Intelligent Surrounding Rock Classification Based on Fuzzy Inference

Research purposes: The classification of surrounding rock is an indispensable boundary condition in tunnel construction. The traditional method of surrounding rock classification has many drawbacks in terms of timeliness and completeness, and the sample size available in actual engineering is relatively small. In this paper, the fuzzy inference method is introduced to intelligentize the classification of surrounding rock, the fuzzy rules are extracted from the previous classification data of surrounding rock, and a fuzzy inference engine is constructed to realize intelligent classification of surrounding rocks based on fuzzy inference, so as to solve practical problems in engineering. Research conclusions:(1) Three kinds of fuzzy rule generation algorithms and their advantages and disadvantages are analyzed and studied. (2) The six conditional parameters and value ranges used by the membership function of fuzzy sets are clarified. (3) The feasibility of grading a small number of samples of surrounding rock realizes efficient and accurate grading of surrounding rock. (4) Practice shows that the intelligent surrounding rock classification system designed based on fuzzy reasoning method can meet the actual needs of engineering, and can provide reference for similar engineering applications. © 2022, Editorial Department of Journal of Railway Engineering Society. All right reserved.