A novel dynamic nonlinear non-Gaussian approach for fault detection and diagnosis

Yihan Ma; Fei Ye; Dazi Li; Jinglin Zhou

doi:10.1016/j.neucom.2025.129403

ScienceGate Book Chapters

JOURNAL ARTICLE

A novel dynamic nonlinear non-Gaussian approach for fault detection and diagnosis

Yihan Ma Fei Ye Dazi Li Jinglin Zhou

Year: 2025 Journal: Neurocomputing Vol: 624 Pages: 129403-129403 Publisher: Elsevier BV

DOI: 10.1016/j.neucom.2025.129403

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Nonlinear system Fault detection and isolation Gaussian Fault (geology) Artificial intelligence Pattern recognition (psychology) Gaussian process Algorithm Machine learning Physics Geology

Metrics

Cited By

11.15

FWCI (Field Weighted Citation Impact)

Refs

0.93

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Mineral Processing and Grinding

Physical Sciences → Engineering → Mechanical Engineering

Spectroscopy and Chemometric Analyses

Physical Sciences → Chemistry → Analytical Chemistry

A novel dynamic nonlinear non-Gaussian approach for fault detection and diagnosis

Metrics

Citation History

Topics

Related Documents

Minimum entropy fault detection for dynamic multivariate nonlinear non-Gaussian stochastic systems

Dynamic kriging based fault detection and diagnosis approach for nonlinear noisy dynamic processes

Fault detection and diagnosis of non-linear non-Gaussian dynamic processes using kernel dynamic independent component analysis

Incipient fault detection in nonlinear non-Gaussian noisy environment

Kriging based Fault Detection and Diagnosis Approach for Nonlinear Noisy Dynamic Processes