Аннотация
Abstract The optical polarization method with ring-shaped photoelastic sensors, digital photography of isochromatic patterns and their clarification using neural networks is developed for the stress measurement in rock mass. The case-studies of the photoelasticity application in solving various problems of elasticity and rock pressure analysis are reviewed. As a result of a lab-scale experiment, a data set of 15000 isochromatic images is collected. The machine learning algorithm was a convolutional neural network, the Inception module. The authors recommend using downhole sensors for the continuous stress monitoring in underground mines and integrating the obtained data in a digital model with the help of IoT.