Unsupervised Fault Detection Driven by Multivariate Time Series for Aeroengines-Reference-Cited by-同舟云学术

Unsupervised Fault Detection Driven by Multivariate Time Series for Aeroengines

Published:2023-03 Issue:2 Volume:36 Page:
ISSN:0893-1321
Container-title:Journal of Aerospace Engineering
language:en
Short-container-title:J. Aerosp. Eng.

Author:

Chen Mengyu¹^ORCID,Li Zechen²,Lei Xiang³,Liang Shan⁴^ORCID,Zhao Shuangxin⁵,Su Yiting⁵

Affiliation:

1. Director, Chengdu Aircraft Industrial (Group) Co., Ltd., Weiyi St. No. 88, Qingyang District, Chengdu, Sichuan 610073, China. ORCID: .

2. Ph.D. Candidate, School of Automation, Chongqing Univ., Shapingba St. No. 174, Shapingba District, Chongqing 400044, China.

3. Director, Chengdu Aircraft Industrial (Group) Co., Ltd., Weiyi St. No. 88, Qingyang District, Chengdu, Sichuan 610073, China.

4. Professor, School of Automation, Chongqing Univ., Shapingba St. No. 174, Shapingba District, Chongqing 400044, China (corresponding author). ORCID: .

5. Vice Director, Chengdu Aircraft Industrial (Group) Co., Ltd., Weiyi St. No. 88, Qingyang District, Chengdu, Sichuan 610073, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Aerospace Engineering,General Materials Science,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JAEEEZ.ASENG-4576

Reference47 articles.

1. A Learning Algorithm for Boltzmann Machines*

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5. An Ordination of the Upland Forest Communities of Southern Wisconsin

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