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A Study of Diagnosing Reciprocating Compressor Faults using EMD-entropy of the Airborne Acoustic Signals

Mondal, Debanjan, Sun, Xiuquan, Gu, Fengshou and Ball, Andrew (2018) A Study of Diagnosing Reciprocating Compressor Faults using EMD-entropy of the Airborne Acoustic Signals. In: Proceedings of 3rd International Conference on Maintenance Engineering. ShieldCrest Publishing, Coimbra, Portugal, pp. 293-307. ISBN 978-989-8200-17-4

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For more effectively and less-costly monitoring of reciprocating compressors, this paper focuses on the developing of a new monitoring method based on airborne sounds which can be easily obtained in and remote way and contains richer information of an entire machine. Possible sound sources of the compressor have been examined according to the working process of mechanical motions and fluid dynamics in order to understand the sound characteristics under different operating conditions. Especially, the sound signal from the compressor is highly non-stationary due to the periodic excitation resulted by the combined effect of gas dynamics and the mechanical forces acting on the compressor associated with the random disturbances of valve motions and flow turbulence and the variations of discharge pressures. In addition, the acoustic signals are also veritably influenced by background noises which often are of unsteady. To characterise such signals for fault detection and diagnosis, Empirical Mode Decomposition (EMD), an effective tool for non-stationary signal analysis, is used to find and enhance the inherent information that correlates more to the various acoustic events involved in compressor operations. Experimental studies, carried out based on a two-stage reciprocating compressor, have shown that Intrinsic Mode Functions (IFM) from EMD can depict more of the signals to indicate the conditions of the machine. In particular, using EMD- entropy as a diagnostic parameter allows common faults such as inter-cooler leakage (ICL) and discharge valve leakage (DVL) to be discriminated and separated from the baseline operation over a wider range of discharge pressures, demonstrating that the proposed EMD acoustic signatures can be an effective approach for monitoring reciprocating machines.

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Item Type: Book Chapter
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
References: [1] Elhaj, M., Gu, F., Ball, A.D., Albarbar, A., Al-Qattan, M. and Naid, A., 2008. Numerical simulation and experimental study of a two-stage reciprocating compressor for condition monitoring. Mechanical Systems and Signal Processing, 22(2), pp.374-389. [2] Toprak, S. and Iftar, A., 2007, October. Fault Diagnosis on Hermetic Compressors Based on Sound Measurements. In Control Applications, 2007. CCA 2007. IEEE International Conference on (pp. 783-788). IEEE. [3] Elhaj, M., Gu, F., Shi. J., and Ball. A. (2001). Early Detection of Leakage in Reciprocating Compressor Valves using Vibration and Acoustic Continuous Wavelet Features. Proc. 14th Int. COMADEM Conference, Manchester University, pp 749 -756. [4] Lowson, M.V., 1970. Theoretical analysis of compressor noise. The Journal of the Acoustical Society of America, 47(1B), pp.371-385. [5] Ball, A.D., Gu, F. and Li, W., 2000. The condition monitoring of diesel engines using acoustic measurements part 2: fault detection and diagnosis (No. 2000-01-0368). SAE Technical Paper. [6] Wu, Z. and Huang, N.E., 2004, June. A study of the characteristics of white noise using the empirical mode decomposition method. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences(Vol. 460, No. 2046, pp. 1597-1611). The Royal Society. [7] Su, W.S., Wang, F.T., Zhang, Z.X., Guo, Z.G. and Li, H.K., 2010. Application of EMD denoising and spectral kurtosis in early fault diagnosis of rolling element bearings. Zhendong yu Chongji(Journal of Vibration and Shock), 29(3), pp.18-21. [8] Wu, F. and Qu, L., 2009. Diagnosis of subharmonic faults of large rotating machinery based on EMD. Mechanical Systems and Signal Processing, 23(2), pp.467-475. [9] Zhang, C., Chen, J.J. and Guo, X., 2010. A gear fault diagnosis method based on EMD energy entropy and SVM. Zhendong yu Chongji(Journal of Vibration and Shock), 29(10), pp.216-220. [10] Huang, J., Hu, X. and Geng, X., 2011. An intelligent fault diagnosis method of high voltage circuit breaker based on improved EMD energy entropy and multi-class support vector machine. Electric Power Systems Research, 81(2), pp.400-407. [11] Cui, H., Zhang, L., Kang, R. and Lan, X., 2009. Research on fault diagnosis for reciprocating compressor valve using information entropy and SVM method. Journal of loss prevention in the process industries, 22(6), pp.864-867. [12] Copco, A. (2018). What is Sound? - AtlasCopco. [online] Atlas Copco. Available at: [Accessed 23 May 2018]. [13] Hansen, C.H., 2001. Fundamentals of acoustics. Occupational Exposure to Noise: Evaluation, Prevention and Control. World Health Organisation, pp.23-52. [14] Verma, N.K., Kadambari, J., Abhijit, B., Tanu, S. and Salour, A., 2011, September. Finding sensitive sensor positions under faulty condition of reciprocating air compressors. In Recent Advances in Intelligent Computational Systems (RAICS), 2011 IEEE (pp. 242-246). IEEE.
Depositing User: Debanjan Mondal
Date Deposited: 23 May 2019 09:56
Last Modified: 23 May 2019 09:56


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