Survey of Condition Indicators for Condition Monitoring Systems

Junda Zhu, Tom Nostrand, Cody Spiegel, and Brogan Morton
Submission Type: 
Full Paper
phmc_14_065.pdf837.3 KBSeptember 2, 2014 - 4:43pm

Currently, the wind energy industry is swiftly changing its maintenance strategy from schedule based maintenance to predictive based maintenance. Condition monitoring systems (CMS) play an important role in the predictive maintenance cycle. As condition monitoring systems are being adopted by more and more OEM and O&M service providers from the wind energy industry, it is crucial to effectively interpret the data generated by the CMS and initiate proactive processes to efficiently reduce the risk of potential component or system failure which often leads to down tower repair or gearbox replacement.,. The majority of CMS are designed and constructed based on vibration analysis which has been refined over the years by researchers and scientists. This paper provides a detailed description and mathematical interpretation of a comprehensive selection of condition indicators for gears, bearings and shafts. Since different condition indicators are sensitive to different kind of failure modes, the application for each condition indicators are also discussed. The Time Synchronous Averaging (TSA) algorithm is applied as the signal processing method before the extraction of condition indicators. Several case studies of real world wind turbine component failure detection using condition indicators are presented to demonstrate the effectiveness of certain condition indicators.

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Submission Keywords: 
Condition monitoring system
Condition Indicator
case study
Submission Topic Areas: 
Health management system design and engineering
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