668 results about "Stress wave" patented technology

The invention provides a resource dynamic monitoring and control method and system based on quota tracking. According to the pipe gallery deformation monitoring and resource optimization system based on optical fiber and sound wave sensing, underground pipe gallery structure stress field propagation data are obtained through an optical fiber sensor array, energy attenuation characteristics of stress waves at reinforcing rib intersection points are analyzed, and a dynamic mapping model of structure deformation risks and monitoring node resource requirements is established. Meanwhile, the frequency domain propagation characteristics of abnormal vibration signals are captured through acoustic sensors arranged at the expansion joints, and a resource allocation strategy matrix is formed; and constructing a quota tracking database, comparing the actual consumption rate of the frequency spectrum quota with a predicted value, generating a resource use efficiency report, and performing frequency spectrum redistribution of frequency hopping interval optimization and transmitting power adjustment on the nodes in the high stress concentration region. According to the technical scheme provided by the invention, the resource dynamic optimization of the underground pipe gallery structure is realized, and the risk early warning precision and the communication efficiency are improved.

The invention provides a forest land tree height measurement and determination method and system based on laser radar point cloud data. Stress wave signals are collected based on a trunk base acoustic emission sensor array to generate an acoustic characteristic parameter set, the digital twin model is driven to complete forest stand structure topological optimization, and a three-dimensional growth vector model reflecting the internal mechanical state of a trunk is formed. And synchronously fusing high-precision slope point cloud data returned by the unmanned aerial vehicle laser radar in real time, correcting a terrain distortion error through a dynamic splicing algorithm in combination with stress distribution characteristics, and generating a crown segmentation boundary constrained by physical characteristics. And finally outputting a tree height parameter corrected by the abrupt slope topography through model iterative optimization and space vector analysis. According to the technical scheme, synchronous sensing of the three-dimensional shape and the mechanical state of the tree in the complex terrain environment is achieved, and the tree height measurement error is reduced.

The invention discloses a bolt on-line monitoring method and system, and the method comprises the steps: generating a micro-motion feature matrix of a bolt according to a multi-dimensional vibration signal and a stress wave propagation characteristic of a bolt connection part; based on the micro-motion characteristic matrix, fusing local stress distribution data acquired by a bolt surface strain gauge, and outputting a health state quantitative index of the bolt; outputting a loosening risk level according to the health state quantitative index and historical loosening evolution data; and based on the looseness risk level and in combination with equipment operation state parameters, a self-adaptive decision tree model is adopted to dynamically adjust monitoring frequency and an alarm threshold value, a real-time monitoring strategy and a visual early warning report are generated, and a wireless transmission module is synchronously triggered to upload the real-time monitoring strategy and the visual early warning report to a cloud operation and maintenance platform. According to the embodiment of the invention, high-precision, self-adaptive and traceable bolt health state evaluation and early warning can be realized.

The invention, which relates to the industrial circuit board monitoring technology field, discloses an industrial circuit board operation abnormity monitoring system comprising a multi-sensor welding spot data acquisition module, a signal processing module, an element welding spot mechanical fatigue monitoring module, a welding spot fatigue fault grading early warning module, and an early warning and response module. Data fusion is carried out on the acoustic emission sensor, the strain gauge sensor and the ultrasonic sensor, the state of the welding spot is monitored synchronously from three dimensions of stress acoustic emission, mechanical deformation and internal defects, the strain gauge sensor captures tiny deformation around the welding spot, and the ultrasonic sensor detects internal potential defects. The acoustic emission sensor senses stress release signals, the three kinds of sensor data are subjected to deep fusion analysis through the D-S evidence theory, the problem of misjudgment caused by one-sided information is effectively avoided, stress waves during crack propagation are captured through the acoustic emission signals, and faults can be diagnosed in time in combination with deformation data of the strain gauge sensor.

The invention discloses a tunnel blasting simulation method and system for a karst area, and relates to the field of tunnel blasting simulation, and the method comprises the steps: building a three-dimensional geologic model of the karst area, and generating an initial ground stress distribution rule through numerical simulation; generating refined initial crustal stress field data; calculating stress wave intensity and time sequence data generated by explosion; acquiring stress wave propagation data; calculating the surrounding rock damage degree and the crack initial position and direction; simulating the surrounding rock crack propagation process, and calculating the penetration probability and the propagation speed of the crack near the karst cave in combination with the karst cave characteristic parameters; analyzing the surrounding rock stability and damage evolution trend of the karst cave area; and optimizing explosive source item parameters and stress wave propagation boundary conditions, and generating a karst area tunnel blasting simulation result. According to the method, the influence of the karst cave on stress wave propagation is accurately simulated, powerful support is provided for optimizing a blasting scheme and improving construction safety and efficiency, and the method has important guiding significance on tunnel engineering under complex geological conditions.

The invention discloses a system and a method for predicting the fatigue life of a flange by utilizing ultrasonic flaw detection, and belongs to the field of artificial intelligence. Comprising an aggressive frequency domain spot feature extraction module, a microdefect enhancement recognition module, an acoustic echo database training module, a damage accumulation-stress wave mapping model construction module, an active echo disturbance injection module, a fatigue life progressive prediction module, a real-time feedback closed-loop control module and a multi-scale self-checking redundancy mechanism module. Spot feature extraction and defect identification share high-frequency phase data to generate a focusing map, and registration with historical defect features is carried out in a database; the mapping model constructs a stress-damage relation according to the stress concentration coefficient and the frequency domain characteristics; the disturbance injection module applies directional excitation to potential fatigue points, and the prediction module constructs a life evolution curve based on response; the feedback control module fits and corrects the database and the disturbance strategy; the self-checking mechanism improves the prediction robustness and self-adaptability through waveform deviation and mismatch correction. The beneficial effects are that the structure safety and the service life management intelligence are improved.

The invention discloses a rock burst global monitoring and dynamic and static far and near field cooperative early warning method and system, and the early warning method comprises the steps: determining a stope space key monitoring region and a stress wave type based on a dynamic load stress wave far field generation and propagation mechanism, delineating a working face surrounding rock high-stress region, and analyzing the structural characteristics of a rock stratum. Arranging a micro-seismic sensor in a far-field key area, and obtaining parameters such as seismic source fracture size, energy and magnitude through waveform inversion; an acoustoelectric system is arranged in a near-field high-stress area, coal rock fracture characteristics are dynamically monitored, and the static load energy storage state of surrounding rock is quantitatively analyzed. And in combination with a stress wave propagation attenuation coefficient, a far and near field fusion early warning criterion under the action of dynamic and static energy superposition is established, and advanced accurate early warning of the rock burst is realized through collaborative analysis of multi-source monitoring data. The disaster-pregnant space global monitoring technology fusing earthquake, sound and electricity is provided, the chain evolution disaster-causing process of dynamic load generation, cross-space propagation and working face surrounding rock damage is considered, and the accuracy of rock burst early warning can be remarkably improved.

The invention discloses a method for grabbing an object by a robot, which comprises the following steps: acquiring surface vibration, transient deformation and three-dimensional deformation data of the object through multi-point pulse excitation, and generating stress wave characteristic mapping data; analyzing internal propagation characteristics of the object according to the stress wave characteristic mapping data, identifying a stress transmission channel, determining a material boundary position and a deformation sensitive area, and generating internal structure characteristic data; calculating a deformation risk coefficient and a stability contribution degree according to the internal structure characteristic data, selecting a grabbing position, and generating grabbing strategy data; and according to the stress wave characteristic mapping data and the grabbing strategy data, the inherent frequency and the local deformation characteristic are identified, a force loading sequence is designed, the vibration state and the deformation amount are monitored, and the force loading sequence is dynamically adjusted. According to the method, the deformation behavior of the object can be accurately predicted, the optimal grabbing strategy is determined by analyzing the internal structure characteristics of the object, dynamic force control is achieved based on frequency modulation, and the instability problem in the grabbing process of the deformed object is effectively solved.

The invention discloses a reinforced cable core wire test method and a related device, and the method comprises the steps: carrying out the matching analysis of the material structure parameters of a to-be-tested cable and the phase change characteristic parameters of a critical phase change fluid, and obtaining test parameters; controlling the critical phase change fluid to perform gas-liquid phase change near a critical point according to the test parameters, and applying a phase change stress wave and a circulating temperature load to the to-be-tested cable to obtain stress response characteristics; analyzing phase change stress wave propagation characteristics according to the stress response characteristics to obtain interface micro-motion characteristic parameters; performing quantitative analysis according to the deviation between the interface micro-motion characteristic parameters and the standard reference data to obtain a failure risk level; and determining safe use parameters according to the failure risk level. According to the method, the high sensitivity of the critical phase change fluid to tiny disturbance near the critical point is utilized, and the synergistic effect of the thermal cycle load and the phase change stress wave is combined, so that the high sensitivity detection of the internal interface micro motion of the cable is realized, and a reliable basis is provided for the performance evaluation and the service life prediction of the cable.

The invention belongs to the technical field of underground blasting, and discloses a blasting parameter screening method and system in one-time well completion blasting of a blind raise. The method comprises the steps that a slotting mode is determined, and then the slotting mode, the number of empty holes, the hole distance between the empty holes and charging holes and the filling length parameters are determined; explosive load calculation, wherein reasonable explosive loads and non-coupling coefficients of the slotting holes and the peripheral holes are determined according to numerical simulation calculation and blasting funnel test results; delay time is determined, the optimal influence time of inter-hole delay on the explosion stress wave superposition effect is calculated in a numerical simulation mode, and the damage effect of stress waves on rocks is optimal; and filling and charging are conducted, due to the fact that upward non-coupling charging is adopted, a reasonable charging mode is determined to ensure the accuracy of the charging amount and the explosive position, and reasonable filling is set to ensure that the explosive energy fully acts on the exploded rock mass. The safety of well completion operation can be greatly improved; the maximum utilization of resources is realized, and the economic benefit is improved.

The invention relates to the technical field of digital twinning, in particular to a digital twinning fused power grid fault prediction system and method, and the system comprises a state sensing module, a path deduction module, a twinning mapping module and a prediction execution module. According to the method, multi-source heterogeneous sensing data are fused, a space-time alignment algorithm is executed to construct a structural state tensor, Laplacian operation is combined with a stress wave propagation model to analyze non-rigid deformation characteristics, a load transfer path atlas is generated to reveal recessive mechanical association, Young modulus is dynamically corrected through a finite element grid to form a structural degradation coefficient matrix, and the structural degradation coefficient matrix is obtained. The time sequence difference and the long short-term memory network are combined to capture the equipment degradation trend, the Kolmogov test is used to quantify the fault space-time distribution probability, the power grid equipment jumps from single threshold early warning to multi-physics coupling prediction, the fault prediction space-time resolution and dynamic adaptability are improved, the artificial experience dependence is reduced, and the fault prediction efficiency is improved. And the robustness of the complex working condition system is enhanced.

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 provides a tunnel blasting scheme determining method and device, and relates to the technical field of tunnel engineering data processing.The method compensates stress wave attenuation caused by large-aperture blast hole air gaps through radial explosive density gradient design, so that the energy utilization rate is higher; the axial charge density is dynamically adjusted on the basis of a three-dimensional clamping coefficient, the problem that energy of a hole bottom high constraint area is insufficient is solved, the explosive density and the hole net topology are collaboratively optimized, the contour forming quality is greatly improved, back break is reduced, and therefore the cost is reduced, and the time is shortened. Due to the fact that explosive and hole net parameters are optimized, energy distribution is more reasonable, blasting disturbance is reduced, stability of surrounding rock is enhanced, safety in a hole is greatly improved, and casualties are reduced.

The invention discloses a tunnel monitoring method and system based on a vibrating wire sensor, and relates to the technical field of tunnel engineering construction safety monitoring, and the method comprises the steps: collecting the vibration frequency data and spatial position coordinates of the vibrating wire sensor in a monitoring region; the method comprises the following steps: calculating a time difference and an energy attenuation ratio between adjacent sensors by extracting spectrum energy density distribution, and constructing a stress wave propagation field; dividing grids in the propagation field to calculate node stress values, generating a stress field distribution cloud picture and extracting a stress concentration area; calculating a gravity center position coordinate change rate and a stress time sequence curve of the stress concentration area, and determining fracture extension parameters; and calculating a surrounding rock bearing capacity attenuation curve based on the parameters, and outputting an early warning signal when the slope exceeds a threshold value. According to the invention, real-time monitoring and early warning of the tunnel surrounding rock instability risk are realized.

The invention discloses an evaluation and improvement method and device for a tunnel blasting effect and a medium, and relates to the technical field of tunnel engineering.The evaluation and improvement method comprises the steps that a tunnel coupling data set is collected, space registration and three-dimensional shape reconstruction are conducted, fracture space distribution is formed, risk probability mapping is conducted on the fracture space distribution, and a fracture risk thermodynamic diagram is output; the fracture risk thermodynamic diagram and tunnel rock mass data are input into a digital twin blasting model, a load mapping layer carries out load gradient distribution, a rock mass response deduction layer carries out stress wave propagation simulation and damage accumulation quantification, an optimized blasting number instruction set is generated, and a drill jumbo is driven to execute blasting operation and vibration monitoring according to the optimized blasting instruction set. And actual blasting effect parameters are obtained. According to the method, accurate simulation of geological conditions and optimal adjustment of blasting parameters are realized through the digital twin blasting model, and meanwhile, refined and interpretable evaluation of the blasting effect is realized through vibration monitoring and error propagation modeling of the actual blasting effect.

The invention discloses a blast furnace cooling wall damage probability prediction method, which relates to the field of industrial equipment maintenance, and comprises the following steps: arranging a temperature sensor array, a vibration sensor and an acoustic emission sensor, and collecting temperature gradient data, mechanical vibration frequency and high-frequency stress wave signals in real time; calculating the slag crust thickness of the hot surface of the cooling wall based on an unsteady state heat transfer equation, introducing an in-furnace gas flow parameter correction model, and generating a dynamic slag crust thickness distribution cloud picture; establishing temperature and vibration reference threshold values under different working conditions according to historical operation data of the cooling wall, and detecting temperature over-limit accumulated duration and a vibration energy spectrum abnormal frequency band in real time; taking the temperature gradient range, the slag skin thickness variation coefficient and the vibration dominant frequency offset as input characteristics, training a multi-dimensional coupled damage probability prediction model through a random forest algorithm, and outputting a recent dynamic damage probability value of each section of cooling wall; and dividing risk grades according to the damage probability value, dynamically adjusting a threshold interval in combination with the real-time smelting strength of the blast furnace, and generating a differentiated maintenance suggestion set.

The invention relates to the technical field of vibration monitoring, in particular to a self-powered transmission line fitting aeolian vibration damage diagnosis system and method, and the system comprises a sensing collection module, a signal decoupling module, a damage identification module, a damage association module and a risk assessment module. According to the method, stress wave velocity and acceleration data are synchronously collected, time alignment is implemented, feature coupling precision is enhanced, wave crest offset and energy density are respectively extracted by using moving average filtering and wavelet transform, effective data segments are dynamically screened, and environmental noise interference is suppressed. A stress wave propagation change rate is quantified based on a path attenuation model, a continuous energy abnormal node is matched to realize damage positioning, a breeze response abnormal region is identified by combining vibration direction change and a signal envelope offset degree, multi-dimensional features are coded and subjected to risk judgment through a neural network, a damage positioning and risk assessment closed-loop framework is formed, and the risk assessment accuracy is improved. And the spatial resolution and evaluation precision of aeolian vibration damage identification under complex working conditions are significantly improved.

The invention discloses a drilling construction intelligent decision support and risk early warning method, device and equipment, and the method comprises the steps: collecting drilling sound wave response data, carrying out harmonic analysis to recognize a reservoir resonance node, and constructing a reservoir energy conduction network; a fluctuation propagation path is tracked based on an energy conduction network, and a construction risk area is identified through stress wave spectrum features; porosity and permeability data are extracted for phase difference analysis, a seepage-construction mismatch factor is generated, and a construction optimization window is actively generated; constructing a geological potential energy gradient field to determine an overflow influence range, and performing tensor coupling on multi-dimensional risk factors to generate a three-dimensional construction decision matrix; an optimal construction scheme is generated through energy minimization and risk-efficiency dynamic balance processing; construction parameter response changes are monitored in real time, abnormal parameter combination symptoms are recognized, a grading risk early warning instruction is generated, and intelligent decision support and risk early warning of drilling construction are achieved.

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 natural gas pipeline leakage detection method based on edge calculation, relates to the technical field of natural gas pipeline leakage detection, and remarkably improves the stability of edge side leakage detection through double innovations of dynamic multi-scale perception and space-time cooperative verification: a dynamic window mechanism breaks through the limitation of a fixed analysis window; through dual triggering of the energy accumulation rate and the pulse density, feature adaptability extraction of leakage events with different intensities is realized, and the missing report rate of tiny leakage is reduced; spatio-temporal fingerprint verification is combined with matching of pipeline stress wave propagation characteristics and sensor types, a physical conduction chain credibility evaluation system is constructed, and false alarm diffusion caused by regional interference is effectively inhibited; the environment entropy dynamic correction and the sensitivity strategy pool form closed-loop optimization, so that the system keeps stable detection performance under complex working conditions such as construction vibration and meteorological sudden change.

The invention provides a coal mine roof dynamic monitoring and early warning method and system based on artificial intelligence, and relates to the field of coal mine safety, and the method comprises the steps: collecting a stress waveform and a displacement waveform of a coal mine roof, extracting stress loosening characteristics, and constructing a three-dimensional stress conduction strength field; identifying a stress sudden change transition point by using a recurrent neural network to form a stress conduction chain; analyzing a regional topology migration rule and extracting a stress field instability path; matching with historical data to determine a prediction window; and continuously verifying the instability path and generating a support reinforcement scheme. The coal mine roof instability risk can be predicted in advance, and the early warning accuracy and timeliness are improved.

The invention discloses a parabola type explosion action and static action dual-energy-gathering device and a blasting method, and relates to the technical fields of directional fracture control blasting, building demolition and the like in mine and tunnel engineering. The device comprises a main body pipe which is a hollow tubular circular ring body and forms a closed channel along the annular direction; the energy-gathered jet flow groove is formed in the outer side wall of the main body pipe and distributed in the axial direction, the cross section contour of the energy-gathered jet flow groove is in a parabola shape, and the energy-gathered jet flow groove is used for guiding explosion stress waves to be intensively propagated and released in the preset direction; the energy gathering seam is formed in the bottom of the energy gathering jet flow groove and penetrates through the inner wall of the main body pipe; and the explosive loading cavity is used for fixedly placing explosives. By combining the dual energy gathering principle of explosion action and static action, energy is concentrated in the energy gathering direction in the explosion process, so that explosion energy is accurately released along a parabola-shaped track, the explosion wave focusing effect is enhanced conveniently, and invalid energy loss is reduced.

The invention relates to a wave-absorbing and vibration-reducing method for dynamic disturbance of an asymmetric high-stress tunnel, which belongs to the technical field of tunnel excavation, and specifically comprises the following steps: step 1, determining the position, range and depth of an asymmetric stress concentration area or a rockburst potential risk area behind a high-stress tunnel face, and determining the position, number and depth of grouting holes; 2, preparing and grouting a wave-absorbing material, and solidifying the wave-absorbing material, wherein the wave-absorbing material comprises the following components: cement, water, a foaming agent, polyacrylonitrile fiber and rubber powder; thirdly, monitoring holes are drilled in the middle and the two ends of the wave-absorbing grouting area, and a vibration sensor is placed in each monitoring hole; and 4, after the vibration sensor monitors that the high-energy disturbance stress wave is transmitted, obtaining an amplitude value through the waveform of the disturbance wave to obtain the main frequency of the disturbance wave. The specific position of wave-absorbing grouting is provided for a rockburst risk area, and the disturbance wave monitoring method provided by the invention can realize disturbance wave attenuation effect evaluation for various disturbance waves.

The invention provides a real-time three-dimensional city modeling and dynamic updating method and system based on deep learning. According to the method, building structure static load parameters of a target building are obtained, a micro-seismic sensor array is deployed at a node of a bearing wall and a frame beam column, and stress wave propagation path data are collected at a preset sampling frequency. And synchronously receiving electrical load data uploaded by the intelligent electric meter, and extracting a current abrupt change characteristic section in a time window corresponding to the abnormal vibration event. Building structure static load parameters, stress wave frequency domain energy distribution and the phase angle offset of the current abrupt change characteristic section are input into the deep learning model, the association rule of structural mechanical response and electrical load disturbance is coupled, and a three-dimensional model updating instruction is generated. And dynamically adjusting the grid vertex coordinates of the target building in the initial three-dimensional city model based on the instruction, and overlapping and displaying the space influence range boundary of the current abrupt change feature segment. The technical scheme provided by the invention is based on real-time three-dimensional city modeling and dynamic updating of deep learning.

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 relates to the technical field of mobile pump collaborative operation, and particularly discloses a tandem type multipurpose crawler mobile pump collaborative operation system which is characterized in that the system acquires pressure data through a pressure drop capturing module and analyzes a pressure-bearing compensation value, and whether a low-pressure trap appears or not is judged; a margin analysis module is combined with the compensation efficiency coefficient to dynamically calibrate the collaborative cavitation margin; the cavitation trend is recognized based on the cavitation proximity by means of a controllable analysis module, and when cavitation forms positive feedback, hierarchical collaborative optimization is conducted on the moving pump; and finally, a coherence model of pressure pulsation and stress waves is established based on cavitation collapse characteristics through a conduction verification module, and a low-pressure trap improvement degree model is established to evaluate the improvement degree. According to the method, the cavitation fault of the series pump set can be prevented, pressure loss under complex working conditions can be dynamically adapted, and collaborative design and operation of the series pump set are optimized.

The invention discloses a surrounding rock tunnel blasting dynamic simulation method, and belongs to the technical field of data simulation. The method comprises the following steps: acquiring three-dimensional geological data; constructing an initial mechanical parameter field of the surrounding rock based on the three-dimensional geological data; based on the initial mechanical parameter field, discretizing the surrounding rock area by adopting a finite element method, dividing grids and initializing mechanical attributes of each unit; based on the mechanical properties, blasting simulation is conducted, in the simulation process, the stress distribution state of the surrounding rock is monitored in real time, and whether the stress concentration phenomenon exists or not is judged; calculating a propagation path and an attenuation rate of a stress wave generated by explosive explosion in the surrounding rock through numerical simulation based on a judgment result; based on the propagation path and attenuation rate of the stress wave, the fracture mode and fragment distribution characteristics of the surrounding rock are analyzed; and obtaining a final blasting simulation result based on the stress distribution state, the fracture mode and the fragment distribution characteristics of the surrounding rock. The method can reflect the dynamic response of the surrounding rock and predict the blasting effect.

The invention belongs to the technical field of equipment monitoring, and discloses a stress wave sensing-based measurement method and system applied to a wind power blade. Comprising the following steps: acquiring stress wave signal data, preprocessing the stress wave signal data, and sequentially performing bipolar cooperative decomposition, error correction and environmental interference suppression on the stress wave signal data to obtain perfect stress wave signal data; performing feature extraction on the perfect stress wave signal data, generating an intermediate feature matrix, performing further feature screening on the intermediate feature matrix, and outputting stress wave signal feature data; constructing a damage assessment model based on the stress wave signal feature data, and performing damage assessment on the wind power blade by using the damage assessment model to obtain a damage assessment record; generating a three-dimensional damage map based on the damage evaluation record, and sending the three-dimensional damage map to a preset wind power equipment safety terminal; equipment monitoring on the wind power blade is realized by using the stress wave.

The invention discloses an analysis method suitable for a stress wave propagation rule in a coal rock medium, and belongs to the technical field of coal mining. The invention discloses an analysis method suitable for a stress wave propagation rule in a coal rock medium. Comprising the following steps: determining physical and mechanical properties and parameters of coal rock, establishing a stress wave propagation theoretical model containing an internal structure and stress distribution characteristics of the coal rock, solving the model by adopting a finite element method and a discrete element method, and changing model parameters based on a verification result through comparison with actual seismic data or industrial test data. The method solves the problems that an existing analysis method is often difficult to comprehensively consider the influence of a complex internal structure of coal rock and non-uniform stress distribution on wave propagation, and limitation also exists when the interference effect of multi-type stress waves and complex boundary conditions are processed. According to the method, the complicated internal structure of the coal rock and the condition of non-uniform stress distribution are comprehensively considered, so that the propagation rule of the stress waves in the coal rock is more accurately predicted.

The invention relates to the technical field of bio-fertilizer crushing, and discloses a dynamic stress regulation and control method of a crusher in a bio-fertilizer production process, which comprises the following steps: arranging a non-uniform gradient microgroove array arranged according to a Fibonacci sequence on a working surface of a cutter, filling a beta-glucan-based viscoelastic composite material in the microgrooves, the grain orientation of a tool matrix is regulated and controlled through an electromagnetic field-assisted directional solidification process, and a dynamic stress wave self-interference regulation and control system is constructed. Through the synergistic effect of geometric arrangement of the microgroove array and the nonlinear damping characteristic of the viscous-elastic material, the destructive interference effect of stress waves is spontaneously formed in the crushing process, and space equalization and peak suppression of dynamic stress of the working face of the cutter are achieved; the problems of stress concentration and tool fatigue of a traditional crusher in high-fiber and high-viscosity bio-fertilizer raw material processing are fundamentally solved, the crushing efficiency is remarkably improved, and the service life of equipment is remarkably prolonged.