10 results about "Slope failure" patented technology

The invention discloses a rock mass parameter inversion method and system based on automatic machine learning, and the method comprises the steps: obtaining temporal and spatial change features from rock mass monitoring data, constructing a feature importance evaluation system, and obtaining a standardized feature vector; according to the coordinated parameter transmission and model synchronization result, rock mass strength and deformation parameters are obtained, a correlation analysis model is adopted to calculate a safety coefficient and a damage probability, and a harmfulness evaluation index is obtained; the method comprises the following steps: acquiring a parameter distribution rule and a change trend, constructing a parameter database system for classified filing and version control, obtaining centralized management platform data, extracting historical tracing information, triggering a dynamic adjustment inversion strategy if the change trend exceeds a preset threshold, and obtaining a real-time updated parameter statistical analysis result for integrated risk prediction. According to the method, the accuracy of rock mass parameter inversion and the real-time performance of engineering risk prediction are remarkably improved, the slope damage probability is reduced, and engineering safety and efficient management are ensured.

The application provides a photovoltaic slope safety evaluation method considering spatiotemporal variability of multi-source parameters, comprising: collecting geological exploration data and multi-source monitoring data of a photovoltaic slope, determining a random distribution type of initial multi-source parameters, and selecting key monitoring data; performing data matching of multi-source parameters and monitoring data, and screening multi-source parameters and monitoring data by using a MIC algorithm; based on field geological exploration data, a three-dimensional simulation model considering spatiotemporal variability of multi-source parameters of the photovoltaic slope is constructed, and a data set is obtained; based on a 1D-CNN-MCMC deep learning model framework, the data set is trained, and a posterior probability distribution of a safety factor FS of the photovoltaic slope is dynamically updated in combination with field monitoring data; a failure probability P of the photovoltaic slope is calculated f , and safety evaluation and early warning are performed. The application comprehensively considers uncertain factors such as slope geological parameter variability, environment, and photovoltaic structure, uses field multi-source monitoring data, obtains a photovoltaic slope failure probability more in line with actual conditions, and performs safety evaluation and early warning.

The invention belongs to the technical field of disaster identification and prediction, and provides a slope failure instability mode intelligent identification method and system, and the technical scheme is that the method comprises the steps: taking the engineering feature information subjected to parameterized coding processing in a slope failure instability database as an input parameter, taking the slope failure instability mode as an output parameter, and constructing a plurality of parameter combination schemes; each individual of the genetic algorithm is expressed as an input feature subset, performance evaluation is performed on the slope failure instability mode intelligent identification model trained under different parameter combination schemes, a fitness function of each individual is determined according to a performance evaluation result, and a feature subset corresponding to the optimal individual is found through iterative optimization; and predicting the to-be-identified scheme based on the obtained feature subset corresponding to the optimal individual to obtain a slope failure instability mode prediction result. And the efficiency and the accuracy of the slope failure instability mode identification means are improved.

The invention relates to a geotechnical characteristic information parameterization method for intelligent prediction of a slope instability mode. The geotechnical characteristic information parameterization method comprises the following steps: identifying and classifying to-be-processed slope original characteristic information; encoding the text type data and the numeric type data; defining a coding result as an input parameter of the slope instability mode prediction model; obtaining classification labels used for representing different instability modes, and defining the classification labels as output parameters; outputting the data set; the data set is used for constructing and training a slope instability mode prediction model. The method has the advantages that the generated standardized data set is clear in physical significance, rigorous in logic and uniform in format and can be directly called by a machine learning algorithm, a high-quality training basis is provided for an intelligent analysis model, and the training efficiency and prediction accuracy of a slope instability mode intelligent judgment model are remarkably improved.

The application provides a submarine slope stability evaluation method and system, and belongs to the field of landslide disaster prevention and control. The method is based on the range of the submarine slope to be evaluated, acquires a digital elevation model (DEM) of the to-be-evaluated area, and divides sample points corresponding to a grid; at least five unstable factors of the sample points are collected, a geomechanics model is constructed to calculate a safety factor, and the sample points are divided into current stable points and observation points; based on the observation points, the contribution values of all parameters of the unstable factors to the safety factor are sorted, and the top three parameters are taken as observation factors; a correlation stability evaluation model is constructed, for each observation point, based on the three observation factors of the current observation point, the nearest neighbor sample point and the second nearest neighbor sample point, the failure probability of the current observation point is calculated, a submarine slope failure risk map is drawn, and an unstable early warning is issued for the observation points reaching the failure probability threshold. The application reduces the calculation amount of the submarine slope stability evaluation, and improves the evaluation accuracy.

The embodiment of the invention provides a side slope stability state dynamic identification method, device and equipment. The side slope stability state dynamic identification method comprises the following steps: obtaining monitoring data of a target side slope about inclination angle change; determining the slope damage type of the target slope according to the monitoring data and a preset slope damage type judgment standard; performing feature extraction on the monitoring data in response to the fact that the slope damage type of the target slope is an acceleration type; determining the current failure rate of the target slope based on the extracted features; and calling a pre-constructed prediction model to generate a time prediction value when the landslide phenomenon of the target slope occurs based on the damage rate.

The application discloses a reinforcing support method for a slide-pile type slope failure mode, and a reinforcing support structure is composed of a steel rail pile structure (1), a prestressed anchor cable structure (2) and a frame beam structure (3) which are combined and connected into a whole; the steel rail pile structure (1) is composed of a row of steel rails which are vertically arranged in an upper slide-pile rock mass (4) of the slide-pile type slope failure structure and deeply penetrate into a stable bedrock in a bedding internal part; the prestressed anchor cable structure (2) is composed of a row of prestressed steel strands which are arranged in a lower rotating rock mass (5) of the slide-pile type slope failure structure and deeply penetrate into the stable bedrock in the bedding internal part; and the frame beam structure (3) is composed of two mutually parallel cross beams (3-1) and a row of vertical beams (3-2) which are in transition with the cross beams (3-1) and are mutually perpendicular to the cross beams (3-1). The application can play a role of "blocking upward and pulling downward" on the slide-pile type rock slope failure, meanwhile, the frame beam can effectively connect all the structures to form a complete reinforcing system, thereby guaranteeing the stability of the slide-pile type failure slope.

This invention relates to a wind-resistant prefabricated foundation for transmission towers in mountainous areas and its assembly method, belonging to the field of power engineering technology. It aims to solve the technical problems of existing mountain transmission tower foundations, such as easy loosening due to freeze-thaw cycles, inconvenient construction, insufficient wind resistance, and slope failure caused by soil erosion. The foundation includes a ground surface, a pit, an anchoring mechanism, a wire mesh foundation I, a wire mesh foundation II, a frozen soil adaptive expansion mechanism, a connecting sleeve, a slope protection mechanism, and foundation columns. Each component is prefabricated in the factory and assembled on-site. The anchoring mechanism achieves automatic anchoring, the wire mesh foundations are arranged in reverse to enhance wind resistance, the frozen soil adaptive expansion mechanism uses its own weight to compensate for freeze-thaw gaps and self-locks, and the slope protection mechanism adapts to soil erosion and adheres closely to the soil surface. This invention eliminates the need for complex grouting, is convenient to construct, achieves freeze-thaw adaptation, strong wind resistance, and prevention of soil erosion, requires no secondary manual maintenance, is suitable for complex working conditions in mountainous areas, and extends the service life of the foundation.

The invention relates to a wind-resistant fabricated foundation suitable for a power transmission tower in a mountainous area and an assembly method thereof, belongs to the technical field of electric power engineering, and aims to solve the technical problems that an existing power transmission tower foundation in the mountainous area is easy to loosen in freeze-thaw cycle, inconvenient to construct, insufficient in wind resistance and ineffective in slope protection due to soil loss. The foundation comprises a foundation surface, a foundation pit groove body, an anchoring mechanism, a mesh cage foundation I, a mesh cage foundation II, a frozen soil self-adaptive expansion mechanism, a butt joint sleeve, a slope protection mechanism and a foundation stand column, all the parts are prefabricated in a factory and spliced on site, the anchoring mechanism achieves automatic anchoring, the mesh cage foundations are reversely arranged, and the wind resistance rigidity is enhanced. According to the self-adaptive slope protection structure, complex grouting is not needed, construction is convenient and fast, freeze-thaw self-adaption, strong wind resistance and soil loss prevention can be achieved, manual secondary maintenance is not needed, the self-adaptive slope protection structure adapts to complex working conditions of mountainous areas, and the service life of a foundation is prolonged.

The invention relates to the field of rock and road engineering, and discloses a slope stability analysis method considering a soil structure. Comprising the following steps: S1, measuring basic parameters of a soil body, S2, measuring a soil-water characteristic curve, S3, calculating an unsaturated permeability coefficient, S4, analyzing structural parameters of the soil body, S5, constructing a slope numerical simulation model, S6, reducing and setting non-equal proportion coefficients, S7, calculating a comprehensive safety coefficient, and S8, simulating slope failure characteristics. According to the method, soil structure quantitative characterization and unsaturated seepage-stress field action are coupled, the influence of the soil structure is considered in slope stability calculation, and accurate simulation of the slope progressive failure process is achieved.