Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6955150 | Mechanical Systems and Signal Processing | 2016 | 14 Pages |
Abstract
In recent years new diagnostics methodologies have emerged, with particular interest into machinery operating in non-stationary conditions. In fact continuous speed changes and variable loads make non-trivial the spectrum analysis. A variable speed means a variable characteristic fault frequency related to the damage that is no more recognizable in the spectrum. To overcome this problem the scientific community proposed different approaches listed in two main categories: model-based approaches and expert systems. In this context the paper aims to present a simple expert system derived from the mechanisms of the immune system called Euclidean Distance Minimization, and its application in a real case of bearing faults recognition. The proposed method is a simplification of the original process, adapted by the class of Artificial Immune Systems, which proved to be useful and promising in different application fields. Comparative results are provided, with a complete explanation of the algorithm and its functioning aspects.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
L. Montechiesi, M. Cocconcelli, R. Rubini,