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Abstract
As regards bearing fault detection of induction motors using stator current, anything unrelated to the faults is the “noise”. The noise attenuation leads to an improved estimation of the bearing fault signal. The gist of this study is the integration and synchronization of the three residues obtained from the current noise cancelation methods: Time Shifting and Linear Prediction. This procedure results in a richer bearing fault signal than any of the individual residues through cross-correlation. The developed method efficiently synchronizes and integrates the current residues so that fault characteristic frequencies can be more conspicuous in spectral analysis. Both simulation and experimental results attest to the merit and effectiveness of the developed method in detecting both outer and inner race bearing faults.
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Notes on contributors
Asadollah Kalantar
Asadollah Kalantar is a Ph.D. student in mechanical engineering at the IUST, Tehran, Iran. Since 2018, He has been the Research and Development (R&D) of IOPTC manager. He works on condition monitoring of rotating machine such as electro pump, turbo generator, and turbo pump.
Mir Saeed Safizadeh
Mir Saeed Safizadeh is an Associate Professor at the IUST, Tehran, Iran. He received the Ph.D. degree in mechanical engineering from the Ecole Polytechnique of Montreal, Canada, in 1999. He works on the field of nondestructive testing, monitoring and diagnosis of rotating machines, fusion of data, and signal processing.
Fardin Dalvand
Fardin Dalvand received the M.Sc. degree in electrical engineering from AUT University, Tehran, Iran, in 2007. Since 2010, he has been an Electrical Engineer in the IOPTC Company, Iran. He works on electric machines, signal processing, modeling, and condition monitoring.