Explainable fault diagnosis of gas-liquid separator based on fully convolutional neural network-Reference-Cited by-同舟云学术

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Explainable fault diagnosis of gas-liquid separator based on fully convolutional neural network

Published:2021-12 Issue: Volume:155 Page:107535
ISSN:0098-1354
Container-title:Computers & Chemical Engineering
language:en
Short-container-title:Computers & Chemical Engineering

Author:

Liu Jiaquan,Hou Lei,Wang Xin,Zhang Rui,Sun Xingshen,Xu Lei,Yu Qiaoyan

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computer Science Applications,General Chemical Engineering

Reference45 articles.

1. Robust interpretable deep learning for intelligent fault diagnosis of induction motors;Abid;IEEE Trans. Instrum. Meas.,2020

2. Interpretable and lightweight convolutional neural network for EEG decoding: application to movement execution and imagination;Borra;Neural Netw.,2020

3. Artificial Intelligence Comes of Age in Oil and Gas;Braswell;Journal of Petroleum Technology,2013

4. Development directions of industrial artificial intelligence;Chai;Acta Autom. Sin.,2020

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