Gaussian Process Model of Surrounding Rock Classification Based on Digital Characterization of Rock Mass Structure and Its Application

Abstract

As the important data basis of surrounding rock classification, rock mass structural information obtained by traditional image processing and feature extraction algorithms could not be quantitatively analyzed because of the uncertainty and geometric randomness of structural planes. In this paper, based on straight line detection, intelligent scissors, and morphological edge detection algorithms, the multiple interpretation system of rock mass image including linear bunching extraction, magnetic tracking extraction, and multiparameter characterization was researched and developed, and the actual distribution information and the related probability distribution model of structural planes could be obtained directly. On the basis of this, plenty of corresponding random rating-values meeting the probability distribution models of these evaluation indices were gained by Monte Carlo Simulation. The distribution probability affiliated with different rock mass grade was attained by inductive statistics, and the robust evaluation of surrounding rock classification could be carried out. Taking the robust results as learning samples, the response model of surrounding rock grade based on Gaussian process classification was established, making the evaluation of surrounding rock subclassification more rapid and robust.

Surrounding Rock Stability Classification Method of Coal Roadway Based on In Situ Stress

“…Owing to the influence of the thickness, structure, bedding, joint, and fracture spacing of the rock mass, the parameters of the rock mass strength index are difficult to obtain, so it is difficult to apply on site. He et al [22][23][24] proposed an improved discontinuous deformation analysis (DDARF) method to achieve the simulation of the joint distribution by performing a numerical simulation of the deformation and fracture processes of the surrounding rock. However, this method requires special petrographic measurement techniques and image processing methods.…”