Fault Diagnosis of Reciprocating Compressor Using Empirical Mode Decomposition-Based Teager Energy Spectrum of Airborne Acoustic Signal

Debanjan Mondal, Dong Zhen, Fengshou Gu, Andrew Ball

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Due to the presence of several rotating and reciprocating components, the acoustic signal obtained from the compressor normally involves transient impact and noise. The nonlinear and non-stationary response also contribute to the corruption of the useful information and lead to the diagnosing difficulty using the traditional methods. Due to the high nonstationary characteristic, time-frequency domain analysis can be a good choice for processing the airborne signal. In this paper, a new method based on empirical mode decomposition (EMD) and the Teager energy operator (TEO) is proposed to extract the fault features from the airborne acoustic signal for the reciprocating compressor fault diagnosis. The very unique advantage of TEO in detecting the transient response from a signals is exploited, and be applied to track the total mechanical energy that is responsible for generating the acoustic signal. Firstly, the signal is decomposed in the monocomponents by using EMD to satisfy the monocomponent criterion of the Teager energy operator. Next, the appropriate intrinsic mode function (IMF) is selected based on the correlation coefficient for obtaining the instantaneous energy by TEO. Finally, the spectrum analysis is done on the energy series for identifying the repeating frequency of the periodic impulses and thereby to diagnose the induced compressor faults under broad range of discharge pressures. The proposed method was also compared with the existing state of the art techniques like Hilbert energy spectrum and traditional spectral analysis. The comparison study shows the effectiveness of the proposed method over the existing methods in diagnosis of reciprocating compressor faults based on airborne acoustic signal analysis.
Original languageEnglish
Title of host publicationProceedings of COMADEM
Subtitle of host publication32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management: COMADEM 2019
PublisherSpringer
Publication statusAccepted/In press - 24 Jun 2019
Event32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference - University of Huddersfield, Huddersfield, United Kingdom
Duration: 3 Sep 20195 Sep 2019
Conference number: 32
http://www.comadem2019.com/ (Link to Conference Website)

Conference

Conference32nd International Congress and Exhibition on Conditioning Monitoring and Diagnostic Engineering Management Conference
Abbreviated titleCOMADEM 2019
CountryUnited Kingdom
CityHuddersfield
Period3/09/195/09/19
Internet address

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  • Cite this

    Mondal, D., Zhen, D., Gu, F., & Ball, A. (Accepted/In press). Fault Diagnosis of Reciprocating Compressor Using Empirical Mode Decomposition-Based Teager Energy Spectrum of Airborne Acoustic Signal. In Proceedings of COMADEM: 32nd International Congress and Exhibition on Condition Monitoring and Diagnostic Engineering Management: COMADEM 2019 Springer.