Abstract
The Bearing is utilized to give free direct development to the moving part or with the expectation of complimentary revolution around a fixed axis. Bearings are considered a main part in various mechanical systems. Multi component vibration signals are generated when the machine works. Accelerometers are used to capture generated vibration signal. Vibration signal analysis is effectively used to diagnose bearing faults. There are various methods using empirical mode decomposition (EMD) as their fundamental method to diagnose bearing faults. The proposed method consists of analyzing the kurtosis of residue obtained after removing higher frequency components of the original signal. The proposed technique identifies the boisterous frequency segment in the signal through the iterative procedure. The experimental data were collected from Case Western Reserve University, Ohio. The simulation is done over MATLAB 7.8.1.
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Case Western Reserve University Bearing Data Center Available at: http://csegroups.case.edu/bearingdatacenter/pages/welcome-case-western-reserve-university-bearing-data-center-website
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Dubey, R., Agrawal, D. (2016). A Novel Approach for Diagnosis of Noisy Component in Rolling Bearing Using Improved Empirical Mode Decomposition. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 380. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2523-2_46
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DOI: https://doi.org/10.1007/978-81-322-2523-2_46
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Publisher Name: Springer, New Delhi
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