Abstract—Diagnosis of mechanical faults in rotating structures is a challenging and complex task, especially in the presence of multiple interacting components like gearboxes in machines, and huge background noise. In this paper, a novel gearbox fault diagnosis algorithm based on particle swarm optimization and band pass filtering is presented. Vibration signal acquired from gearbox is adaptively filtered through a band pass filter optimized by particle swarm optimization for extraction of faulty pulses buried in huge background noise. The effectiveness, feasibility and robustness of the proposed method are demonstrated on experimental data. The proposed method has successfully achieved reasonable speed up factor required for real-time applications and at the same time, the quality of the results is preserved.

Index Terms—vibration measurement, structural health diagnostic, signal processing, band pass filters, particle swarm optimization.

Cite: Sajid Hussain, "Gearbox Health Monitoring by Evolutionary Optimization," Journal of Industrial and Intelligent Information, Vol. 3, No. 3, pp. 216-221, September 2015. doi: 10.12720/jiii.3.3.216-221