Early-Stage Fault Diagnosis for Rotating Element Bearing Using Improved Harmony Search Algorithm With Different Fitness Functions

Bearings are the backbone of every rotary machine that ranges from civilian to military applications. A single fault in a bearing can shut down whole causing personal damage and economic loss. To prevent sudden rotating machines, signal processing techniques used find out early-stage faults. In this paper, new detection algorithm is proposed uses Harmony Search (HS) determine optimum frequency spectrum. For that, bandpass filter applied vibration signal, parameters such as center frequency, bandwidth, order dynamic depend on type faults resonance band. estimate filter, different fitness functions based kurtosis spectrum kurtosis. The have highest value compared healthy method fully data-driven, HS employed optimize filter. results with fast kurtogram, it has concluded designed using better performance. validate method, two datasets simulation obtained MATLAB environment.