Condition Monitoring of Lubricant Shortage for Gearboxes Based on Compressed Thermal Images

Xiaoli Tang, Ke Li, Pieter A. van Vuuren, Junfeng Guo, Funso Otuyemi, Fengshou Gu, Andrew D. Ball

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

Abstract

Condition monitoring of gearboxes is a crucial task because gearboxes are essential power transmission components whose failure can lead to a catastrophic breakdown of machines. The common faults of a gearbox system, such as tooth breakage, wear, scuffing, spalling and lubricant starvation, have a significant influence on the inside friction and heat dissipation, and consequently, it changes the temperature field distribution within the gearbox. Thermal imaging is a promising technique in the field of machine condition monitoring via the variation detection of heat distribution. However, the thermal images require significant storage space, a high transfer rate and high-speed hardware. To achieve intelligent and efficient machine condition monitoring with the advanced thermal imaging technique, this study reduces the dimensionality of thermal images of a two-stage gearbox system via compressive sensing (CS) and classifies three different lubricant shortage conditions based on the compressed features with an intelligent convolutional neural network (CNN). The experimental results demonstrate that the compressed thermal images contain sufficient fault information and are capable of diagnosing the inadequate lubrication faults for gearboxes operating at various working conditions.

Original languageEnglish
Title of host publicationAdvances in Asset Management and Condition Monitoring, COMADEM 2019
EditorsAndrew Ball, Len Gelman, B.K.N. Rao
PublisherSpringer, Cham
Pages927-938
Number of pages12
Volume166
ISBN (Electronic)9783030577452
ISBN (Print)9783030577445
DOIs
Publication statusPublished - 28 Aug 2020
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)

Publication series

NameSmart Innovation, Systems and Technologies
PublisherSpringer
Volume166
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

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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