Resilient fault detection for industrial process using adaptive Fisher discriminant analysis with wavelet denoising

Resilient fault detection for industrial process using adaptive Fisher discriminant analysis with wavelet denoising

In this paper, fault detection in industrial process using adaptive fisher discriminant analysis (AFDA) with optimization of wavelet denoising (WD) parameters is discussed. Particle swarm optimization (PSO) is used to set the wavelet denoising parameters. Among several important factors in effective...

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Bibliographic Details
Main Authors: Faizan E. Mustafa, Ali M. El-Rifaie, M.M.R. Ahmed, Fahmi Elsayed, Hasnain Ahmad, Ijaz Ahmed
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Results in Engineering
Subjects:
Adaptive FDA
False alarm rate
Industrial process
Particle swarm optimization
Missed detection rate
Wavelet denoising
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025027379
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