Clonal Optimization of Negative Selection Algorithm with Applications in Motor Fault Detection

In this paper, we employ the clonal optimization method to optimize the detectors in the negative selection algorithm (NSA). Taking advantage of the clonal optimization strategy, the NSA detectors can be optimized for anomaly detection. A new motor fault detection scheme using our NSA is also discussed. We demonstrate the efficiency of the proposed approach with an example of bearings fault detection.

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