Deep hybrid state network with feature reinforcement for intelligent fault diagnosis of delta 3-D printers

Shaohui Zhang, Zhenzhong Sun, Chuan Li, Diego Cabrera, Jianyu Long, Yun Bai

Research output: Contribution to journalArticlepeer-review

17 Scopus citations
Original languageEnglish
Article number8728244
Pages (from-to)779-789
Number of pages11
JournalIEEE Transactions on Industrial Informatics
Volume16
Issue number2
DOIs
StatePublished - Feb 2020

Bibliographical note

Funding Information:
Manuscript received January 6, 2019; revised April 17, 2019 and May 9, 2019; accepted May 29, 2019. Date of publication June 3, 2019; date of current version January 14, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 51605406, Grant 51775112, and Grant 71801046; and in part by the Natural Science Foundation of Guangdong Province under Grant 2018A030310029. Paper no. TII-19-0046 (Corresponding author: Jianyu Long.) S. Zhang, Z. Sun, C. Li, J. Long, and Y. Bai are with the School of Mechanical Engineering, Dongguan University of Technology, Dongguan 523808, China (e-mail:, zhangsh@dgut.edu.cn; drzzsun@sina.com; chuanli@dgut.edu.cn; longjy@dgut.edu.cn; baiyun@dgut.edu.cn).

Publisher Copyright:
© 2005-2012 IEEE.

Keywords

  • Deep hybrid state network (DHSN)
  • delta three-dimensional (3-D) printer
  • fault diagnosis
  • feature reinforcement

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