Health Indices Based on Morphology and Complexity Measures of Vibration Signals for Machine Condition Monitoring and Prognostics



Published Mar 26, 2021
Samanta biswanath C. Nataraj


The paper presents health indices (HI) for monitoring and prognostics of machine condition. HI are developed using morphology and entropy based complexity measures of machine vibration signals. The indices are compared with a recently introduced energy based feature and the commonly used statistical measure of signal kurtosis. The procedure of extracting HI is illustrated first using the simulated response of a simple gear model with tooth crack. Next the HI extraction process is applied to the experimental vibration data of a helicopter drivetrain gearbox with a seeded tooth fault. The effectiveness of the extracted HI is compared for gear condition monitoring and prognostics.

How to Cite

biswanath, S., & Nataraj, C. (2021). Health Indices Based on Morphology and Complexity Measures of Vibration Signals for Machine Condition Monitoring and Prognostics. Annual Conference of the PHM Society, 1(1). Retrieved from
Abstract 162 | PDF Downloads 145



classification, gears, helicopters, applications: helicopter

(Al-Balushi and Samanta, 2002) K. R. Al-Balushi and B. Samanta. Gear fault diagnosis using energybased features of acoustic emission signals, Proceedings of IMechE, Part I: Journal of Systems and Control Engineering, vol. 216, pp. 249-263, 2002.

(Choi and Li, 2006) S. Choi and C. J. Li X. Estimation of gear tooth transverse crack size from vibration fusing selected gear condition indices, Measurement Science and Technology, vol. 17, pp. 2395-2400, 2006.

(Costa et al., 2005) M. Costa, A. L. Goldberger, and C.K. Peng. Multiscale entropy analysis of biological signals, Physics Review, vol.71, paper id:021906, 2005.

(Hardman et al., 1999) W. Hardman, A. Hess, and J. Sheaffer. SH-60 helicopter integrated diagnostic system (HIDS) program- diagnostic and prognostic development experience, in Proceedings of IEEE Aerospace Conference, Aspen, CO, USA, March 613, pp. 473-491, 1999.

(He and Bechhoefer, 2008) D. He and E. Bechhoefer. Development and validation of bearing diagnostic and prognostic tools using HUMS condition indicators, in Proceedings of 2008 IEEE Aerospace Conference, Big Sky, MT, 2008.

(Heng et al., 2009) A. Heng, S. Zhang, A. C. C. Tan, and J. Mathew. Rotating machinery prognostics: state of the art, challenges and opportunities, Mechanical Systems and Signal processing, vol. 23, pp.724-739, 2009.

(Henry et al., 2002) B. Henry, N. Lovell, and F. Camacho. Nonlinear dynamics time series analysis. In Nonlinear Biomedical Signal Processing, Vol. 2, Dynamic Analysis and Modeling, Metin Akay (Ed.), ISBN: 9780780360129, 2002.

(Hochmann and Bechhoefer, 2003) D. Hochmann and E. Bechhoefer. Gear tooth crack signals and their detection via the FM4 measure in application for a helicopter HUMS (health usage and management systems), in Proceedings of 2003 IEEE Aerospace Conference, Big Sky, MT, pp. 3313-3326, 2003. (Janjarasjitt et al., 2008) S. Janjarasjitt, H. Oack and K.

A. Loparo. Bearing condition diagnosis and prognosis using applied nonlinear dynamical analysis of machine vibration signal, Journal of Sound and Vibration, vol. 317, pp. 112-126, 2008.

(Jardine et al., 2006) A. K. S. Jardine, D. Lin, and D. Banjevic. A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mechanical Systems and Signal Processing, vol. 20, pp.1483-1510, 2006. (Jia et al., 2006) W. Jia, R. J. Sclabassi, L.-S. Pon, M.

L. Scheuer, and M. Sun. Spkie separation from EEG/EMG data using morphological filter and wavelet transform. Proceedings of 28 th IEEE EMBS Annual International Conference, New York, NY, pp. 6137-6140, 2006.

(Li et al., 2008) X. Li, G. Ouyang and Z. Liang. Complexity measure of motor current signals for tool flute breakage detection in end milling, International Journal of Machine Tools and Manufacture, vol. 48, pp. 371-379, 2008.

(Maragos and Scafer, 1987) P. Maragos and R. Schafer. Morphological filters-part I: their set-theoretic analysis and relations to linear shift-invariant filters, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 35, pp.1153- 1169, 1987.

(Maragos, 1989a) P. Maragos. A representation theory for morphological image and signal processing, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, pp. 586-599, 1989.

(Maragos, 1989b) P. Maragos. Pattern spectrum and multiscale shape representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, pp. 701-716, 1989.

(Nikolaou and Antoniadis, 2003) N. G. Nikolaou and I.A. Antoniadis. Application of morphological operators as envelope extractors for impulsive-type periodic signals, Mechanical Systems and Signal Processing, vol. 17, pp. 1147-1162, 2003.

(Pincus, 1991) S. M. Pincus. Approximate entropy as a measure of system complexity, Proc Natl Acad Sci USA, vol.88, pp. 2297-2301, 1991.

(Richman and Moorman, 2000) J. S. Richman and J.R. Moorman. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol vol.278, pp.2039-2049, 2000.

(Samanta, 2004) Samanta, B. Gear fault detection using artificial neural networks and support vector machines with genetic algorithms. Mechanical Systems and Signal Processing, vol. 18, pp. 625644, 2004.

(Samanta and Nataraj, 2008a) B. Samanta and C.Nataraj. Prognostics of machine condition using soft computing, Robotics and Computer-Integrated Manufacturing, vol. 24, pp. 816-823, 2008.

(Samanta and Nataraj, 2008b) B. Samanta and C.Nataraj. Prognostics using morphological signal processing and computational intelligence, in Proceedings of 1 st IEEE intl. Conf. PHM2008, Denver, CO, 2008.

(Samanta and Nataraj, 2009a) B. Samanta and C.Nataraj. Use of particle swarm optimization for machinery fault detection. Engineering Applications of Artificial Intelligence, vol. 22, pp. 308-316, 2009.

(Samanta and Nataraj, 2009b) B. Samanta and C. Nataraj. Prognostics of machine condition using energy based monitoring index and computational intelligence, Transactions of ASME, Journal of Computing and Information Science in Engineering, paper# JCISE 2008-55 (in press), 2009.

(Smith, 2003) J. D. Smith.. Gear Vibration and Noise, 2 nd Edn., Mercel Dekker, New York, 2003.

(Sun et al., 2003) P. Sun, Q. H. Wu and A. M.Weindling, A. Finkelstein, and K. Ibrahim. An improved morphological approach to background normalization of ECG signals, IEEE Transactions on Biomedical Engineering, vol. 50, pp. 117-121,
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