering geological construction, and discloses a tunnel surrounding rock crustal stress intelligent analysis method and system based on parameters while drilling. Dynamic coordinate system construction, mechanical specific energy calculation, Stacking model classification, wave velocity ellipsoid modeling, dynamic weight fusion and differential drive re-calibration are realized, and three-dimensional stress field high-precision reconstruction and construction parameter optimization are completed; the system comprises a multi-source sensing module, a dynamic modeling module, a hybrid analysis module, an adaptive fusion module, a three-dimensional reconstruction module and a closed-loop control module. According to the method, high-precision ground stress analysis is realized through cooperation of multi-source data fusion and a mixed model and combination of dynamic weight distribution and a local re-calibration mechanism. Complementation of a wave velocity ellipsoid physical model and a Stacking integrated learning model is innovatively adopted, and octree space reconstruction and closed-loop control are combined, so that the complex geological adaptability is improved, and the construction efficiency and the system reliability are optimized.

The invention relates to the technical field of intelligent operation and maintenance, in particular to a bridge maintenance system based on data analysis, which comprises a multi-source data acquisition module, a fatigue degradation monitoring module, a wave velocity anomaly positioning module, a risk collaborative judgment module and a maintenance task planning module. According to the method, structural fatigue characteristics are subjected to cross validation by integrating two-dimensional data of a strain sequence and a stress wave propagation parameter, and a dynamic window range deviation degree is adopted to replace a static threshold value to establish a datum reference linked with a bridge bearing period; a same-path propagation difference value is extracted by using a high-frequency and low-frequency stress wave frequency band energy separation technology to detect continuous overrun, and a degradation trend weight and a priority list of damage space distribution are generated in combination with multi-index coexistence verification and a hierarchical sorting strategy; resource allocation is optimized by integrating a multi-level response mechanism of emergency repair coordinate positioning, directional detection and regular inspection, accurate crack positioning is achieved, the early degradation trend capturing capacity is enhanced, the misjudgment risk is reduced, and an operation and maintenance response chain is shortened.

The invention discloses a molded case circuit breaker short-circuit fault positioning method, and the method comprises the steps: obtaining the current differential response data of all branches of a molded case circuit breaker control loop when a short-circuit fault occurs based on a magnetoresistive sensor, obtaining a first data set, analyzing the first data set, and extracting the wavefront features of each branch; wavefront arrival time is obtained based on wavefront features, the first data set is input into a wave velocity calibration model to obtain frequency-dependent wave velocities of all branches, and the wavefront arrival time and the frequency-dependent wave velocities are input into a short-circuit fault positioning model to obtain space coordinates of fault points; and carrying out confidence evaluation on the fault point space coordinates to obtain an evaluation result, and judging whether to send the fault point space coordinates to a terminal user based on the evaluation result. The current differential response data is obtained based on the magnetoresistive sensor, the wavefront features are extracted, the frequency-varying wave velocity calibration and path compensation optimization model is combined, the problems of insufficient signal capture, wave velocity modeling deviation and low time difference detection precision in a traditional method are solved, and the short-circuit fault positioning method has the advantage of improving the short-circuit fault positioning precision and reliability.

The invention discloses a joint inversion method for near-well characteristics of a fracturing crack based on high-frequency tube waves and water attack, and relates to the technical field of fracturing crack inversion. The method comprises the following steps: establishing a tube wave shaft crack model; carrying out segmentation, zero padding and Fourier transform on the pre-pressing pipe wave excitation signal, then substituting the pre-pressing pipe wave excitation signal into a pipe wave shaft crack model for inversion to obtain an optimal pipe wave quality factor and an optimal pipe wave velocity, and correcting the model; the depth of a fracturing main liquid inlet point is calculated based on a pump stopping water attack curve; and performing segmentation, zero padding and Fourier transform on the pressed pipe wave excitation signal, and then substituting the pressed pipe wave excitation signal into the corrected pipe wave wellbore crack model for inversion. According to the method, the echo signal obtained through calculation is closer to the real situation, the depth of the main liquid inlet point is determined in advance, accurate and rapid inversion of the tube wave is facilitated, and meanwhile the inversion time can be greatly saved.

The invention discloses a submarine cable insulation performance online monitoring and fault positioning method, a medium and equipment. The method comprises the following steps: S1, synchronously acquiring multi-source sensing data in real time; s2, multi-modal noise cooperative suppression and feature extraction; s3, insulation state degradation evaluation based on multi-feature fusion; s4, double-end traveling wave accurate fault positioning is carried out; and S5, carrying out data visualization and alarm linkage. According to the invention, marine complex environmental noise interference can be effectively suppressed, key parameters representing the insulation state of the submarine cable are monitored in real time in a multi-dimensional manner, and early warning of insulation degradation and preliminary judgment of a fault mode are realized through an intelligent fusion evaluation model. And the improved traveling wave accurate capture and wave velocity dynamic correction technology is utilized to realize accurate positioning of a fault point, so that the accuracy and sensitivity of submarine cable state monitoring and the fault positioning precision can be remarkably improved, and powerful technical support is provided for safe and economical operation of submarine cables.

The invention relates to the technical field of medical elastography and material multi-scale mechanical measurement, in particular to an elastography method and system based on an instantaneous scattering displacement field, and the method comprises the steps: driving a passive / active method scattering displacement field excitation device through a frequency domain controllable sine wave signal, and generating a scattering displacement field on a target material, an instantaneous displacement field is obtained through high spatial resolution measurement, then sliding window local interception, two-dimensional autocorrelation calculation and nonlinear fitting based on the Rayleigh / shear wave spatial autocorrelation theory are performed on the single-frame instantaneous displacement field, shear wave velocity distribution is obtained, and then the viscoelasticity modulus of a target area is inverted to achieve comprehensive characterization of the viscoelasticity of the material. According to the scheme, the single-frame scattering displacement field is excited and collected, and the elasticity inversion is performed based on the instantaneous displacement field, so that the dependence of traditional elasticity imaging on high-frame-rate equipment is broken through, the material viscoelasticity evaluation can be efficiently completed at low cost, and the application prospect in the fields of clinical diagnosis and mechanical measurement is wide.

The invention discloses a gas permeability monitoring method and system based on carbon dioxide geological sequestration, and relates to the technical field of gas permeability monitoring, and the method comprises the following steps: obtaining geological data and a first constraint condition of a target stratum; disturbing the seismic wave frequency to generate a plurality of seismic monitoring control sets; constructing a three-dimensional geological model and a wave velocity change simulation model of the sequestration area, and performing forward simulation to obtain wave velocity change response data under different frequency combinations; wave velocity disturbance characteristic distribution caused by carbon dioxide injection under different earthquake monitoring control sets is obtained, and the set evaluation model is weighted and trained; constructing a second set according to an evaluation result of the set evaluation model and a corresponding earthquake monitoring control set; and fitting a multi-dimensional curved surface according to the second set, and screening an optimal seismic monitoring control set for seismic data acquisition and inversion, thereby solving the problem that traditional single-frequency-band inversion cannot dynamically match a stratum structure and permeability characteristics.

The invention discloses a secant pile nondestructive testing system and method based on multi-source sensing data fusion, and belongs to the technical field of civil engineering detection, the full pile long strain is axially monitored through an optical fiber, three-dimensional imaging and stress wave global scanning of a secant interface are realized through a sound wave transmitting-receiving probe pair, line-plane-body multi-level detection is formed, and the secant pile nondestructive testing system and the secant pile nondestructive testing method based on multi-source sensing data fusion are obtained. Through cooperative complementation of strain / temperature data, stress wave data and wave velocity three-mode data, defect type probabilistic recognition is achieved, the weight of each sensor is dynamically adjusted according to the real-time environment, and the defect comprehensive probability is calculated and output. And dynamic weight distribution is realized. Through multi-source sensing data fusion analysis, pile body integrity, occlusion interface compactness and temperature strain distribution characteristics can be accurately identified, and the method has the characteristics of multiple detection dimensions, high precision and strong interference resistance.

The invention discloses a mechanical arm regulation and control multi-sensor array underground structure detection system and detection method based on reinforcement learning, a vibration source module provides a sweep frequency vibration signal, a multi-sensor array collects a reflected signal, a data processing module receives and processes the reflected signal, and the data processing module receives and processes the reflected signal; the imaging module generates a three-dimensional underground structure image through a wave velocity inversion and reverse time migration imaging technology, the intelligent optimization and adaptive adjustment module adaptively adjusts vibration source signal parameters and sensor array layout through a reinforcement learning algorithm, and the display terminal displays detection data and imaging results in real time and provides parameter optimization suggestions. According to the invention, real-time and automatic adjustment of vibration source signals and sensor layout is realized through an intelligent optimization and adaptive adjustment module constructed through a reinforcement learning algorithm, and a high-resolution underground structure three-dimensional image is generated accordingly. And an efficient and accurate underground structure identification and positioning scheme can be provided.

The invention provides a seismic source positioning method and system based on three-dimensional seismic reflection data and electronic equipment, and relates to the technical field of seismic exploration, and the method comprises the steps: carrying out the initial positioning of a seismic source according to the three-dimensional geological reflection data of a target research region, and obtaining a first seismic source position; extracting a reflected wave time sequence array mapped to the detection point array from the three-dimensional geological reflection data; taking the first seismic source position as an optimization starting point, and performing correlation analysis on the three-dimensional geological reflection data and the reflected wave time sequence array to obtain seismic source space-time parameters; pre-constructing a three-dimensional seismic wave velocity model; and carrying out inversion iteration by taking the seismic source space-time parameters as initial conditions and taking the three-dimensional seismic wave velocity model as iteration constraints, and determining the position of a target seismic source. The technical problem of low positioning precision under a complex geological structure due to insufficient consideration of seismic wave propagation characteristics and reflection characteristics in the prior art is solved, and the technical effect of improving the seismic source positioning precision is achieved.

The invention discloses a transmission tower vulnerability analysis method and system based on seismic simulation, and belongs to the technical field of electric power facility disaster prevention, and the method comprises the steps: correcting bedrock seismic oscillation parameters based on equivalent shear wave velocity, and generating a high-precision earth surface PGA distribution diagram; automatically positioning a key node layer through eigenvalue decomposition, reducing the order of the three-dimensional model of the power transmission tower into a two-dimensional series multi-degree-of-freedom model, and outputting a layer mass vector, a condensation stiffness matrix and rod piece bending stiffness; performing time-history analysis by using the corrected PGA-driven reduced-order model to generate an earthquake damage probability; the multi-source remote sensing data and the PGA are fused, the landslide space probability is output through a deep learning model, and the impact strength and the landslide kinetic energy are calculated to judge the landslide damage probability; and based on the dual-threshold condition triggering probability union set, calculating a comprehensive damage probability, and generating a three-dimensional vulnerable curved surface. According to the method, the problems of high missing report rate and low calculation efficiency of single disaster assessment are solved, and minute-level accurate early warning of the composite disaster risk of the power transmission tower is realized.

The invention discloses a blasting vibration test-based rock mass wave velocity field measurement method, which is applied to a blasting operation area, is consistent with a tunnel blasting propulsion direction, does not need to independently open up a test area, and can obtain rock mass vibration data of a measurement point corresponding to a vibration measurement instrument after blasting only by arranging the vibration measurement instrument on an excavated tunnel bottom plate. According to the method, the rock mass average wave velocity can be rapidly and accurately calculated by combining the pre-measured error time of the vibration measurement instrument, the limitation of the arrangement distance of the vibration measurement instrument is broken through, the measurement range is remarkably expanded, the cost and difficulty of rock mass wave velocity measurement are effectively reduced, wave velocity measurement is completed under the condition that the original property of the rock mass is kept, and the rock mass average wave velocity is calculated. The actual rock mass condition of the blasting construction area is fed back in time, high adaptability to different rock mass properties is achieved, a scientific basis is provided for engineering design and construction, and safety and efficiency of construction are guaranteed.

The invention discloses a blade bolt state monitoring system and method based on an acoustic emission technology in the technical field of state monitoring of wind power generation equipment. The method comprises the following steps: acquiring acoustic emission signal data of a blade bolt connection area acquired by an acoustic emission sensor array; sequentially carrying out preprocessing and feature extraction processing on the basis of the acoustic emission signal data, and then calculating a wavelet packet energy entropy value; judging whether a triggering condition of multi-sensor data fusion weighting judgment is met or not based on the wavelet packet energy entropy value; when any triggering condition is met, it is judged that the state of the bolt is abnormal, and after comprehensive state recognition is conducted through multi-sensor data fusion weighted judgment and modal acoustic emission wave velocity correction positioning, early warning information including the damage type, the severity degree and position information is output; when the triggering condition is not met, it is judged that the bolt state is normal, and circulating monitoring continues. According to the invention, accurate evaluation and early warning of the blade bolt state are realized through signal acquisition, processing, analysis and early warning.

The invention relates to the technical field of power distribution network fault positioning, in particular to a power distribution network fault traveling wave positioning method and system, and the method comprises the steps: synchronously collecting a transient signal through a distributed traveling wave sensing unit, and extracting an initial traveling wave arrival time; constructing an adaptive wave velocity model based on line physical parameters to calculate an equivalent propagation velocity; dynamically generating a traveling wave propagation tree according to the real-time switch state to determine an effective monitoring path; based on the propagation path and the actual arrival time, an optimization algorithm is adopted to determine a preliminary fault point; and calculating a consistency index of the polarity of the traveling waves of the adjacent nodes, starting a multi-hypothesis tracking mechanism in a preliminary point neighborhood when the consistency index is lower than a threshold value, performing confidence coefficient weighted evaluation by combining a traveling wave attenuation model, and outputting an accurate positioning result. According to the method, through cooperation of dynamic topology mapping, adaptive wave velocity correction and multi-source closed-loop verification, the precision, reliability and adaptive capability of fault positioning in a complex power distribution network environment are remarkably improved, and the operation and maintenance requirements of rapid self-healing are met.

The invention belongs to the technical field of structural damage monitoring, and particularly relates to a structural dynamic tomography and damage monitoring method using self-excitation waves, which comprises the following steps: S1, carrying out spatial discretization processing on a monitored object, and establishing a three-dimensional discrete model; arranging a plurality of sensors on a monitoring object; recording the space coordinates of each sensor; s2, applying external excitation to a known position, and inverting an initial wave velocity field in the monitoring object; s3, extracting self-excitation waves of the monitored object received by each sensor; s4, identifying the arrival time of each self-excitation wave signal on each sensor; the space coordinates of the wave source of each excitation wave signal are calculated through inversion; s5, synchronously updating the wave velocity field based on the space coordinates of the wave sources of the respective excitation waves, and processing to obtain a damage result of the monitored object; and S6, performing corresponding processing based on a damage result. According to the method, dynamic tomography and real-time monitoring of the damage position, range and evolution process can be realized.

The invention belongs to the field of polar acoustic measurement, and relates to a method for estimating the sound velocity and thickness of an ice layer by using airwaves and ice layer bending waves, which comprises the following steps of: acquiring broadband pulse sound signals by using a sensor fixed on an ice surface; recording the distance between the detonating device and the ice surface sensor; performing time-frequency analysis on the broadband pulse signal acquired by the ice surface sensor; obtaining a time-frequency spectrum of the signal through time-frequency analysis, calculating the propagation velocity of the airwave, converting the time-frequency spectrum into a group velocity spectrum, and extracting a group velocity dispersion curve of the bending wave; initializing the longitudinal wave velocity, the transverse wave velocity, the ice layer thickness and the seawater sound velocity of the ice layer; calculating an expected group velocity curve according to the sound propagation model, and constructing a cost function; and optimizing the cost function by adopting a particle swarm algorithm, and outputting a final parameter estimation value. The method can be realized only by using a single sensor, and the synchronization of transmitting equipment and receiving equipment is not required; the sound velocity and thickness of the ice layer can be inverted by using the relationship between the group velocity and the acoustic parameters.

The invention relates to the technical field of blasting charging devices, in particular to a surface mine pre-splitting blasting parameter design method which comprises the following steps: acquiring P-wave velocity and differentially constructing a stiffness sequence, mapping a hole depth axis to identify a sudden change area, monitoring displacement and crack rate to extract triaxial deformation, identifying an unstable rock section and setting a charging section. According to the method, the P-wave speed is obtained, differential processing is carried out on the P-wave speed, the P-wave speed is converted into the rigidity gradient change rate, the rigidity gradient change rate is mapped to a hole depth axis recognition sudden change area, crack propagation and hole wall displacement are monitored, and an unstable rock stratum is positioned; and three-axis deformation is extracted to enhance prediction precision, a charging section is set, the dosage is calculated, the energy release efficiency is optimized, and blasting interference optimization is carried out by combining the time delay difference and the inter-hole included angle division distance.

The invention discloses a rock compressive strength prediction system and method based on grey correlation analysis and GWO-BILSTM, and the system is characterized in that a data collection unit is used for collecting Schmidt rebound index, Leeb hardness, Rockwell hardness, longitudinal wave velocity, density and uniaxial compressive strength measured values, and taking the above factors as original data; a gray correlation analysis module, a model optimization module and a compressive strength prediction module are arranged in the data processing unit, and the gray correlation analysis module is used for performing normalization processing on data and calculating a gray correlation degree; the model optimization module is used for optimizing the compressive strength prediction module; the compressive strength prediction module is used for predicting the compressive strength of the rock and outputting a result to the visual output module; the method comprises: collecting data; correlation degree analysis and input feature screening; establishing a rock compressive strength prediction model based on a bidirectional long-short-term memory network, and performing optimization by using a GWO algorithm; and carrying out actual prediction. The system and the method can realize efficient and accurate prediction of the compressive strength of the rock.