Shandong University

Zhaoyang Wang

Peng Lin

Zhenhao Xu

Shucai Li

Dongdong Pan

Xin Huang

Tengfei Yu

Huihui Xie

Heng Shi

Youbo Liu

Guanglu Xu

Yilei Hua

A TBM-mounted system and method for quickly predicting compressive strength of rocks based on rock mineral composition and fabric characteristics. The system is mounted on gripper shoe's side surface of an open-type TBM, and includes a protective device, hydraulic device, servo motor, detection device, control system and a data comprehensive analysis platform. The hydraulic device is mounted on the protective device's side wall, for controlling movement of detection device horizontally. The servo motor controls rotation of detection device. The detection device collects a variety of geological parameters of target surrounding rock affecting compressive strength of rock and providing basic data for compressive strength prediction of rock. The control system controls work of hydraulic device, servo motor and each detection device. The data comprehensive analysis platform is connected to each detection instrument, receives geological parameters collected, processes and analyzes each parameter, and gives a prediction of compressive strength of rock.

TBM-mounted system and method for quickly predicting compressive strength of rocks based on rock mineral composition and fabric characteristics

A system and method for identifying lithology based on images and XRF mineral inversion solving the problem that conventional lithology identification relies on manual work, which is time-consuming, subjective and can cause misjudgment. The identification system includes an autonomous vehicle; an X ray fluorescence spectrometer probe, and tests surrounding rock element information; image collection device; and vehicle-mounted processor. The processor inverts the received surrounding rock element information into mineral information based on a Barthes-Niggli standard mineral calculation method; and receive surrounding rock images and a corresponding inclination angle thereof, convert the surrounding rock images into image information in a one-dimensional vector format, splice the image and mineral information which is in a one-dimensional format, and distinguish the spliced information based on a preset neural network to identify rock lithology.

System and method for identifying lithology based on images and XRF mineral inversion

Growing community of inventors

Jinan, China

Zhaoyang Wang