Smart condition monitoring by intergration of vibration, oil and wear particle analysis

Ebersbach, Stephan, Peng, Zhongxiao, and Kessissoglou, Nicole (2007) Smart condition monitoring by intergration of vibration, oil and wear particle analysis. In: Proceedings of the 14th International Congress on Sound and Vibration 2007, pp. 1-9. From: 14th International Congress on Sound and Vibration, 9-12 July 2007, Cairns, Qld, Australia.

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Abstract

Vibration, oil and wear particle analyses typically represent the core techniques used for machine condition monitoring. While these techniques have been incorporated in many maintenance programs found throughout industry, the results of each analysis are generally considered independently for machine health assessment. Due to the complexity of condition monitoring and the lack of a successful correlation algorithm, the potential benefits of an integrated condition monitoring program have not been realised. This paper outlines the development stages of an expert system designed to perform automated machine condition monitoring of gearbox and associated components faults, by using a correlation algorithm to combine the results obtained from vibration, oil and wear particle analysis. The design aspects of the correlation algorithm are presented in detail, including an analysis of the detection abilities of the three condition monitoring techniques. The development also included a rigorous testing phase which included the verification of all implemented reasoning logic, as well as analysis of laboratory and industry derived data. Some testing results are also discussed, outlining the fault identification ability of the algorithm for typically encountered gearbox faults. The analysis of machine condition data by a correlated approach of vibration, oil and wear particle analysis has a number of benefits compared to conventional condition monitoring practices. These include accurate, efficient and early fault detection of gearbox and bearing faults, as well as the ability to perform root-cause analysis. The automated analysis algorithm permits non-expert personnel to perform routine comprehensive machine condition monitoring, while providing a consistent objective analysis of the machine health.

Item ID: 3124
Item Type: Conference Item (Refereed Research Paper - E1)
Keywords: gearbox; vibration analysis; wear analysis; wear debris analysis; machine condition monitoring
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ISBN: 978-0-7334-2516-5
Date Deposited: 22 Oct 2009 03:12
FoR Codes: 09 ENGINEERING > 0913 Mechanical Engineering > 091399 Mechanical Engineering not elsewhere classified @ 100%
SEO Codes: 86 MANUFACTURING > 8614 Machinery and Equipment > 861404 Mining Machinery and Equipment @ 60%
86 MANUFACTURING > 8614 Machinery and Equipment > 861401 Agricultural Machinery and Equipment @ 30%
86 MANUFACTURING > 8614 Machinery and Equipment > 861403 Industrial Machinery and Equipment @ 10%
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