Low-cost and Small-sample Fault Diagnosis for 3D Printers Based on Echo State Networks

Kun He, Lianghua Zeng, Qin Shui, Jianyu Long, Chuan Li, Diego Cabrera

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations
Original languageEnglish
Title of host publication2019 Prognostics and System Health Management Conference, PHAI-Qingdao 2019
EditorsWei Guo, Steven Li, Qiang Miao
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728108612
DOIs
StatePublished - Oct 2019
Event10th Prognostics and System Health Management Conference, PHM-Qingdao 2019 - Qingdao, China
Duration: 25 Oct 201927 Oct 2019

Publication series

Name2019 Prognostics and System Health Management Conference, PHM-Qingdao 2019

Conference

Conference10th Prognostics and System Health Management Conference, PHM-Qingdao 2019
CountryChina
CityQingdao
Period25/10/1927/10/19

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work is supported in part by the National Natural Science Foundation of China (71801046, 51605406 and 51775112), and the Research Program of Higher Education of Guangdong (2016KZDXM054, 2018KQNCX343).

Publisher Copyright:
© 2019 IEEE.

Keywords

  • 3D printer
  • echo state networks
  • fault diagnosis
  • feature extraction
  • machine learning

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