537results about "Seismology" patented technology

Systems and methods for monitoring and evaluating time-series real-time environment data to create a high-resolution, high-fidelity actual (e.g., nowcast) and predicted (e.g., forecast) representation of an environment of interest. In some aspects, the system comprises instructions to obtain a set of real-time environment measurements stored in a data repository corresponding to a time-series capture of environment data across an observational time period, identify one or more precursory signals within the set of real-time environment measurements, determine at least one anomalous precursory signal from the one or more precursory signals that exceeds the corresponding signal threshold, generate a time-series representation of an actual environment state across the observational time period based on the at least one anomalous precursory signal and the set of real-time environment measurements, and display, at a user interface, the generated time-series representation of the actual environment state.

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 provides a shallow-buried tunnel blasting surface vibration waveform prediction method and system, and relates to the technical field of surface vibration waveform prediction, and the method comprises the steps: collecting geological, blasting and environmental parameters of historical and current blasting, and forming a standardized parameter set through three-stage index storage, abnormal value screening and standardization processing; establishing a mapping relation between blasting parameters and a vibration waveform time domain sequence based on an LSTM neural network, and predicting a current blasting vibration waveform; fusing the geological condition influence factors, the environmental sensitivity influence factors and the predicted waveform features to generate a comprehensive safety assessment index; and according to a matching result of the index and a multi-level safety threshold value, the risk is divided into four levels of safety, low risk, medium risk and high risk, and differential management and control are executed, so that accurate prediction and dynamic regulation and control of the blasting vibration risk are realized. According to the invention, the vibration wave propagation process in the shallow tunnel blasting construction can be accurately simulated, so that the influence of blasting can be better evaluated.

The invention belongs to the technical field of mine safety and engineering earthquake monitoring, and particularly relates to a mine earthquake earth surface vibration intensity prediction method and system based on an improved sine and cosine algorithm, and the method comprises the steps: firstly constructing a mine earthquake intensity prediction model containing geometric attenuation, inelastic attenuation and an earthquake source energy item, and then constructing a target function based on measured data, and optimizing model parameters by adopting an improved sine and cosine algorithm. The algorithm improvement comprises the following steps: adaptively adjusting a search step size through a dynamic amplitude exponential decay strategy, and balancing global exploration and local development capabilities; and a periodic random restart mechanism is introduced, and the position of the individual with the worst fitness is reset to avoid premature convergence. Through the combination of the physical model and the intelligent optimization algorithm, the problems of fixed function form and low parameter optimization efficiency of the traditional empirical model are solved, and high-precision prediction of the mining induced earthquake surface vibration intensity is realized.

The invention discloses an acoustic emission signal noise reduction and feature extraction method and system suitable for a deep roadway, and relates to the technical field of safety monitoring of deep mineral resource mining, and the method comprises the specific steps: arranging an acoustic emission sensor array along the deep roadway, collecting multi-source data, converting the multi-source data into digital signals, and storing the digital signals; identifying an interference type through a wavelet packet decomposition and environment correction algorithm; self-adaptive noise reduction is carried out by using a complexity sensitive penalty algorithm; time domain and frequency domain features are extracted, coupling parameters are calculated, and time domain and frequency domain features are obtained through Hilbert-Huang transform; and finally, through principal component analysis dimensionality reduction and mutual information entropy screening, constructing a feature vector and transmitting the feature vector to a safety early warning system. According to the invention, the processing precision and reliability of the acoustic emission signal are improved through the multi-source signal acquisition module, the interference identification module and the adaptive noise reduction module; signal characteristics are comprehensively described through algorithm optimization, key characteristics are output through characteristic optimization, real-time monitoring and early warning are achieved through a dynamic damage vector algorithm, and deep roadway construction safety is guaranteed.

The invention provides a TLF-GV signal correlation earthquake magnitude prediction method and system, and a medium, belongs to the technical field of earthquake prediction, and aims at solving the problems that a traditional magnitude prediction model lacks physical constraints, TLF-GV features are not fully utilized, the interpretability is poor, and cooperation with a preorder technology is lacked. Comprising the following steps: extracting a multi-source feature vector of a TLF-GV signal containing a gravity component absolute amplitude, a vibration component relative amplitude and a signal phase; based on the G-R law, constructing the positive correlation physical characteristics log10 (GVCIpeak) and BF * Tanomal of the abnormal intensity and the magnitude of the TLF-GV signal; weighting the features according to a Bayesian factor BF value; fitting according to historical samples to obtain a physical empirical formula of positive correlation of GVCI peak logarithm and magnitude as a physical constraint, and constructing a loss function by taking the physical constraint as a regularization item and combining with a mean square error of a magnitude prediction task; and constructing an XGBoost model, and training according to the training set to obtain a prediction model for earthquake magnitude prediction. According to the method, quantitative prediction of earthquake magnitude is realized based on multi-source features of TLF-GV signals in combination with a physically constrained XGBoost regression model.

The invention relates to the technical field of intelligent operation and maintenance of a power system, in particular to an intelligent early warning method and system for preventing external damage of a power transmission line. The method comprises the following steps: acquiring acoustic data of a power transmission line through an acoustic sensor; performing voiceprint feature sparse reconstruction according to the transmission line acoustic data to obtain voiceprint feature data; performing sparse causal graph matching on the voiceprint feature data to obtain sound source behavior causal graph data; performing double-domain attention cross recognition according to the sound source behavior causal atlas data to obtain sound source separation recognition data; and performing scene map generation on the sound source separation identification data to obtain sound source scene map data. According to the invention, by constructing the nested causal chain graph and fusing the propagation weight mechanism, the development evolution and multi-stage trigger relationship of the external damage event of the power transmission line can be accurately captured. Compared with a traditional single-point detection method, the method has higher chain reasoning ability and early risk identification ability, and the response foresight and causal interpretability of an early warning system are effectively improved.

The invention discloses an earthquake forecasting and tsunami early warning method and system, and the method comprises the steps: monitoring the earth electromagnetic field data in real time, and recognizing and extracting a regional transient electromagnetic signal which accords with a preset abnormal feature as an earthquake precursor signal; taking the position of the precursor signal as a reference, and predicting the earthquake generation time, the magnitude and the potential influence area based on an earth crust stress wave propagation model; when the early warning condition is met, earthquake early warning information containing risk avoiding guidance is generated and issued, and if the prediction area relates to the coastal area and the earthquake magnitude reaches a threshold value, tsunami early warning information is synchronously generated and issued. The corresponding system comprises a geomagnetic monitoring module, a forecast analysis module and an early warning issuing module. According to the method, pre-earthquake prediction based on the physical precursor is realized, the prediction time is remarkably prolonged, the problems that earthquake and tsunami early warning information is separated and published lags are solved, and the disaster response capability is improved.

The invention provides a high-stress rock mass disturbance catastrophe real-time early warning method based on a fracture comprehensive signal, which belongs to the technical field of geotechnical engineering, and constructs a comprehensive acoustic parameter ASCP by fusing various parameters such as amplitude, dominant frequency, energy distribution, crack fractal characteristics, rock mass fracture event density and the like in an acoustic emission signal. The calculation process is combined with contribution weights of different parameters to the destruction stage, and weight values are jointly calibrated through data analysis. On the basis of a large amount of engineering field monitoring and indoor true triaxial test data, the evolution law of the ASCP in the rock mass damage process is analyzed, multiple early warning thresholds of an ASCP evolution curve starting early warning threshold and an ASCP catastrophe early warning threshold are provided, and the early warning accuracy and timeliness are improved. According to the early warning method, various parameters of sound signals are integrated, a multi-threshold early warning method is established, the contribution degrees of various main sensitive parameters of high-stress rock mass disturbance damage sound emission are integrated, and the early warning accuracy, timeliness, high efficiency and economical efficiency are improved.

The invention provides a TLF-GV signal correlation earthquake three-element joint probability prediction method and system, belongs to the technical field of earthquake prediction, and aims to solve the problems that traditional three-element prediction lacks joint fusion, evidence conflicts are difficult to process, and weights are fixed. Comprising the following steps: extracting physical features of TLF-GV signals, carrying out preorder three-element prediction results and model credibility parameters, splicing the physical features into feature vectors, inputting the feature vectors into a dynamic weight prediction model constructed by a shallow MLP, and outputting time, magnitude and position weights; dividing the three elements into 3 * 3 * 3 = 27'time-magnitude-position 'propositions, generating basic probability assignment (BPA) of each proposition based on weights, and quantifying evidence contradictions through a conflict coefficient K; and adopting a Dempster combination rule to obtain a joint BPA, calculating a mean value of a reliability function and a likelihood function of each proposition as a comprehensive probability, and extracting a maximum probability proposition as a coupling result. According to the method, the scientificity and practicability of strong earthquake short-term and temporary prediction are remarkably improved.

The invention discloses an anti-clogging rapid laying construction method for municipal drainage pipelines in a pluvial area, and relates to the technical field of municipal engineering. According to the method, through construction early-stage investigation and pretreatment, a high-pressure jet grouting pile and a steel sheet pile are combined to form a water interception curtain and vacuum well point dewatering is adopted, and a pipeline with a nanometer hydrophobic coating and a flow guide protruding edge is prefabricated; during rapid excavation, rapid hardening concrete is used for supporting, and a prefabricated module foundation with a permeable blind pipe is laid; laser positioning is adopted for hoisting, and double sealing is adopted for interfaces; graded gravel and a curing agent are used for backfilling, and ground penetrating radar is matched for detection; acceptance inspection is combined with a closed water test and an endoscope, and an intelligent monitoring device is installed to be connected into an intelligent system. The problems that construction efficiency is low and pipelines are prone to clogging in rainy areas are solved, the construction period is shortened by 30% or above, the initial clogging rate is reduced by 60%, and the method is suitable for drainage projects in areas with the annual precipitation being 800 mm or above.

The invention relates to the technical field of roadway surrounding rock stability detection, and discloses a water immersion roadway surrounding rock loosening circle detection method and system, and the method comprises the steps: drilling small-angle inclined drill holes in two sides of a roadway, and injecting pressure water to form a water immersion saturated environment; sound time data are collected through an ultrasonic probe, and a wave velocity-hole depth curve is constructed; identifying a wave velocity gradient abrupt change area based on attenuation characteristics of surrounding rock fractures to sound waves; the inner boundary and the outer boundary of the loose circle are dynamically judged through the wave velocity gradient change rate, and finally a detection report containing the loose circle range is generated. By actively simulating the water immersion coupling environment and combining gradient change rate analysis, the problem of inaccurate boundary recognition caused by water influence of a traditional acoustic wave method is solved, and the accuracy and reliability of a detection result are remarkably improved.

The constructing of a natural fracture model of a secondary reservoir in a field by using the information from a primary reservoir within a stacked 3D geological model. A fracture model may be constructed for a primary reservoir that incorporates a specific paleo-stress regime and information from a stacked 3D geological model, a deformation model, and a geomechanical model. Parameters such as a deformation model, brittleness index, and stress model may be extracted from the fracture model for a primary reservoir. A fracture model for the secondary reservoir is then constructed from the extracted parameters, and the fracture model is used to identify locations in the secondary reservoir for drilling and other operations.

The invention provides a physical information long-short-term memory network site seismic response prediction method based on kinematics derivative constraint and data folding. The method comprises the following steps: collecting and preprocessing bedrock and ground surface seismic oscillation data; displacement, speed and acceleration supervision labels are constructed through surface acceleration integration; constructing a long-short-term memory network containing a data folding and unfolding module; physical constraint loss is constructed by utilizing kinematics derivative relations between displacement and speed and between speed and acceleration, and a network is trained by combining an adaptive weight strategy; and outputting earth surface displacement, speed and acceleration time history by adopting the trained network. According to the method, under the condition that constitutive parameters of a soil layer are not explicitly given, physical consistency constraint can be applied to the field seismic response prediction process, the long-time program train training burden is reduced through sequence folding processing, and the method is suitable for field seismic response prediction.

The invention provides an eddy current detection micro-vibration signal transmission method and system based on optical fiber sensing. The method comprises the following steps: firstly, forming periodic pressure disturbance in a preset area; secondly, generating a micro-vibration signal based on periodic pressure disturbance; converting the micro-vibration signal into a backscattering light signal; phase demodulation is carried out on the backscattered light signal, and the phase variation is extracted, so that the phase variation corresponds to the dynamic change of the eddy current field; then, according to the incidence relation between the phase variation and the flight parameters of the unmanned aerial vehicle, the phase variation is coded into a digital eddy current characteristic sequence; and finally, transmitting the digital eddy current characteristic sequence to a far-end monitoring platform through an optical fiber communication link so as to complete transmission of the eddy current detection micro-vibration signal. According to the technical scheme provided by the invention, the pertinence and reliability of monitoring are improved, and high-sensitivity detection, accurate feature extraction and reliable remote transmission of micro-vibration signals of an eddy current field are also realized.

The invention belongs to the technical field of ice collapse monitoring, and particularly discloses an infrasound signal-based ice collapse monitoring and glacial lake outburst forecasting method and system, and the method comprises the steps: collecting an infrasound signal of a monitoring region; analyzing the infrasound signal, and judging whether the infrasound signal meets the following conditions: the sound pressure amplitude is greater than 0.05 Pa, the frequency is between 1.50 Hz and 10 Hz, and the duration is greater than 1 second; and if yes, judging that an ice collapse event is monitored. The ice lake outburst forecasting method comprises the following steps: when an ice collapse event is monitored, determining an elevation h3 of a position where ice collapse occurs; and based on the elevation h3 of the ice collapse position, in combination with the elevation h1 of a terminal moraine dam of the ice lake and the elevation h2 of the lake surface, calculating whether the surge generated by the ice collapse into the lake can cause the ice lake outburst, and if so, giving out an ice lake outburst early warning. According to the invention, monitoring and early warning of ice collapse and ice lake disasters can be realized.

Disclosed are systems and methods that employ elastic fiber optic, time-of-flight sensors for long distance landslide monitoring with sub-mm precision. The time-of-flight (ToF) sensor is integrated in conjunction with a single-photon avalanche diode (SPAD). By coupling both the emission source and the detector with a stretchable optical fiber, our inventive systems and methods continuously monitor the length of the stretchable optical fiber by measuring a traveling time of an optical pulse traversing the stretchable optical fiber. A significant, detectable change in the length of the stretchable optical fiber – indicative of ground movement or deformation, triggers an alarm, providing an early warning for potential landslides. As such, systems and methods according to aspects of the present disclosure provide a reliable, sensitive, precise, cost-effective, real-time solution for landslide detection and monitoring – a problem that has plagued the art.

The invention discloses an earthquake monitoring and early warning method and system based on an earthquake precursor, and relates to the technical field of earthquake forecasting, and the method comprises the steps: collecting the core data and auxiliary state data of the earthquake precursor, marking a sample label, and forming a training data set; establishing a core parameter screening model, and training the core parameter screening model by using the training data set to obtain core parameters; constructing a typical working condition library, calculating an Euclidean distance between a real-time data point and a historical working condition sample point, selecting first K neighbor points, and returning a working condition category with the highest frequency as a current operation working condition; corresponding anomaly prediction models are established according to the different operation conditions, and anomaly types under the different current operation conditions are predicted according to the anomaly prediction models; an EWI index is calculated through the core parameters, and when the EWI index is larger than an index threshold value, earthquake early warning is triggered; otherwise, continuously monitoring. According to the invention, real-time early warning of the earthquake precursor is realized under the condition that the equipment is abnormal.

The invention discloses a TLF-GV-based earthquake prediction signal anomaly detection method and system, and relates to the technical field of earthquake monitoring and prediction, and the method comprises the steps: collecting TLF-GV original time sequence signals; decomposing the TLF-GV original time sequence signal to obtain an IMF component; a gravity-related IMF component and a vibration-related IMF component of a frequency band corresponding to the TLF-GV original time sequence signal are screened out from the IMF components, and noise reduction and reconstruction are carried out respectively; performing physical enhancement processing on the reconstructed dynamic gravity signal and vibration signal; calculating a gravity-vibration contribution index GVCI and a Bayesian factor BF; effective abnormal points are screened out through three-level abnormal detection; according to the method, aliasing-free separation of dynamic gravity and vibration is realized, the signal separation precision is improved, a mode number does not need to be preset, and the method adapts to the aperiodic characteristics of TLF-GV signals.

A method including receiving a reservoir model of a target under-ground region. The method also includes extracting, from the reservoir model, a historic pressure distribution in grid cells of the target underground region. The method also includes extracting, from the reservoir model, distances. Each distance represents a distance between a grid cell and a corresponding lineament in the target underground region. The method also includes receiving historic earthquake data of past earthquakes in the target underground region. The method also includes generating a vector. The vector includes features and corresponding values for at least i) the historic pressure distribution, ii) the distances, and iii) the historic earthquake data. The method also includes training a trained machine learning algorithm by recursively executing a machine learning algorithm on the vector until convergence.

The invention relates to the technical field of ultrasound, in particular to an ultrasonic phased array sparse arraying method. Comprising the following steps: firstly, constructing a planar rectangular ultrasonic array model and determining basic parameters; setting a fitness function by taking a minimum maximum sidelobe level (MSLL) as an optimization criterion; secondly, introducing a tent chaotic mapping-good point set mixing method to obtain a classical solution population; a quantum bit coding strategy is introduced in the coding stage, individuals in the population are expressed as quantum bits, a standard NOA strategy is executed on the classical solution population to update the population, then the update quantity is synchronized to the quantum bits, and finally a new generation of classical solution population is generated through quantum rotation and collapse operation and the fitness is evaluated; integrating a covariance matrix adaptive evolution strategy (CMA-ES) in the optimization iteration process, and dynamically adjusting the shape, direction and step length of search distribution; and finally updating the global optimum. According to the method, the array element distribution of the sparse array is optimized through the multi-strategy fusion ENOA algorithm, the peak side lobe level of the array can be remarkably reduced, the anti-interference capability and precision of target detection are improved, and meanwhile, the hardware cost of the array is reduced.

The invention relates to the technical field of stratum detection and track control in front of a tunnel face of an expressway tunnel, and provides an unfavorable geological exploration method based on inclined drilling. The method aims at solving the problems that in the prior art, a static geologic model is disjointed with an actual stratum, passive response is made to stratum changes, a stratum subdivision adjustment plan is lacked, and a multi-drill-hole collaborative iteration mechanism does not exist. The method comprises the following steps: firstly, collecting multi-source geological data to construct a dynamic geological model capable of being iteratively updated, generating an initial trajectory and presetting a differentiated stratum adjustment plan; integrating sensing, execution and control components to complete calibration and simulation test; then drilling is conducted according to the initial track, and initial calibration, predictive adjustment and real-time response closed-loop control are sequentially executed; and finally, the effect is verified through imaging and rock core analysis, the model is optimized through drilling data inversion, and multi-drill-hole cooperative detection precision iteration is achieved. Stratum detection accuracy and trajectory control precision are improved, and support is provided for safe and efficient development of tunnel construction.

A method of training a machine learning model representing association between geotechnical parameters and geophysical measurement data is disclosed. The method comprises the steps of: obtaining geotechnical training data for a first area; obtaining geophysical training data for a second area, wherein the second area is larger than and surrounds the first area; assigning sample weights to a training matrix depending on distance between the geophysical and geotechnical training data such that geophysical training data further away from the geotechnical training data has smaller weight during a learning phase compared to geophysical training data closer to the geotechnical training data; and training the machine learning model using the weighted training matrix.Unlocking insights from Geo-Data, the present invention further relates to improvements in sustainability and environmental developments: together we create a safe and liveable world.

A method for building a 3D model of a reservoir includes defining a pre-sedimentation model comprising a bottom surface comprising a plurality of cells, and iterating a plurality of deposition modelling steps, including simulating deposition of a layer of sediments on the bottom surface or a previously-deposited layer of sediment, each layer corresponding to a determined period of time of sedimentation and comprising a plurality of cells, and computing petrophysical parameters associated to at least a cell of the generated layer. Simulating deposition of a layer of sediments includes introducing a plurality of particles within the model, simulating transport of the particles comprising moving a particle from one cell to another or depositing the particle, and generating a layer comprising a plurality of cells, each cell associated to a thickness of deposited particles. The petrophysical parameters are computed from mineral elements and sizes of the particles deposited in each cell.

The utility model discloses an induction device and flower basket carrying equipment. The induction device comprises a first mounting base and an inductor. The first mounting seat is provided with a first supporting part which is used for supporting a flower basket; the first mounting seat is further provided with a containing cavity, a detection hole and a wire passing hole, and the detection hole and the wire passing hole are both communicated with the containing cavity; the inductor comprises a body and a wire harness, and the wire harness is connected with the body; the body is installed on the first installation base and located in the containing cavity. The body can detect whether the first supporting part supports the flower basket or not through the detection hole; and at least one part of the wire harness is positioned in the wire passing hole. According to the induction device, the inductor can be protected more comprehensively.

A method, computer program product, and computing system are provided for defining one or more injector completions and one or more producer completions in one or more reservoir models. One or more edges between the one or more injector completions and the one or more producer completions in the one or more reservoir models may be defined. The one or more edges between the one or more injector completions and the one or more producer completions may define a graph network representative of the one or more reservoir models. The one or more reservoir models may be simulated along the one or more edges between the one or more injector completions and the one or more producer completions.

A calibration system includes a test loop placed over one or more antennas of a logging tool, an integrated calibration transceiver, wherein the integrated calibration transceiver is disposed in an electronic chassis of the logging tool, and a port disposed in the logging tool and configured to receive a connector of the test loop to connect the test loop to the integrated calibration transceiver, wherein the integrated calibration transceiver is configured to generate a test signal to drive the test loop and receive the test signal from the test loop.

This invention belongs to the field of coal mining technology, specifically relating to a water storage method in aeolian sandy aquifer mining areas. This invention innovatively utilizes directional drilling to connect aeolian sandy aquifers in open-area zones with those in non-open-area zones, improving rapid cross-regional water recharge and significantly increasing the total water storage capacity of the entire mining area. To prevent large amounts of water from being discharged through surface springs, coal pillars are used to alter the original seepage path of the aquifers. The subsidence of the coal pillar area is smaller than that of the mining area, blocking or reducing spring discharge and increasing the migration path of groundwater, thereby increasing infiltration. This invention increases the amount of water resources infiltrated from aeolian sandy ...

A synthetic rope or cable having a supportive core (1) contained within an internal cavity of a hollow braided synthetic strength member (5), the supportive core (1) shaped to adapt to the internal cavity of the hollow braided synthetic strength member (5), the supportive core (1) sheathed within a flow shield (4); the hollow braided synthetic strength member (5) formed about the combination of the supportive core and the flow shield that sheaths the core; the flow shield formed of the braid strands and being a hollow braided construction; and the hollow synthetic strength member formed of the braided braid strands, characterized in that each braid strand forming a braided flow shield is formed of at least two yarns.