Fault Diagnostics of Planet Gears in Wind Turbine Using Autocorrelation-Based Time Synchronous Averaging (ATSA)

Jong Moon Ha, Jungho Park, Byeng D. Youn, and Yoong Ho Jung
Submission Type: 
Full Paper
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phmce_14_056.pdf3.89 MBMay 30, 2014 - 1:32am

A planetary gearbox is widely used in various rotating systems because it can be used as a speed reducer or increaser without change in direction of shaft while transferring great driving power. Despite many attempts it is still challenging to diagnose potential faults of the planetary gearbox because of multiple contacts and axis rotation of planet gears resulting in complex vibration characteristics. This paper thus presents an original method to isolate vibration signals induced by the planet gears from the complex vibration signals for fault diagnostics of the planetary gearbox. First, an in-depth study on the vibration characteristics of planet gears is presented using the autocorrelation function of the vibration signal. The autocorrelation-based time synchronous averaging (ATSA) method is then developed for the isolation of the vibration signals produced by the planet gears. The vibration signals were utilized for extracting health related data which facilitate the efficient fault diagnostics of the planet gears. Case study with a wind turbine testbed showed that the proposed method can diagnose the root crack of the planet gears.

Publication Year: 
2014
Publication Volume: 
5
Publication Control Number: 
056
Page Count: 
8
Submission Keywords: 
Wind Turbine
fault diagnostics
Planetary gearbox
Time Synchronous Averaging (TSA).
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
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