938 results about "Seismology" patented technology

The invention discloses a real-time surrounding rock deformation monitoring and data acquisition method and system, which is applied to long-distance weak surrounding rock tunnel construction, and comprises the following steps: determining the dynamic change trend of underground water seepage rate and ground stress distribution gradient by adopting a time sequence analysis method; based on the trend, carrying out risk partitioning on the tunnel construction section by adopting a K-means clustering algorithm, determining a deformation sensitive area, and optimizing the spatial distribution of the monitoring points according to the deformation sensitive area; monitoring data are acquired in real time, and when the data fluctuation period exceeds a threshold value, the data acquisition frequency of the corresponding monitoring point is automatically improved; processing high-frequency acquired data by adopting a long-short-term memory network to obtain a real-time surrounding rock deformation prediction result; the prediction result and the multi-source real-time geological parameters are fused, a Bayesian updating method is adopted for processing, a quantitative surrounding rock stability evaluation result is obtained, closed-loop self-adaptive optimization of a monitoring scheme and accurate risk prediction are achieved, and the safety early warning capacity of tunnel construction and the utilization efficiency of monitoring resources are remarkably improved.

The invention discloses a geological disaster monitoring system based on multi-modal data, and relates to the technical field of geological disaster monitoring, and the system comprises a crack analysis module which carries out the time-space correlation mining of the crack propagation rate of a monitoring region, and analyzes the nonlinear evolution characteristics and spatial differentiation rules of rock mass fracture; and the critical identification module is used for performing wavelet packet energy spectrum analysis on the inclination angle change rate of the geologic body, identifying a critical turning point of rigidity attenuation of the geologic structure in combination with a preset algorithm, judging whether the overall stability enters an instability acceleration stage or not, and performing multi-parameter collaborative detection, crack evolution cross validation and dynamic trend stability verification to obtain the stability of the geologic structure. The accuracy and reliability of geological structure rigidity attenuation critical turning point recognition are remarkably improved, a more accurate rigidity attenuation stage judgment basis is provided for an early warning module, and the capturing capacity of a multi-modal data geological disaster monitoring system for structure instability precursor is enhanced.

The invention relates to a coal mining subsidence area plant foundation monitoring method and system based on multi-source data fusion, and the method comprises the steps: obtaining multi-source monitoring data of a target coal mining subsidence area plant area, the multi-source monitoring data comprising satellite remote sensing data, ground measurement data and interference radar data; performing time synchronization and space unification on the multi-source monitoring data to obtain monitoring data with unified space; performing fusion processing on the monitoring data with uniform space to obtain comprehensive deformation data; constructing a three-dimensional settlement deformation field according to the comprehensive deformation data, and extracting deformation rate and acceleration information of each monitoring point through a gradient calculation method; and according to the deformation rate and the acceleration information, obtaining risk assessment of the plant foundation in the target coal mining subsidence area. The technical problems of multi-source heterogeneous data fusion and real-time settlement monitoring and early warning are effectively solved, and the precision and timeliness of foundation settlement monitoring are improved.

The invention provides a deep-buried tunnel TBM vibration and excavation unloading fracture micro-seismic discrimination method and system, and relates to the technical field of tunnel construction, and the method comprises the steps: obtaining micro-seismic event data in a target area; spatial classification is carried out according to the micro-seismic event data, and the influence range of the excavation unloading effect is obtained; performing region division according to the influence range to obtain a rock fracture signal after noise reduction; performing multi-layer decomposition on the rock fracture signal by using wavelet transform to obtain a characteristic parameter set; performing energy grading according to the characteristic parameter set to obtain a grading result; constructing a discrimination standard according to the grading result to obtain the discrimination standard; and performing discrimination based on the discrimination standard to obtain a discrimination result. According to the method, the dynamic model is constructed based on the multi-energy-level discrimination standard, main control factor classification is performed on the real-time micro-seismic event, real-time dynamic discrimination of TBM vibration and excavation unloading fracture in the construction process is achieved, and the early warning timeliness of time-delay rock burst is remarkably improved.

The invention relates to the technical field of mine safety monitoring and geophysical exploration, in particular to a mine water disaster intelligent alarm system responding to multi-dimensional physical field parameter abnormity, which comprises a full-space data acquisition module for acquiring monitoring area observation data and calling a background geological physical model; the ideal reference reconstruction module is used for constructing an ideal physical field reference in a non-abnormal state; the double difference extraction module is used for calculating an observation residual error of observation data relative to a reference and a theoretical residual error of simulation response relative to the reference; the inversion coupling verification module is used for driving the theoretical residual error to approach to the observation residual error and extracting parameter sensitivity characteristics; the intelligent alarm judgment module is used for analyzing sensitivity characteristics and convergence states; generating an alarm instruction if the feature is determined to be the entity fluid abnormal feature; if it is determined that the target abnormal interference feature is not the target abnormal interference feature, signal suppression processing is executed; according to the invention, the false alarm rate of mine water disaster detection is greatly reduced.

The invention discloses a deep well rock mass instability failure time accurate forecasting and early warning system, and relates to the technical field of deep well rock mass failure early warning, and the deep well rock mass instability failure time accurate forecasting and early warning system comprises the following steps: collecting a plurality of deep well rock samples to carry out a uniaxial compression experiment, and collecting acoustic emission signals in real time based on an acoustic emission sensor to obtain original acoustic emission signal data; carrying out self-adaptive preprocessing, and carrying out data classification and integration to obtain rock sample acoustic emission parameter data; constructing an original damage forecasting model, and performing model training and verification optimization based on the rock sample acoustic emission parameter data to obtain a rock damage forecasting model; collecting an acoustic emission signal of the deep well rock mass, and predicting the instability failure time of the deep well rock mass in real time based on the rock failure forecasting model; the method is used for solving the problems that when an existing deep well rock mass damage early warning technology carries out early warning on rock mass instability damage through acoustic emission monitoring, single or few characteristic parameters are manually processed and analyzed, and the early warning reliability and timeliness are not high.

The invention discloses an open-pit mine slope risk prediction method and system based on multi-source data, and relates to the technical field of intelligent geological engineering, and the method comprises the steps: collecting geological data, displacement monitoring data and environmental activity data of an open-pit mine slope, carrying out the preprocessing, and constructing a three-dimensional digital twinborn body; carrying out fusion calculation on the preprocessed displacement monitoring data and environmental activity data through a physical information neural network, predicting a displacement value and a stress value of the strip mine slope, and obtaining full-field physical quantity prediction data; according to the strip mine slope slip crack surface damage evolution path, the stability risk levels of the whole strip mine slope and different areas in the strip mine slope are judged, high-risk areas are positioned, and a strip mine slope risk prediction report is generated. According to the method, the damage evolution path of the slip crack surface of the strip mine slope is dynamically deduced, so that space-time continuous modeling of the damage evolution process, early recognition of the slope instability precursor and accurate insight of the risk evolution trend are realized.

The invention relates to the technical field of electric digital data processing, in particular to a dangerous rock instability monitoring and early warning method. The method comprises the following steps: collecting multi-modal original data related to the dangerous rock in real time, and preprocessing the multi-modal original data to obtain multi-dimensional core parameters; lithologic partitioning is carried out on the monitoring area based on the borehole acoustic logging data, and a lithologic partitioning result is obtained; carrying out data association and fusion by adopting a D-S evidence theory based on the lithologic partitioning result and the multi-dimensional core parameters, and generating a comprehensive support degree of each catastrophe state; multi-modal characteristic spectrum mathematical characterization is carried out based on the multi-dimensional core parameters, a precursor mode corresponding to the multi-modal characteristic spectrum subjected to mathematical characterization is identified, and space-time correlation verification is carried out on an identification result; and according to the comprehensive support degree, the identification result and the time-space correlation verification result, outputting a graded early warning instruction of dangerous rock instability. According to the invention, the problems of one-sided consideration, low precision and poor real-time performance of dangerous rock instability early warning in the prior art can be solved.

The invention discloses a mine roadway deformation data real-time analysis system based on edge calculation, which relates to the technical field of intelligent sensing and data analysis fusion, and comprises a data acquisition module for acquiring roadway deformation initial data through a sensor, simulating a deformation field evolution process by adopting a finite element analysis method, and analyzing the deformation field evolution process; the feature extraction module is used for extracting key stress distribution parameters from the non-uniform field distribution features, if the parameters exceed a preset threshold value, the key stress distribution parameters are marked as a risk concentration area, a monitoring position candidate set is determined, and the signal quality evaluation module is used for evaluating the monitoring position candidate set according to the monitoring position candidate set. Acquiring a signal-to-noise ratio and an integrity data quality index of a sensor signal, and performing priority grouping on the monitoring points through a clustering algorithm to obtain a dynamic priority evaluation result; according to the mine roadway deformation data real-time analysis system based on edge calculation, intelligence, real-time performance and high reliability of mine roadway deformation monitoring are achieved.

The invention relates to the technical field of track bridge engineering, in particular to a high-speed railway track-bridge system earthquake-caused residual irregularity prediction method, which comprises the following steps of: determining a target object, and constructing an earthquake-caused irregularity database based on historical earthquake oscillation data of the target object; based on the earthquake-induced irregularity damage database, constructing an earthquake-induced peak irregularity deep learning prediction model fused with the vibration mode superposition method, and performing prediction by adopting the earthquake-induced peak irregularity deep learning prediction model to obtain an earthquake-induced peak irregularity prediction value; calculating an earthquake-caused residual irregularity equivalent coefficient based on earthquake-caused peak irregularity and earthquake-caused residual irregularity in the earthquake-caused irregularity damage database; and earthquake-caused residual irregularity is predicted based on the predicted earthquake-caused peak irregularity predicted value and the earthquake-caused residual irregularity equivalent coefficient. According to the method, the engineering safety and reliability of the result are ensured based on the mapping relation of the probability assurance rate, and the method has high efficiency and safety and is suitable for practical engineering application.

The invention relates to a geological forecasting technology, discloses a tunnel advanced geological forecasting method based on multi-geophysical prospecting joint inversion and multi-source data fusion, and solves the problems of poor efficiency and reliability caused by lack of effective constraints of an initial inversion model during joint detection of existing multiple geophysical prospecting methods. And the judgment accuracy is influenced by the failure of deep fusion of multi-source geological data. The method comprises the following steps of: detecting geological conditions in front of a tunnel face by adopting advanced horizontal drilling and advanced geophysical prospecting to obtain an advanced horizontal drilling detection result and original data of each geophysical prospecting method; the method comprises the following steps of: establishing an initial model by taking a prior mean constraint and a structure constraint as means and utilizing an advanced horizontal drilling detection result, and carrying out echelon joint inversion of a multi-geophysical prospecting method by taking high-precision information as a prior condition of low-precision information and taking structural plane information as a prior condition of resistivity information inversion; carrying out dimension reduction fusion and cross correction on the inversion result of each parameter; and finally, identifying geological information in front of the tunnel face by explaining the meaning of the parameter data and imaging.

The invention provides a mine slope risk assessment method and system based on multi-source data space-time fusion, and relates to the technical field of mine monitoring, and the method comprises the steps: obtaining geological and engineering data, and constructing a basic model representing a slope three-dimensional space structure; collecting multi-source heterogeneous monitoring data on a mine slope field, and aligning and fusing the multi-source heterogeneous monitoring data with the basic model in a space-time dimension to generate a continuous dynamic parameter field; and setting a data fusion model, and taking the basic model and the dynamic parameter field as input to obtain a four-dimensional space-time fusion risk field. According to the method, the basic model representing the three-dimensional space structure of the slope is constructed, and a unified space-time bearing base is provided for all heterogeneous monitoring data, so that originally isolated data such as GNSS displacement, deep displacement, blasting vibration and underground water level can be fused in a unified coordinate system; the problem of data splitting in the prior art is fundamentally solved, and integral and integrated expression of slope engineering and geological conditions is formed.

The invention discloses an intelligent geophysical exploration geological exploration analysis system, and relates to the field of geological exploration, and the system comprises a collection and preprocessing module which is used for carrying out the adaptive collection of multiple types of geophysical field signals of a target exploration region, and synchronously carrying out the preliminary noise reduction and quality optimization of original signals through signal purification processing; the fusion module is used for receiving the preprocessed multi-type geophysical field signals and carrying out normalization and feature depth correlation fusion on coordinates of data of different dimensions through spatial-temporal feature correlation processing; the method can dynamically adapt to environmental noise optimization signal acquisition, extracts stratum recessive characteristics through multi-dimensional data fusion and intelligent mining, constructs an accurate three-dimensional geologic model, positions stratum attribute deviation and grades through multi-scale analysis, presents exploration results in combination with three-dimensional visualization, and generates target region optimization suggestions.

The invention discloses a multi-source information real-time identification and positioning method for a coal mine rock burst risk area. The method comprises the following steps: integrating a micro-seismic system, a rock noise system, a stress system and a geological system to construct an acquisition network; extracting multi-source characteristic indexes and carrying out space-time unification; establishing a dynamic weighted risk fusion model to calculate a comprehensive risk index RI of a three-dimensional grid unit, wherein the weight of the comprehensive risk index RI is dynamically and adaptively adjusted along with mining; based on the RI value, a high-risk area is identified and positioned through three-dimensional visualization, and graded early warning information is generated; according to the invention, a time-space synchronous multi-source information acquisition network is constructed, and uniform preprocessing and feature extraction are carried out on four types of data of microseism, rock noise, stress and geologic structure, so that deep fusion and collaborative analysis of multi-source information are realized, and an information island phenomenon existing in traditional monitoring is overcome; and the judgment on the rock burst risk is more comprehensive.

The invention discloses a geological disaster monitoring and early warning system based on a rock-soil body micro-seismic sensing network, particularly relates to the technical field of geological disaster early warning, and is used for solving the problems of insufficient positioning precision and poor early warning reliability caused by neglecting rock stratum heterogeneity in an existing seismic source positioning method. The method comprises the following steps: constructing a three-dimensional heterogeneous rock stratum model containing fractures and faults by acquiring geological exploration data of a monitored area, simulating a distortion propagation path of micro-seismic waves in an anisotropic medium, and generating a waveform feature library; extracting time-frequency domain energy distribution of an actual signal, matching the time-frequency domain energy distribution with the feature library, and dynamically correcting equivalent wave velocity field parameters; calculating a propagation time difference matrix in combination with sensor coordinates and a corrected wave velocity field, and constructing a nonlinear equation set taking wave velocity deviation as a constraint to solve seismic source space coordinates; and finally, generating a dynamic early warning signal based on the distribution relationship between the seismic source and the rock stratum model. And the seismic source positioning precision and the early warning accuracy in a complex rock mass environment are remarkably improved.

The invention belongs to the technical field of geophysical exploration, and particularly discloses a differential transient electromagnetic method device and an unexploded ordnance detection method thereof.The differential transient electromagnetic method device is characterized in that a transmitter injects emission current into an emission loop, and the emission loop generates a primary field excitation signal; the underground anomalous body target generates a secondary field excitation signal under the action of the primary field excitation signal; the receiving coil assembly is based on the structure of a differential coil, synchronously counteracts a primary field excitation signal and a uniform background signal in an induced voltage, and expands a local asymmetric differential signal generated by an underground anomalous body target; and the receiver carries out time sequence analysis on the local asymmetric differential signals and extracts differential signal features so as to realize positioning and identification of an underground anomalous body target. The device is suitable for detection of shallow-buried small bodies such as UXO, the overall arrangement range of the device is small, and rapid arrangement and mobile observation in the field are facilitated.

The invention relates to the technical field of coal mine safety monitoring, and discloses a coal mine tunnel laser radar three-dimensional dynamic monitoring method. Aiming at the problems that in the prior art, data of a laser radar is easy to interrupt or unreliable under a severe working condition, and monitoring continuity is poor due to insufficient multi-source data fusion, the method is characterized in that laser radar surface data and optical strain gauge point data are synchronously acquired; constructing a roadway digital twinborn model; carrying out fusion and assimilation on the multi-source data by utilizing a Transform mechanism to obtain initial roadway deformation data; judging the credibility of the laser radar data based on Bayesian estimation; when the data are missing or uncredible, deducing full-field deformation by utilizing a gating mechanism in combination with optical strain gauge point data and a digital twin model; and finally, generating and outputting a three-dimensional dynamic deformation field. The system is mainly used for real-time, continuous and high-reliability deformation monitoring and safety early warning of the coal mine tunnel.

The invention belongs to the technical field of data processing, and particularly relates to a ground pressure monitoring and early warning method and system based on multi-source data fusion, and the method comprises the steps: constructing a space-time distance improvement DBSCAN algorithm of micro-seismic events, carrying out the clustering of the micro-seismic events through the improved DBSCAN algorithm, and calculating the risk source index of each micro-seismic event cluster; in the three-dimensional grid space, acquiring risk potential energy of each grid unit according to the risk source index, the distance between the micro-seismic event cluster and the grid unit and the stress state of the grid unit; calculating a ground pressure risk index by combining the current value of the risk potential energy and the time change of the risk potential energy; and performing multi-level early warning according to the ground pressure risk index. Ground pressure early warning is carried out by fusing the microseismic space-time aggregation characteristics, the stress field state and the risk dynamic evolution trend, and the accuracy and timeliness of ground pressure disaster early warning are improved.

The invention relates to a method and system for determining a rock burst risk based on a micro-seismic source parameter, and the method comprises the steps: determining a to-be-predicted region and a micro-seismic source parameter threshold value corresponding to the to-be-predicted region, obtaining a first micro-seismic source parameter of the to-be-predicted region in a future time period, and determining a rock burst risk based on the first micro-seismic source parameter and the micro-seismic source parameter threshold value. Obtaining a first result of the rock burst risk of the to-be-predicted area in the future time period, obtaining a current second micro-seismic source parameter of the to-be-predicted area, obtaining a second result of the current rock burst risk of the to-be-predicted area based on the second micro-seismic source parameter and a micro-seismic source parameter threshold value, and summarizing the first result and the second result to obtain a prediction result of the rock burst risk of the to-be-predicted area. According to the method and the device, the accuracy and the efficiency of rock burst risk assessment are improved, a potential rock burst risk area can be found in advance based on the target result of the rock burst risk, and safe production of a coal mine is guaranteed.

The invention relates to the field of geological exploration, in particular to an intelligent analysis method and system for geological exploration data of a coal mining subsidence area. The invention discloses an intelligent analysis system for geological exploration data of a coal mining subsidence area. The intelligent analysis system comprises a data acquisition module, an underground three-dimensional model construction module, a foundation stability evaluation module, a residual deformation prediction module and a suitability judgment module. According to the method, multi-source data such as drilling data, geophysical prospecting data, remote sensing topographic data, monitoring actual measurement data and geotechnical test data are comprehensively analyzed, a unified underground three-dimensional model is constructed, and the limitation of data isolation of a traditional exploration method is broken through; according to the method, through drilling and geophysical prospecting bidirectional complementary correction and combination of a settlement monitoring sequence and static attributes, a more accurate and comprehensive geological exploration result is provided for a coal mining subsidence area, and the accuracy of foundation stability evaluation and deformation prediction is remarkably improved.

The invention discloses a rock mass fracture early warning method for a hydraulic tunnel, belongs to the technical field of tunnel safety monitoring, and can solve the problem that an existing method cannot specifically recognize isolated impact noise and rock mass real fracture signals in the construction period of the hydraulic tunnel under the background of strong noise. The method comprises the following steps: S1, acquiring an original micro-seismic signal synchronously acquired by a sensor array in a hydraulic tunnel; s2, detecting a micro-seismic event from the original micro-seismic signal to obtain an event signal set, and determining a reference channel signal according to the event signal set; s3, extracting cross correlation coefficient peak values of event signals of each channel in the event signal set and reference channel signals, and counting the number of channels of which the cross correlation coefficient peak values exceed a cross correlation coefficient threshold value as the number of coherent channels; and S4, calculating a frequency band energy ratio of the reference channel signal, and generating a rock mass fracture early warning signal when the number of coherent channels and the frequency band energy ratio meet preset conditions. The method is used for rock mass fracture early warning of the hydraulic tunnel.

A mine earthquake dangerous area prediction method fusing a deformation localization theory and transfer learning belongs to the field of mine dynamic disaster prevention and control, and comprises the following steps: 1) aiming at the problem of uneven distribution of micro-earthquake events, adopting a multi-scale adaptive kernel density estimation method to construct a cloud picture depicting micro-earthquake characterization deformation localization spatial evolution; the method comprises the following steps of (1) taking a DIC deformation field cloud picture of a laboratory rock uniaxial compression experiment as a source domain data set, and taking a cloud picture generated by processing field micro-seismic data as a target domain data set, and (3) constructing an SRES-DA-BiLSTM transfer learning model.According to the method, the spatio-temporal evolution law of mine seismic activities is effectively captured, and high-precision recognition of dangerous areas is achieved.

The invention discloses a geophysical three-dimensional visualization and geologic model construction system, which belongs to the technical field of geophysical data processing and three-dimensional geologic modeling and comprises a multi-source data acquisition module, a volume rendering module, an interactive segmentation module, an uncertainty expression module, a multi-scale fusion module, an attribute interpolation module and a model construction module. Multi-source geophysical data are converted into a visual three-dimensional visual model through a volume rendering technology, an interactive segmentation algorithm is adopted to accurately extract a geologic body boundary, an uncertainty expression mechanism is innovatively introduced to quantify the reliability of the model, and a multi-scale fusion technology is integrated to realize seamless connection from a regional structure to an ore deposit fine structure. The Kriging interpolation functional product physical property parameter three-dimensional distribution field is provided, the spatial cognitive ability and the decision-making efficiency under the complex geological condition are remarkably improved, and a powerful visual analysis platform is provided for geological exploration and resource evaluation.

The invention discloses an end slope mining side slope real-time stability testing system and method, and relates to the technical field of open pit coal mine end slope mining safety monitoring and early warning, and the method comprises the steps that a distributed optical fiber sensing network arranged on a side slope surface and a mining chamber top plate collects acoustic emission and strain time sequences; a solid-state laser radar array arranged on the stope platform collects slope surface point cloud data of the stope platform; during data acquisition, the solid-state laser radar array and the distributed optical fiber sensing network are in time alignment; carrying out slope displacement increment extraction on the slope point cloud data of the monitored area by the edge GPU node; the data analysis cloud platform is used for performing microfracture identification according to the acoustic emission and strain time sequence; and inputting the slope displacement increment, the micro-fracture event count and the strain time sequence into the trained stability evaluation model to obtain a stability evaluation result, and capturing the internal micro-fracture, surface micro-displacement and shear-expansion coupling characteristics in real time, and providing high-reliability instability prediction.

The invention belongs to the technical field of geological analysis, and discloses a ground subsidence analysis method and device, and the method comprises the steps: matching a sensor layout strategy corresponding to a foundation subsidence risk and meteorological data of a monitoring region; acquiring land subsidence data of the monitoring area according to a sensor; performing time-frequency analysis on the land subsidence data to obtain a geoacoustic spectrogram corresponding to the land subsidence data; inputting the geoacoustic spectrogram into a preset neural network, and outputting a settlement semantic vector corresponding to the geoacoustic spectrogram; acquiring and analyzing historical land subsidence data, and constructing a subsidence rule corresponding to the historical land subsidence data; and inputting the settlement semantic vector and the settlement rule into a preset space-time analysis model, and predicting to obtain a future settlement trend of the monitored area. By using the method disclosed by the invention, the problem that all risks in a certain area cannot be checked when geological data is monitored based on local monitoring points can be solved, and the problem that the geological risk analysis efficiency is relatively low can be solved.

The invention belongs to the technical field of induced polarization advanced detection. According to the TBM excavation-following induced polarization real-time advanced detection method and system, a TBM cutterhead and a TBM shield serve as power supply electrodes, and the detection efficiency and the TBM excavation efficiency are improved; acquiring first detection data when the TBM cutterhead clings to the tunnel face and the TBM cutterhead and the TBM shield supply power at the same time and second detection data when the TBM cutterhead leaves the tunnel face after retreating, the TBM cutterhead is not in contact with the surrounding rock and the TBM shield supply power independently, and taking a difference value between the first detection data and the second detection data as final detection data of the current detection round, and performing three-dimensional imaging processing on the final detection data of the plurality of detection rounds in any imaging period to obtain a continuous three-dimensional detection result in the imaging period. According to the TBM tunnel detection method, the difference of the detection data is made for denoising processing after tunneling of each round, real-time imaging is achieved in the imaging process, and the TBM tunnel detection effect is improved.

The invention relates to the technical field of strip mine side slope slippage trend early warning, and particularly discloses a strip mine side slope slippage trend early warning system based on active micro-vibration excitation, which comprises the following components: an excitation unit which is composed of a frequency-adjustable micro-vibration exciter which periodically applies low-amplitude controllable mechanical disturbance signals to a side slope rock mass, the rock-soil medium structure response is excited, and the early warning sensitivity is improved; the sensing unit comprises a three-axis acceleration sensor, a displacement meter, a GNSS (Global Navigation Satellite System) sensor and a ground acoustic wave sensor, and is used for recording response change in a vibration disturbance signal propagation process and obtaining data; the analysis unit comprises an edge intelligent terminal, a slippage trend identification model built in the edge intelligent terminal and a lightweight neural network, and the slippage trend identification model performs sensing processing on the data and outputs a slippage trend label; and the communication control unit is used for ensuring that the data streams of the units are stable and cooperatively run with the modules.

The invention relates to the technical field of coal mine slope monitoring, and discloses a coal mine slope deformation monitoring system and method based on multi-source data fusion. The system comprises a data acquisition module, a mode matching module, an action point positioning module, a matching degree analysis module and a weight calculation module. The data acquisition module acquires a slope displacement sequential sequence, a stress change gradient and micro-seismic energy distribution in real time; a mode matching module screens a deformation mode section matched with the current deformation strength feature from a historical database; the action point positioning module analyzes the displacement data, determines a displacement acceleration action point and calculates the time delay amount; the matching degree analysis module compares the stress before and after the acceleration action point with the displacement data sequence trend to determine the deformation matching degree; and the weight calculation module determines the deformation weight of the mode section in combination with the time delay amount, the deformation matching degree and the deformation strength difference. According to the system, slope deformation monitoring and trend judgment are optimized through multi-source data fusion and historical mode association.

The invention belongs to the technical field of dike breach emergency rescue, and discloses a dike breach breach potential intelligent deduction and submerging probability visualization system and method and a medium. The engineering intervention deduction engine is constructed on the basis of a physically guided neural operator, takes a two-dimensional multi-physical reconstruction field containing pile body positions, material distribution, a flow velocity field and terrains as input, and directly outputs a water flow velocity-water depth physical field time history in a future time period; the online self-evolution engine is used for triggering fine adjustment of the model by comparing a deduction result with the deviation of real-time monitoring data; and the uncertainty quantification visual interface is used for dynamically displaying the deduction result in the form of a probabilistic submerging thermodynamic diagram. According to the method, a deduction framework integrating physical constraints and neural operators is created for the first time, the technical problems that traditional numerical simulation calculation is low in efficiency and pure data driving methods are physically inconsistent are solved, the unification of minute-level deduction speed and physical rule following is achieved, and real-time and reliable scientific decision support is provided for dike breach emergency rescue.