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Advances in Mechanical Engineering
Volume 2012 (2012), Article ID 518468, 8 pages
Research Article

Fault Severity Estimation of Rotating Machinery Based on Residual Signals

School of Mechanical Engineering, China University of Mining and Technology, Xuzhou 221116, China

Received 29 July 2012; Accepted 17 September 2012

Academic Editor: C. S. Shin

Copyright © 2012 Fan Jiang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Fault severity estimation is an important part of a condition-based maintenance system, which can monitor the performance of an operation machine and enhance its level of safety. In this paper, a novel method based on statistical property and residual signals is developed for estimating the fault severity of rotating machinery. The fast Fourier transformation (FFT) is applied to extract the so-called multifrequency-band energy (MFBE) from the vibration signals of rotating machinery with different fault severity levels in the first stage. Usually these features of the working conditions with different fault sensitivities are different. Therefore a sensitive features-selecting algorithm is defined to construct the feature matrix and calculate the statistic parameter (mean) in the second stage. In the last stage, the residual signals computed by the zero space vector are used to estimate the fault severity. Simulation and experimental results reveal that the proposed method based on statistics and residual signals is effective and feasible for estimating the severity of a rotating machine fault.