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Ji, Y. (author), Li, Ni (author), Cheng, Zhanming (author), Fu, Xiaoqian (author), Sun, Xiaoguang (author), Chowwanonthapunya, Thee (author), Zhang, Dawei (author), Ren, Jingli (author), Dey, P. (author), Dong, Chaofang (author)
Corrosion jeopardizes the materials longevity and engineering safety, hence the corrosion rate needs to be forecasted so as to better guide materials selection. Although field exposure experiments are dependable, the prohibitive cost and their time-consuming nature make it difficult to obtain large dataset for machine learning. Here, we...
journal article 2022
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Chen, Yiming (author), Sun, Xu (author), Xu, Liang (author), Ma, Sencai (author), Li, Jun (author), Pang, Y. (author), Cheng, Gang (author)
The most common failures of belt conveyors are runout, coal piles and longitudinal tears. The detection methods for longitudinal tearing are currently not particularly effective. A key study area for minimizing longitudinal belt tears with the advancement of machine learning is how to use machine vision technology to detect foreign items on...
journal article 2022