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公开(公告)号:US20230003674A1
公开(公告)日:2023-01-05
申请号:US17777700
申请日:2020-12-30
Applicant: SHANDONG UNIVERSITY
Inventor: Zhenhao XU , Peng LIN , Guanglu XU , Heng SHI , Tengfei YU , Zhaoyang WANG , Yilei HUA
IPC: G01N23/223
Abstract: 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.
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公开(公告)号:US20230144184A1
公开(公告)日:2023-05-11
申请号:US17881158
申请日:2022-08-04
Applicant: SHANDONG UNIVERSITY
Inventor: Zhenhao XU , Peng LIN , Shucai LI , Huihui XIE , Heng SHI , Zhaoyang WANG , Fumin LIU , Ruiqi SHAO
CPC classification number: E21B49/003 , E21B49/005 , E21D9/003 , E21B2200/20
Abstract: An advanced geological prediction method and system based on perception while drilling, and relates to advanced geological prediction. The solution includes: acquiring drilling parameters during drilling; obtaining physical and mechanical parameters of tunnel surrounding rocks by inversion based on drilling parameters; acquiring rock slag or powder based on flushing fluid collected during drilling; acquiring geochemical characteristic parameters of rock slag or powder; and obtaining at least one adverse geology recognition result and surrounding rock classification result using a pre-trained deep learning model, and realizing advanced geological prediction. Combined with advanced geological drilling, the solution reflects geological characteristics from changes of physical and mechanical properties of tunnel surrounding rocks and changes of geochemical characteristic parameters. Advanced prediction of geology ahead of a tunnel face is realized by collection and analysis of drilling parameters and flushing fluid during advanced drilling and the fusion of big data and a deep learning algorithm.
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公开(公告)号:US20220412867A1
公开(公告)日:2022-12-29
申请号:US17777801
申请日:2020-01-21
Applicant: SHANDONG UNIVERSITY
Inventor: Zhenhao XU , Huihui XIE , Shucai LI , Peng LIN , Xin HUANG , Zhaoyang WANG , Dongdong PAN , Youbo LIU
IPC: G01N15/02
Abstract: 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.
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