Tunnel face surrounding rock intelligent grading method based on neural network

• Main Authors: ZHANG JUNQING, TANG CHAO, MA XIHAI, QIAO HONGLEI, XU LIMING, TIAN JING, ZHANG TIEJUN, LIANG ZUQUAN, LI LUHENG, YANG XIN'AN
• Format: Patent
• Language: Chinese; English
• Published: 21.07.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a tunnel face surrounding rock intelligent grading method based on a neural network. The method comprises surrounding rock strength acquisition, rock integrity acquisition and surrounding rock grading. The step of acquiring the surrounding rock strength comprises the following steps: selecting a tunnel face surrounding rock rebound value and a geological development degree which are tested on site as input indexes; constructing an RBF learning model based on an RBF neural network intelligent algorithm, and inputting learning sample data into the RBF learning model to optimize parameters; and establishing an RBF learning model by using the optimized parameters, and inputting test sample data into the RBF learning model to obtain a surrounding rock strength output result. The step of acquiring the integrity degree of the rock comprises the following steps: shooting an image of surrounding rock of a tunnel face; acquiring a complete image of the tunnel face by using an image recognition p