Data-Driven Optimal Test Selection Design for Fault Detection and Isolation Based on CCVKL Method and PSO-Reference-Cited by-同舟云学术

Data-Driven Optimal Test Selection Design for Fault Detection and Isolation Based on CCVKL Method and PSO

Published:2022 Issue: Volume:71 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Li Yang¹^ORCID,Chen Hongtian²^ORCID,Lu Ningyun¹^ORCID,Jiang Bin¹^ORCID,Zio Enrico³^ORCID

Affiliation:

1. College of Automation Engineering and the Key Laboratory of Internet of Things and Control Technologies, Nanjing University of Aeronautics and Astronautics, Nanjing, China

2. Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Canada

3. Crisis Research Centre (CRC), MINES ParisTech, PSL Research University, Paris, France

Funder

National Natural Science Foundation of China

NSFC through the Projects of International Cooperation and Exchanges

“111” Project

Postgraduate Research and Practice Innovation Program of Jiangsu Province

Funding for Outstanding Doctoral Dissertation in the Nanjing University of Aeronautics and Astronautics

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09760375.pdf?arnumber=9760375

Reference39 articles.

1. On the distributional transform, Sklar's theorem, and the empirical copula process

2. Structural reliability analysis using a copula-function-based evidence theory model

3. The Monte Carlo Simulation Method for System Reliability and Risk Analysis

4. Conditional Joint Distribution-Based Test Selection for Fault Detection and Isolation

5. A new test points selection method for analog fault dictionary techniques

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