22 results about "Inversion analysis" patented technology

The invention relates to the technical field of slope engineering parameter inversion, in particular to a rock-soil mass parameter probability inversion analysis method based on constrained Bayesian updating, which comprises the following steps: determining prior distribution of slope rock-soil mass parameters, and constructing a slope monitoring data likelihood function; constructing a target constraint likelihood function according to the target constraint condition; combining prior distribution, a slope monitoring data likelihood function and a target constraint likelihood function by using a Bayesian theory to determine posterior distribution of rock-soil body parameters, thereby determining equivalent samples of the rock-soil body parameters by using a target sampling algorithm, and updating reliable indexes of a target slope by using the equivalent samples, thereby improving the reliability of the target slope. And obtaining the updated slope reliability index. Therefore, the problems that the traditional Bayesian inference in the related technology is mainly used for inverting the geotechnical material parameters by fusing the monitoring data, and when the types and the number of the monitoring data are limited, the traditional Bayesian inference is often uncertain, the inversion stability is poor, and the uncertainty of the geotechnical material parameters cannot be effectively reduced are solved.

The invention relates to the technical field of geological modeling, in particular to a geological modeling construction optimization method suitable for surface mine geological disaster exploration. The method comprises the following steps: fully collecting and integrating geological data and geophysical data, determining a reasonable drilling position by using a scientific geological inversion analysis method, constructing an ore body model by combining drilling sampling data, and constructing a geological profile map by using a GIS (Geographic Information System) to obtain accurate contour parameters so as to construct an original geological three-dimensional model. Meanwhile, a Bayesian method is introduced to calculate probability distribution of the stratum surface, and an original model is labeled and compiled to obtain a final high-precision three-dimensional geological model, so that the defects of a traditional method can be effectively overcome, and the accuracy, reliability and scientificity of geological modeling are improved; and more accurate and comprehensive geological information support is provided for prediction, evaluation and prevention of geological disasters of the surface mine.

The invention discloses a tunnel safety construction advanced detection method combining forward modeling and inversion analysis. The method comprises the following steps: S1, collecting data of a tunnel construction area, performing electromagnetic wave forward modeling by using GPRMax, establishing a geologic structure model, and obtaining electromagnetic characteristic data; s2, according to geological radar actual measurement data, in combination with a GPRMax simulation result, a geological abnormal area is identified, and potential risk points are marked; s3, performing three-dimensional numerical simulation of the tunnel construction process by utilizing FLAC3D according to the geologic structure model and the potential risk point data; s4, according to a simulation result, evaluating stress distribution and a displacement field in the tunnel construction process, and optimizing a tunnel construction scheme; and S5, in the construction process, in combination with real-time monitoring data, performing comparative analysis with a simulation result, and dynamically adjusting and optimizing structural model parameters. According to the advanced detection method for tunnel safety construction, the safety risk in the tunnel construction process can be accurately predicted, and the construction safety is improved.

The present invention relates to the technical field of inversion analysis of layered surrounding rocks, and discloses a three-dimensional geostress field inversion intelligent analysis system and method for layered surrounding rocks. The system includes a three-dimensional geological numerical module, an intelligent inversion analysis module, and an inversion result verification module. The method includes collecting geological data in the target layered surrounding rocks; normalizing the geological data and performing sensitivity analysis; constructing a three-dimensional geological model and performing numerical simulation; intelligently generating a geostress field inversion intelligent analysis model based on the three-dimensional geological model; training the geostress field inversion intelligent analysis model using training samples; inputting real-time geological data into the geostress field inversion intelligent analysis model to obtain geostress inversion analysis results; visually outputting the geostress analysis results; and adjusting the geostress field inversion intelligent analysis model according to measured data. The present invention can provide a scientific geostress field analysis basis for complex projects such as tunnel projects, underground projects, and hydropower stations.

The invention discloses an electric spark source multidirectional detection system and method based on a polarization effect, the system comprises a source drill rod, a capacitance drill rod, a conductive drill rod and a console, discharge electrodes respectively correspond to excitation ports in different orientations, and three space orthogonal excitation ports are formed in this way for time-sharing excitation. Three pure transverse wave sources with known polarization directions are manufactured, so that the detection precision is improved for subsequent inversion analysis; obtaining a three-component seismic trace record data set corresponding to the three seismic sources; processing the data set to obtain three groups of azimuth data; thirdly, defining a model parameter vector and determining a full-waveform inversion function; according to the method, an adjoint state method is adopted to obtain a gradient direction enabling an objective function to descend, an L-BFGS algorithm is utilized to iteratively update model parameters, and finally, an optimal solution is utilized to be combined with three groups of azimuth data to carry out full-waveform inversion, so that azimuth anisotropy information of a detection area is obtained. And the accurate identification of the disaster geologic body in the detection target area is realized by fusing the multidirectional detection data.

The invention discloses a flying gangue dynamic damage characteristic inversion method based on dynamic-static behavior calibration, and relates to the technical field of coal mining. Comprising the following steps: acquiring experimental design parameters and test results of dynamic-static rock mechanical behavior tests, and then constructing a corresponding stope model for a simulation experiment to obtain simulation results; based on the test result and the simulation result, micromechanical parameters of a digital core in the stope model are determined through numerical simulation inversion analysis, and an initial stope model is obtained; based on flying gangue test data, carrying out calibration design on the flying gangue motion effect in the initial stope model, then carrying out a flying gangue motion simulation experiment, and optimizing global control parameters of the stope model according to actual measurement characteristics; and finally, carrying out a simulation experiment on the spatio-temporal evolution process of the flying waste rock movement to determine the flying waste rock dynamic damage characteristics. According to the method, the problem that the intrinsic law of the flying waste rock spatio-temporal evolution process is difficult to actually measure at present is solved, and a reliable way is provided for revealing the intrinsic law of the flying waste rock spatio-temporal evolution.

The invention relates to the technical field of material micro-area mechanical property testing, and discloses a material mechanical constitutive inversion analysis method and device and electronic device.The method comprises the steps that a nanoindentation test is conducted on a to-be-tested material, and an average load-depth curve is obtained; extracting inversion input parameters based on the average load-depth curve; constructing a dimensionless function based on dimensional analysis and a characteristic strain method, fitting the dimensionless function, and establishing a Ludwick constitutive inversion model; and on the basis of the inversion input parameters and the Ludwick constitutive inversion model, the mechanical constitutive parameters are solved, the multiple mechanical constitutive parameters of the material can be directly and uniquely inverted, and the experiment complexity and cost are remarkably reduced while the accuracy and uniqueness of the inversion result are guaranteed.

The invention belongs to the field of temperature field finite element calculation, and discloses a concrete dam operation period temperature field reconstruction calculation method and system, and the method comprises the following steps: S1, determining a concrete temperature field basic theory; s2, establishing a stable temperature field reconstruction method; s3, establishing an unstable temperature field reconstruction method; and S4, verifying the validity of the algorithm in the dam surface temperature inversion analysis process. According to the method, the sensitivity degree of the overall temperature field precision to changes can be reduced, and the temperature field calculation efficiency relative to a traditional inversion analysis method can be improved.

The invention provides an accurate detection method and device for the thermal conductivity of a soldering lug. The method comprises the following steps: applying a thermal pulse to the surface of a to-be-measured material, detecting the propagation time difference of the thermal pulse from a starting point to each measurement point, and constructing a time distribution matrix based on all the propagation time differences; obtaining a target propagation time data set according to the time distribution matrix, and collecting a temperature corresponding to each propagation time in the target propagation time data set on the measurement point to construct a temperature distribution model; based on the temperature distribution model and the target propagation time data set, generating a simulation result of the thermal diffusion behavior of the to-be-tested material under the action of the thermal pulse, and judging whether the simulation result accords with a preset range or not; if the simulation result accords with a preset range, performing inversion analysis based on the simulation result to obtain a first thermal conductivity distribution characteristic graph; and determining the target thermal conductivity of the to-be-tested material based on the first thermal conductivity distribution characteristic pattern. According to the scheme, the thermal conductivity of the material can be accurately obtained.

The invention relates to the technical field of hydraulic engineering dam safety monitoring and maintenance, in particular to a concrete faced rockfill dam extrusion damage predicting and repairing method based on three-dimensional rheological inversion. The method comprises the following steps: firstly, fusing multi-source monitoring data to construct a dam body three-dimensional rheological mechanical model; then, utilizing an intelligent optimization algorithm to drive inversion analysis, automatically determining model parameters, and realizing long-term deformation prediction; based on multiple risk criteria such as stress, displacement and the like, a damaged high-risk area is visually positioned in the model; furthermore, the technical effects of different repair schemes are rehearsed and compared in the digital twinborn model; and finally generating a repair decision report containing the optimal scheme. According to the method, automation and intelligentization of the whole process from data monitoring to decision repair are realized, the objectivity of diagnosis, the accuracy of prediction and the scientificity of decision are greatly improved, and a key technical support is provided for long-term safe operation of the high dam.

The application discloses a tunnel surrounding rock deformation prediction method based on time series and inversion analysis, and comprises the following steps: S1, setting tunnel monitoring points, collecting, testing and preprocessing relevant data obtained by the tunnel monitoring points to obtain pretreatment data; S2, analyzing the surrounding rock level, buried depth and support structure of the monitoring section of each tunnel monitoring point, setting tunnel monitoring reference control values and early warning values; S3, obtaining the management level of the monitoring section of each tunnel monitoring point according to the pretreatment data combined with the tunnel monitoring reference control values and early warning values, analyzing each management level and determining the section for time series analysis and inversion analysis; and S4, collecting the time series data of the section for time series analysis and inversion analysis, and adopting a wavelet-time series analysis model to predict the deformation of the surrounding rock. The application can timely make an advanced prediction on the geological conditions in front of the tunnel and accurately judge the stability of the surrounding rock.

This application discloses a method and system for inverting and analyzing borehole fracture stress fields based on the right dihedral method, relating to the fields of geophysics and geological engineering technology. The method includes: batch loading fault data through a GUI interface and converting it to NED direction cosines; using the right dihedral method to divide the fault into compression and tension zones; using a coarse-fine two-stage grid search to determine the optimal principal stress direction and matching rate; searching for the minimum principal stress direction in the vertical plane and calculating the dual stress axis matching rate; finally, outputting the three principal stress directions based on the comprehensive matching probability and generating a stereographic projection map. This application improves data input efficiency through batch loading via a GUI interface; the two-stage grid search algorithm eliminates human error and improves the calculation accuracy of the optimal principal stress direction and matching rate; multiple statistical indicators provide quantitative evaluation, improving the reliability of the inversion results; and the GUI interface's visualization of the inversion results enhances engineering applicability and interactive efficiency.

The application discloses a long-term performance prediction method and a safety evaluation method for high core wall rockfill dams, comprising: obtaining multi-scale high core wall rockfill dam surface deformation displacement monitoring data based on the Beidou navigation positioning system, space-based radar interferometry and unmanned aerial vehicle LiDAR; establishing a time sequence displacement three-dimensional fusion model of space-time integration coupling dynamic filtering according to the multi-scale high core wall rockfill dam surface deformation displacement monitoring data; jointly using large-scale geotechnical centrifuge testing, large-scale indoor material testing, large-scale fine numerical simulation, prototype monitoring and inversion analysis of field test data to study the deformation mechanism of the time sequence displacement three-dimensional fusion model under different stress conditions; generating a prediction model according to the deformation mechanism of the time sequence displacement three-dimensional fusion model under different stress conditions, and predicting the long-term performance of the high core wall rockfill dam by using the prediction model. The application can improve the safety guarantee level of high dams and large reservoirs.

The application provides a kind of side slope fissure passive source seismic wave imaging method, the patent adopts multi-wave multi-component seismograph, simultaneously gathers multiple seismic wave signals on three components, including surface wave, body wave and the like.This design significantly improves the richness of data, so that in data processing, a variety of seismic wave signals can be comprehensively utilized for inversion analysis.By joint processing and constraint of different wave types, the multi-solution problem in geophysical inversion can be effectively reduced, and the stability and reliability of the results are improved.In addition, the acquisition of multi-component data makes the imaging more comprehensive, especially in the characterization of fissure directionality and geometric features, which has obvious advantages.

The invention discloses a karst disaster source water-rich characteristic multi-field coupling inversion analysis method. The method comprises the following steps: acquiring a tracing penetration curve and a water head change curve of a target area and extracting travel time characteristics; constructing a uniform parameter state vector containing a permeability coefficient, a water storage coefficient and an effective porosity, and establishing a forward model for describing solute transport and an underground water flow process; calculating a sensitivity matrix of the uniform parameter state vector to the observation data based on a forward model, and constructing a joint objective function containing a spatial adaptive regularization item according to the sensitivity matrix; and carrying out iterative solution on the target function by adopting a prediction-correction alternate updating strategy to obtain optimized parameter distribution and delineating a disaster-causing structure position. According to the method, by constructing a multi-physics field synchronous coupling mechanism and a self-adaptive constraint strategy, the problems of error one-way accumulation and physical parameter coupling splitting in traditional serial inversion are solved, and the recognition precision and resolution of the water-rich disaster-caused structure under the complex geological condition are improved.

The invention discloses a magmatic rock spatial distribution prediction method and system based on big data, and the method comprises the steps: obtaining the state data and historical data of a predicted magmatic rock region, constructing a shape impact factor according to the analysis result of a sample of magmatic rock in the predicted magmatic rock region, carrying out the inversion analysis of geophysical data, and obtaining the spatial distribution of the magmatic rock in the predicted magmatic rock region. Matching the sample analysis result with the target state data to obtain a first prediction parameter, inputting the first prediction parameter and a magmatic rock historical database matching result into a magmatic rock spatial distribution prediction model to obtain a magmatic rock prediction parameter, and performing geophysical simulation according to the magmatic rock prediction parameter, and optimizing the magmatic rock spatial distribution prediction model according to a geophysical simulation result, and determining a magmatic rock spatial distribution prediction result. The method not only can improve the accuracy of magmatic rock spatial distribution prediction, but also has good interpretability, and can be directly applied to a magmatic rock spatial distribution prediction system based on big data.

The invention relates to the technical field of mining area geological exploration, and particularly discloses an inversion analysis method for a concealed structure of a mining area coal face. According to the method, the geophysical exploration anomaly index, the coal mining tunneling anomaly index, the hydrogeological state evaluation index and the gas state evaluation index of each grid unit area of the mining area coal face corresponding to the current monitoring time period are comprehensively analyzed; the hidden structure hidden danger level of each grid unit area of the mining area coal face corresponding to the current monitoring time period is obtained, and corresponding early warning is carried out, so that on one hand, the defects of hidden structure hidden danger early warning analysis of the mining area coal face in the prior art are overcome; and the hidden danger analysis result of the hidden structure of the mining area coal face is more comprehensive and reliable. And on the other hand, the response timeliness of potential safety hazards of the hidden structure of the coal face in the mining area is improved, meanwhile, the probability of accidents caused by the hidden structure is reduced, and reliable guarantee is provided for safe mining of a coal mine.

The application discloses a kind of generalized theory numerical calculation method of the thermal conductivity of multiphase random mixing porous medium, the method includes the following steps: step 1, obtain the porosity of soil sample;Step 2, obtain the thermal conductivity of soil particles;Step 3, obtain the effective thermal conductivity of soil sample and the full state thermal conductivity surface under the porosity of soil sample;Step 4, obtain the volumetric water content and ice content of soil sample.The application innovatively proposes the strategy of using extreme state to calculate the thermal conductivity of soil particles, realizes the double check of parameters, eliminates the calculation error caused by the difference of soil mineral composition, and can obtain the effective thermal conductivity of soil body by calculation using conventional soil parameters.Using the method of the application, the thermal conductivity of soil body can be predicted with high precision only by using easily obtained physical parameters, and online monitoring and inversion analysis can be carried out.This is especially suitable for large-scale engineering projects and soil thermal response prediction, which greatly saves time and economic cost.

The application provides a method for applying a multi-dimension multi-level analysis method to a concrete dam safety monitoring analysis system platform, which comprises the following steps: step 1, classifying different dimensions and different types of monitoring physical quantities obtained by monitoring a reservoir dam by using an SVM classification principle, and judging whether the monitoring physical quantities are gross errors by using a Lade criterion; step 2, performing first layer data analysis on the processed different dimensions and different types of monitoring physical quantities, realizing data compilation, and displaying on the platform; step 3, performing second layer data analysis on the structural analysis and calculation of the dam by combining inversion analysis and using strength theory; step 4, establishing a monitoring model to perform third layer data analysis, and guaranteeing short-term prediction accuracy; and step 5, establishing a medium and long term prediction monitoring model to perform fourth layer data analysis, and guaranteeing long-term prediction accuracy.

The application provides a method and system for simultaneously measuring the ice content and unfrozen water content of frozen soil, and belongs to the technical field of frozen soil parameter measurement based on machine learning. The temperature response curve of frozen soil under a pulse heat source and specific frozen soil parameters are obtained. The specific frozen soil parameters include frozen soil particle density, frozen soil particle thermal conductivity, frozen soil particle specific heat capacity and frozen soil particle specific gravity. The obtained temperature response curve and specific frozen soil parameters are processed by using a pre-trained inversion analysis model to obtain the ice content and unfrozen water content of frozen soil. The application can simultaneously measure the ice content and unfrozen water content of frozen soil within one minute, greatly improves the measurement efficiency, and avoids the assumption conditions of an empirical model.

The present application relates to the technical field of geological modeling, in particular to a geological modeling construction optimization method suitable for open-pit mine geological disaster exploration. The method comprises the following steps: collecting and integrating geological data and geophysical data, determining reasonable drilling positions by using scientific geological inversion analysis method, combining drilling sampling data to construct ore body model, and using GIS system to construct geological profile map to obtain accurate contour parameters, and then constructing original geological three-dimensional model. At the same time, the Bayesian method is introduced to calculate the probability distribution of stratum, and the original model is labeled and compiled to obtain the final high-precision three-dimensional geological model. The method can effectively overcome the shortcomings of traditional methods, improve the accuracy, reliability and scientificity of geological modeling, and provide more accurate and comprehensive geological information support for the prediction, evaluation and prevention of open-pit mine geological disasters.

The invention discloses an inversion analysis method applied to cell stress research, and relates to the technical field of microfluidics, and the method comprises the following steps: firstly, constructing a multi-stage bidirectional fluid-solid coupling kinetic model of a fluid-droplet-particle system, and realizing iterative analysis from suspension liquid, droplet deformation and droplet content particle stress; secondly, a high-speed microscopic imaging system is used for obtaining dynamic distribution of a flow field in the micro-flow tube, and an experimental observation database is constructed; thirdly, establishing a numerical model, and comparing a simulation result of the numerical model with experimental observation data; and finally, quantizing deviation between numerical simulation and experimental data through an inversion function, optimizing model parameters, and realizing accurate inversion of the size of the cell surface stress in a micro-droplet wrapping state. The method is high in detection precision and good in inversion reliability.