An Order-Invariant and Interpretable Dilated Convolution Neural Network for Chemical Process Fault Detection and Diagnosis-Reference-Cited by-同舟云学术

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An Order-Invariant and Interpretable Dilated Convolution Neural Network for Chemical Process Fault Detection and Diagnosis

Published:2023 Issue: Volume: Page:1-11
ISSN:1545-5955
Container-title:IEEE Transactions on Automation Science and Engineering
language:
Short-container-title:IEEE Trans. Automat. Sci. Eng.

Author:

Li Mengxuan¹^ORCID,Peng Peng²^ORCID,Sun Haiyue²^ORCID,Wang Min³,Wang Hongwei²^ORCID

Affiliation:

1. College of Computer Science and Technology, Zhejiang University, Hangzhou, China

2. Zhejiang University–University of Illinois, Urbana–Champaign Institute, Haining, China

3. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/8856/4358066/10172249.pdf?arnumber=10172249

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4. MQKIN: Manufacturing Quality Knowledge-Driven Interpretable Fault Diagnosis Network for Robotic Grinding Equipment;IEEE Transactions on Automation Science and Engineering;2024

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