Insight Volume 63 No 7
July 2021
Comment, by Dr W E Gardner
NEWSDESK: Loughborough University develops new AI tool for recognising
and classifying wind turbine blade defects; Non-destructive inspection of large components taken to the next level; Hitachi High-Tech opens state-of-the-art production facility in Shanghai, China
FEATURES
Wheel flat detection and severity classification using deep learning techniques,
by J Sresakoolchai and S Kaewunruen
Detection and evaluation of rolling stock wheelset defects using acoustic emission,
by J Sresakoolchai and S Kaewunruen
Detection and evaluation of rolling stock wheelset defects using acoustic emission,
by E Giannouli, M Papaelias, A Amini, Z Huang, V L Jantara Junior, S Kerkyras, P Krusuansombat, F P Garcia Marquez and P Vallely
Improving the robustness of DI and PVI further using fast guided filter on
radiographic images,
by Changying Dang, Jiansu Li, Zhiqiang Zeng, Wenhua Du and Rijun Wang
by Changying Dang, Jiansu Li, Zhiqiang Zeng, Wenhua Du and Rijun Wang
Optimising sensor pitch for magnetic flux leakage imaging systems,
by R Murshudov, J M Watson, C W Liang, J Sexton and M Missous
by R Murshudov, J M Watson, C W Liang, J Sexton and M Missous
Mechanical properties of TiO2 nanotubes investigated by AFM and FEM,
by Zuozhang Wang, Ji Zhou, Yunhong Jiang, Zhongmei Yang and Yanhuai Ding
by Zuozhang Wang, Ji Zhou, Yunhong Jiang, Zhongmei Yang and Yanhuai Ding
Multivariate non-destructive evaluation for tensile strength of steel based on
neural network,
by Junyang Tan, Dan Xia, Shiyun Dong, Honghao Zhu and Binshi Xu
by Junyang Tan, Dan Xia, Shiyun Dong, Honghao Zhu and Binshi Xu
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