Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Qihang Fang"'
Autor:
Tariku Sinshaw Tamir, Gang Xiong, Zhen Shen, Jiewu Leng, Qihang Fang, Yong Yang, Jingchao Jiang, Ehtisham Lodhi, Fei-Yue Wang
Publikováno v:
Heliyon, Vol 9, Iss 9, Pp e19689- (2023)
Additive manufacturing (AM), also known as 3D printing, is a new manufacturing trend showing promising progress over time in the era of Industry 4.0. So far, various research has been done for increasing the reliability and productivity of a 3D print
Externí odkaz:
https://doaj.org/article/30bb153c32044ce8b2fa2aa9a15644bd
Autor:
Tariku Sinshaw Tamir, Gang Xiong, Xisong Dong, Qihang Fang, Sheng Liu, Ehtisham Lodhi, Zhen Shen, Fei-Yue Wang
Publikováno v:
International Journal of Control, Automation and Systems. 20:968-982
Autor:
Qihang Fang, Gang Xiong, MengChu Zhou, Tariku Sinshaw Tamir, Chao-Bo Yan, Huaiyu Wu, Zhen Shen, Fei-Yue Wang
Publikováno v:
IEEE Transactions on Automation Science and Engineering. :1-27
Publikováno v:
IEEE Journal of Radio Frequency Identification. 6:758-763
Autor:
Yongqiang Yang, Zhenbiao Tan, Qihang Fang, Xin Zhou, Hui Li, Changhui Song, Sheng Liu, Shifeng Wen, Shengnan Shen
Publikováno v:
Journal of Manufacturing Processes. 68:347-355
Selective laser melting (SLM) is an additive manufacturing technology that has an extensively applied foreground and practical value in many fields. Despite its powerful manufacturing ability, defects are prone to occur and therefore a more reliable
Publikováno v:
2022 IEEE 18th International Conference on Automation Science and Engineering (CASE).
Autor:
Qihang Fang, Yingda Yin, Qingnan Fan, Fei Xia, Siyan Dong, Sheng Wang, Jue Wang, Leonidas J. Guibas, Baoquan Chen
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200793
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd2dcad83c31da394fc595722e4b4938
https://doi.org/10.1007/978-3-031-20080-9_8
https://doi.org/10.1007/978-3-031-20080-9_8
Publikováno v:
Optics & Laser Technology. 130:106347
In situ monitoring of spatter signatures is often employed to improve product quality during laser-based powder bed fusion (LPBF). This paper describes a novel neural network (NN) based image segmentation method for spatter extraction with a simple l