Recent Advanced In AI Based Intelligent Fault Techniques for Rolling Element Bearing – A Review

Research areas:

• Volume 2,Issue 4, Jan. 2014

Year:

2014

Type of Publication:

Article

Keywords:

Fault Detection, Rolling Bearing, Neural Network, Expert System, Fuzzy Logic, Hybrid AI Techniques

Authors:

Vaishali Patel; Amit Patel

Journal:

IJAIM

Volume:

3

Number:

4

Pages:

104-108

Month:

January

Abstract:

Bearings are essential components of most machinery and their operating conditions influence directly the operation of the whole machinery. The majority of the problems in rotating machines are caused by faulty bearings. Moreover, most of the bearing condition monitoring methods in vogue needs the assistance of an expert in the interpretation of results, and the success rates achieved are less than those required by the modern automated industries. Hence, the need arises for the development of a new scheme to outperform all the state-of-the-art techniques in ANN. This paper presents a review of the application of Artificial Intelligence (AI) techniques in fault diagnosis of rolling bearing. The variety of methods used, are discussed and analyzed with critical comments. Based on the overall review of the techniques for diagnosis bearing, some conclusions are drawn from the literature.

Full text: IJAIM_206_Final.pdf