Artificial Immune System for Condition Monitoring Based on Euclidean Distance Minimization

In recent years new alternative diagnostics methodologies have emerged, with particular interest to machineries operating in non-stationary conditions, which have shown to be a severe limit for standard consolidated approaches. In particular this paper focuses on the condition monitoring of ball-bearings in variable-speed applications. In this context the paper aims to present a simple method inspired and derived from the mechanisms of the immune system, and its application in a real case of bearing faults recognition. The proposed algorithm is a simplification of the original process, adapted to a particular case of a much bigger class of algorithms and methods grouped under the name of Artificial Immune Systems, which have proven to be useful and promising in many different application fields. The proposed algorithm is based on the Euclidean distance minimization in the evaluation of the binding between antigens. Experimental results are also provided with an explanation of the algorithm functioning