{"DOI":"10.5281/zenodo.4418876","abstract":"Railway bearing is one of the important parts which constructs
boogie structure in a passenger train. This part should be
monitored from bearing failure phenomena at any time for
passenger safety during traveling. This study presents an
effective denoising noisy signal for bearing condition monitoring.
A noisy signal was created first, then separated by Empirical
Mode Decomposition (EMD) to be intrinsic mode
decompositions (IMFs). From IMFs, the noise can be detected,
and then it was removed. Following, IMFs which contain no
noise was then reconstructed to be a new signal. The Hilbert-
Huang spectrum (HHT) spectrum of reconstruction signal was
generated by applying Hilbert transform. HHT of the
reconstruction signal was then compared to the HHT baseline
spectrum and HHT contained noise. The result showed that the
proposed technique works well for analyzing signals. Without
reconstruction technique, the railway bearing condition was
difficult to be revealed by the HHT spectrum.","author":[{"family":"Susanto"},{"family":"Artono"},{"family":"Khonjun"},{"family":"Mahmud"}],"id":"unknown","issued":{"date-parts":[[2020,9,30]]},"publisher":"Zenodo","title":"Denoising of Disturbed Signal using Reconstruction Technique of EMD for Railway Bearing Condition Monitoring","type":"article-journal"}