Wavelet Packet Analysis and Empirical Mode Decomposition for the Fault Diagnosis of Reciprocating Compressors

Ugonnaya Muo; Misan Madamedon; Andrew Ball; Fengshou Gu

doi:10.23919/IConAC.2017.8082065

Wavelet Packet Analysis and Empirical Mode Decomposition for the Fault Diagnosis of Reciprocating Compressors

Ugonnaya Muo, Misan Madamedon, Andrew Ball, Fengshou Gu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Citations (Scopus)

Abstract

This paper investigates the use of advance signal processing techniques for the classification of four common reciprocating compressor conditions. Non-stationary vibration signals from the compressor are decomposed based on two emerging techniques: WPT (Wavelet Packet Transform) and EMD (Empirical Mode Decomposition) and harmonic changes of the optimal components of each technique are used for condition monitoring and diagnostics of the machine. Performance comparison of WPT and EMD is done for the envelope analysis of the optimal wavelet packet and the IMF (Intrinsic Mode Function) component that can extract salient features of the four compressor conditions including one normal and three fault conditions (intercooler leakage, discharge valve leakage and the combination of intercooler and discharge valve leakage). Harmonic changes produced after envelope analysis of the best packet and IMF component are used for classification and results show that WPT technique is more robust and effective in fault classification compared to EMD.

Original language	English
Title of host publication	Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	7
ISBN (Electronic)	9780701702601
ISBN (Print)	9781509050406
DOIs	https://doi.org/10.23919/IConAC.2017.8082065
Publication status	Published - 26 Oct 2017
Event	23rd International Conference on Automation and Computing: Addressing Global Challenges through Automation and Computing - University of Huddersfield, Huddersfield, United Kingdom Duration: 7 Sep 2017 → 8 Sep 2017 Conference number: 23 https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042 (Link to Conference Website)

Conference

Conference	23rd International Conference on Automation and Computing
Abbreviated title	ICAC 2017
Country/Territory	United Kingdom
City	Huddersfield
Period	7/09/17 → 8/09/17
Other	The scope of the conference covers a broad spectrum of areas with multi-disciplinary interests in the fields of automation, control engineering, computing and information systems, ranging from fundamental research to real-world applications.
Internet address	https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042 (Link to Conference Website)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.23919/IConAC.2017.8082065Licence: Unspecified

http://eprints.hud.ac.uk/id/eprint/33645Licence: Unspecified

Cite this

Muo, U., Madamedon, M., Ball, A., & Gu, F. (2017). Wavelet Packet Analysis and Empirical Mode Decomposition for the Fault Diagnosis of Reciprocating Compressors. In Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017) Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/IConAC.2017.8082065

@inproceedings{441c55a586dc447eb5d86564cce8f850,

title = "Wavelet Packet Analysis and Empirical Mode Decomposition for the Fault Diagnosis of Reciprocating Compressors",

abstract = "This paper investigates the use of advance signal processing techniques for the classification of four common reciprocating compressor conditions. Non-stationary vibration signals from the compressor are decomposed based on two emerging techniques: WPT (Wavelet Packet Transform) and EMD (Empirical Mode Decomposition) and harmonic changes of the optimal components of each technique are used for condition monitoring and diagnostics of the machine. Performance comparison of WPT and EMD is done for the envelope analysis of the optimal wavelet packet and the IMF (Intrinsic Mode Function) component that can extract salient features of the four compressor conditions including one normal and three fault conditions (intercooler leakage, discharge valve leakage and the combination of intercooler and discharge valve leakage). Harmonic changes produced after envelope analysis of the best packet and IMF component are used for classification and results show that WPT technique is more robust and effective in fault classification compared to EMD.",

keywords = "Condition monitoring, Wavelet packet transform, Vibration analysis, Empirical mode decomposition, Fault diagnosis",

author = "Ugonnaya Muo and Misan Madamedon and Andrew Ball and Fengshou Gu",

year = "2017",

month = oct,

day = "26",

doi = "10.23919/IConAC.2017.8082065",

language = "English",

isbn = "9781509050406",

booktitle = "Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "23rd International Conference on Automation and Computing : Addressing Global Challenges through Automation and Computing, ICAC 2017 ; Conference date: 07-09-2017 Through 08-09-2017",

url = "https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042",

}

Muo, U, Madamedon, M, Ball, A & Gu, F 2017, Wavelet Packet Analysis and Empirical Mode Decomposition for the Fault Diagnosis of Reciprocating Compressors. in Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc., 23rd International Conference on Automation and Computing, Huddersfield, United Kingdom, 7/09/17. https://doi.org/10.23919/IConAC.2017.8082065

Wavelet Packet Analysis and Empirical Mode Decomposition for the Fault Diagnosis of Reciprocating Compressors. / Muo, Ugonnaya; Madamedon, Misan; Ball, Andrew et al.

Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017). Institute of Electrical and Electronics Engineers Inc., 2017.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Wavelet Packet Analysis and Empirical Mode Decomposition for the Fault Diagnosis of Reciprocating Compressors

AU - Muo, Ugonnaya

AU - Madamedon, Misan

AU - Ball, Andrew

AU - Gu, Fengshou

N1 - Conference code: 23

PY - 2017/10/26

Y1 - 2017/10/26

N2 - This paper investigates the use of advance signal processing techniques for the classification of four common reciprocating compressor conditions. Non-stationary vibration signals from the compressor are decomposed based on two emerging techniques: WPT (Wavelet Packet Transform) and EMD (Empirical Mode Decomposition) and harmonic changes of the optimal components of each technique are used for condition monitoring and diagnostics of the machine. Performance comparison of WPT and EMD is done for the envelope analysis of the optimal wavelet packet and the IMF (Intrinsic Mode Function) component that can extract salient features of the four compressor conditions including one normal and three fault conditions (intercooler leakage, discharge valve leakage and the combination of intercooler and discharge valve leakage). Harmonic changes produced after envelope analysis of the best packet and IMF component are used for classification and results show that WPT technique is more robust and effective in fault classification compared to EMD.

AB - This paper investigates the use of advance signal processing techniques for the classification of four common reciprocating compressor conditions. Non-stationary vibration signals from the compressor are decomposed based on two emerging techniques: WPT (Wavelet Packet Transform) and EMD (Empirical Mode Decomposition) and harmonic changes of the optimal components of each technique are used for condition monitoring and diagnostics of the machine. Performance comparison of WPT and EMD is done for the envelope analysis of the optimal wavelet packet and the IMF (Intrinsic Mode Function) component that can extract salient features of the four compressor conditions including one normal and three fault conditions (intercooler leakage, discharge valve leakage and the combination of intercooler and discharge valve leakage). Harmonic changes produced after envelope analysis of the best packet and IMF component are used for classification and results show that WPT technique is more robust and effective in fault classification compared to EMD.

KW - Condition monitoring

KW - Wavelet packet transform

KW - Vibration analysis

KW - Empirical mode decomposition

KW - Fault diagnosis

UR - http://www.scopus.com/inward/record.url?scp=85040003172&partnerID=8YFLogxK

U2 - 10.23919/IConAC.2017.8082065

DO - 10.23919/IConAC.2017.8082065

M3 - Conference contribution

SN - 9781509050406

BT - Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 23rd International Conference on Automation and Computing

Y2 - 7 September 2017 through 8 September 2017

ER -

Wavelet Packet Analysis and Empirical Mode Decomposition for the Fault Diagnosis of Reciprocating Compressors

Abstract

Conference

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this