Fault detection and isolation using probabilistic wavelet neural operator auto-encoder with application to dynamic processes-Reference-Cited by-同舟云学术

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Fault detection and isolation using probabilistic wavelet neural operator auto-encoder with application to dynamic processes

Published:2023-05 Issue: Volume:173 Page:215-228
ISSN:0957-5820
Container-title:Process Safety and Environmental Protection
language:en
Short-container-title:Process Safety and Environmental Protection

Author:

Rani Jyoti,Tripura Tapas,Kodamana Hariprasad,Chakraborty Souvik,Tamboli Prakash Kumar

Funder

Board of Research in Nuclear Sciences

Publisher

Elsevier BV

Subject

Safety, Risk, Reliability and Quality,General Chemical Engineering,Environmental Chemistry,Environmental Engineering

Reference71 articles.

1. Dynamic failure analysis of process systems using neural networks;Adedigba;Process Saf. Environ. Prot.,2017

2. Sounds and acoustic emission-based early fault diagnosis of induction motor: a review study;AlShorman;Adv. Mech. Eng.,2021

3. Risk-based fault detection and diagnosis for nonlinear and non-gaussian process systems using r-vine copula;Amin;Process Saf. Environ. Prot.,2021

4. A data-driven bayesian network learning method for process fault diagnosis;Amin;Process Saf. Environ. Prot.,2021

5. A deep learning model for process fault prognosis;Arunthavanathan;Process Saf. Environ. Prot.,2021

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