Slope stability analysis system and method based on machine vision

Abstract

The invention relates to the field of slope stability analysis, and discloses a slope stability analysis method based on machine vision, which comprises the following steps: acquiring image information of a slope at different time periods, and generating a slope image data set; preprocessing the acquired slope image data set, extracting time features and spatial features of the preprocessed slope image data set, and associating the extracted time features and spatial features to each pixel point of the slope image; according to a feature extraction result, carrying out standardized and normalized data processing on the extracted result, carrying out modeling analysis according to a data processing result, and outputting a simulation analysis result; and generating an evaluation report according to the simulation analysis result. By observing the spatial relationship of the target spots on the side slope images collected at different times, possible deformation of the side slope is predicted, so that the prediction efficiency of the stability of the side slope is improved.

Description

technical field [0001] The invention relates to the technical field of slope stability analysis, in particular to a machine vision-based slope stability analysis system and method. Background technique [0002] my country is a country with frequent geological disasters. According to relevant data, nearly 70% of geological disasters are related to slope instability and collapse. Therefore, accurate, effective and rapid analysis and evaluation of slope stability is of great significance for the risk management and control of slope geological hazards. [0003] Slope engineering is a system with uncertainty, nonlinearity, and high complexity, and its stability is affected by various random, fuzzy, and complex factors. However, the use of these methods is limited by factors such as the availability and accuracy of slope engineering geological data and the knowledge and experience of evaluators. [0004] Therefore, try to use uncertain analysis methods, such as fuzzy analytic hi...

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Problems solved by technology

[0003] Slope engineering is a system with uncertainty, nonlinearity, and high complexity, and its stability is affected by various random, fuzzy, and complex factors. However, the use of these methods is limited by factors such as the availability and accuracy of slope engineering geological data and the knowledge and experience of evaluators.

[0004] Therefore, try to use uncertain analysis methods, such as fuzzy analytic hierarchy process, rough set theory, intuitionistic fuzzy set method, Bayesian method, machine learning method, etc. to analyze slope stability. It has been well applied in , but because it requires too many samples, and the sample data in the test process often faces the problem of insufficient, so the prediction accuracy is limited by the number of samples and cannot be effectively improved, and the Although the prediction method overcomes some limitations of a single algorithm, it introduces new parameters into the optimized model, which increases the complexity of the model, but the efficiency and accuracy of its prediction results have not been significantly improved.

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