Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88423
Title: Integrated condition monitoring and prognosis method for incipient defect detection and remaining life prediction of low speed slew bearings
Authors: Caesarendra, Wahyu
Tjahjowidodo, Tegoeh
Kosasih, Buyung
Tieu, Anh Kiet
Keywords: DRNTU::Engineering::Mechanical engineering
Condition Monitoring
Kernel Regression
Issue Date: 2017
Source: Caesarendra, W., Tjahjowidodo, T., Kosasih, B., & Tieu, A. K. (2017). Integrated condition monitoring and prognosis method for incipient defect detection and remaining life prediction of low speed slew bearings. Machines, 5(2), 11-. doi:10.3390/machines5020011
Series/Report no.: Machines
Abstract: This paper presents an application of multivariate state estimation technique (MSET), sequential probability ratio test (SPRT) and kernel regression for low speed slew bearing condition monitoring and prognosis. The method is applied in two steps. Step (1) is the detection of the incipient slew bearing defect. In this step, combined MSET and SPRT is used with circular-domain kurtosis, time-domain kurtosis, wavelet decomposition (WD) kurtosis, empirical mode decomposition (EMD) kurtosis and the largest Lyapunov exponent (LLE) feature. Step (2) is the prediction of the selected features’ trends and the estimation of the remaining useful life (RUL) of the slew bearing. In this step, kernel regression is used with time-domain kurtosis, WD kurtosis and the LLE feature. The application of the method is demonstrated with laboratory slew bearing acceleration data.
URI: https://hdl.handle.net/10356/88423
http://hdl.handle.net/10220/45773
ISSN: 2075-1702
DOI: http://dx.doi.org/10.3390/machines5020011
Rights: © 2017 by The Author(s). Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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