Abstract
Vibration signals measured from a mechanical system are useful to detect system faults. Signal processing has been used to extract fault information in bearing systems. However, a wide vibration signal frequency band often affects the ability to obtain the effective fault features. In addition, a few oscillation components are not useful at the entire frequency band in a vibration signal. By contrast, useful fatigue information can be embedded in the noise oscillation components. Thus, a method to estimate which frequency band contains fault information utilizing group delay was proposed in this paper. Group delay as a measure of phase distortion can indicate the phase structure relationship in the frequency domain between original (with noise) and denoising signals. We used the empirical mode decomposition of a Hilbert-Huang transform to sift the useful intrinsic mode functions based on the results of group delay after determining the valuable frequency band. Finally, envelope analysis and the energy distribution after the Hilbert transform were used to complete the fault diagnosis. The practical bearing fault data, which were divided into inner and outer race faults, were used to verify the efficiency and quality of the proposed method.
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Shuai Jin is a graduate student of the Department of Mechanical Engineering at Inha University. He has studied signal processing and health monitoring. To date, he is working at Hyundai Motor Institute in China.
Sang-Kwon Lee was born in Pusan, Korea in 1959. He studied Mechanical Engineering at Pusan National University, Pusan, Korea with a bachelor’s degree. He received his Ph.D. in 1998 with a degree in signal processing at the Institute of Sound and Vibration Research of Southampton University in UK. He has 11 years of working experience in automotive noise control at Hyundai Motor Company and Renault Samsung Motor Company in Korea. He moved to Inha University, Inchon, Korea in 1999. He is continuing the sound and vibration research at the Department of Mechanical Engineering, Inha University.
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Jin, S., Lee, SK. Bearing fault detection utilizing group delay and the Hilbert-Huang transform. J Mech Sci Technol 31, 1089–1096 (2017). https://doi.org/10.1007/s12206-017-0208-z
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DOI: https://doi.org/10.1007/s12206-017-0208-z