Wavelet Package Denoising of Acoustic Emission Signals for Lubrication Oil Monitoring in Engine Systems

Nasha Wei, Zhi Chen, Fengshou Gu, Andrew D. Ball

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Lubricating oil quality deterioration or insufficient lubrication level will cause excessive wear of the piston-cylinder liner system, which will severely reduce the engine life and the sealing of the combustion chamber. Acoustic emission (AE) signals generated during the friction-lubrication process of the piston ring-cylinder system are unsteady weak signals under strong background noise that is difficult to extract and analyze. This work presents an oil condition monitoring approach based on optimal wavelet analysis of acoustic emissions. AE signals measured on engine body consist of rich information of engine operations, which includes not only lubrication conditions but also large AE impulses of valve impacts, fuel injections, and combustions. Wavelet packets based angle-frequency analysis enhances these impulsive AEs, thereby making it easy to exclude these impulses. This then results in residual AEs with more continuous AE spikes in the middle of a stroke for indicating lubrication conditions. In particular, a novel WP threshold denoising method based on an AE model of fluid-asperity shearing interaction is proposed to remove the large impulses. Experimental studies are conducted based on a four-stroke diesel operating with three popular engine lube-oils: 0W20, 10W30, and 15W40 in turn. These oils have subtle differences in tribo-properties (mainly viscosity values) and induce different AE signals. Applying the WP threshold denoising to AE signals allows optimal signatures to be selected so that these three types of oils can be separated under a wide range of operating conditions. This shows that AE is capable of detecting difference from used oils which usually has large changes in viscosity. Also, it proves the effectiveness of the WP-based denoising method.

Original languageEnglish
Title of host publicationProceedings of IncoME-V & CEPE Net-2020
Subtitle of host publicationCondition Monitoring, Plant Maintenance and Reliability
EditorsDong Zhen, Dong Wang, Tianyang Wang, Hongjun Wang, Baoshan Huang, Jyoti K. Sinha, Andrew David Ball
Place of PublicationCham
PublisherSpringer Nature Switzerland AG
Pages69-80
Number of pages12
Volume105
Edition1st
ISBN (Electronic)9783030757939
ISBN (Print)9783030757922
DOIs
Publication statusPublished - 16 May 2021
Event5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network - Zhuhai, China
Duration: 23 Oct 202025 Oct 2020
Conference number: 5
https://link.springer.com/book/10.1007/978-3-030-75793-9#about

Publication series

NameMechanisms and Machine Science
Volume105
ISSN (Print)2211-0984
ISSN (Electronic)2211-0992

Conference

Conference5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network
Abbreviated titleIncoME-V and CEPE Net-2020
CountryChina
CityZhuhai
Period23/10/2025/10/20
Internet address

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