Health Assessment of Rotating Machinery Using a Rotary Encoder

In this paper, a systematic framework is established for health assessment of rotating machinery using a rotary encoder. In this framework, spectral quadratic weighting is first developed to convert encoder signals into acceleration series. Comb filtering is then introduced to remove the interferences resulting from drive/load variations. Finally, an adaptive denoising scheme based on Gini index is proposed to enhance the impulses caused by mechanical defects. The simulation and experimental results show that the proposed method is sensitive to incipient faults, and offers a promising tool for health assessment of rotating machinery.