Work

Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals

Year: 2014

Type: article

Source: Applied Acoustics

DOI: 10.1016/j.apacoust.2014.08.016

Authors: Jaouher Ben Ali, Nader Fnaiech, Lotfi Saidi, Brigitte Chebel-Morello, Farhat Fnaiech

Institutions: Tunis University, Franche-Comté Électronique Mécanique Thermique et Optique - Sciences et Technologies, National Engineering School of Tunis

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: closed

Funders: University of Cincinnati, Case Western Reserve University

OpenAlex ID: W2003205626

FWCI: 29.77

Cites: 31

Cited by: 778

Related to: 10