Trends in non-stationary signal processing techniques applied to vibration analysis of wind turbine drive train – A contemporary survey. (15th February 2017)

• Record Type: Journal Article
• Authors: Uma Maheswari, R.; Umamaheswari, R.
• Is Part Of: Mechanical systems and signal processing. Volume 85(2017)
• Page Start: 296
• Page End: 311
• Publication Date: 2017-02-15
• Subjects: Vibration analysis -- Condition monitoring -- Fault diagnosis -- Drive trains -- Non-stationary signal processing -- Time frequency analysis; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2016.07.046
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: Condition Monitoring System (CMS) substantiates potential economic benefits and enables prognostic maintenance in wind turbine-generator failure prevention. Vibration Monitoring and Analysis is a powerful tool in drive train CMS, which enables the early detection of impending failure/damage. In variable speed drives such as wind turbine-generator drive trains, the vibration signal acquired is of non-stationary and non-linear. The traditional stationary signal processing techniques are inefficient to diagnose the machine faults in time varying conditions. The current research trend in CMS for drive-train focuses on developing/improving non-linear, non-stationary feature extraction and fault classification algorithms to improve fault detection/prediction sensitivity and selectivity and thereby reducing the misdetection and false alarm rates. In literature, review of stationary signal processing algorithms employed in vibration analysis is done at great extent. In this paper, an attempt is made to review the recent research advances in non-linear non-stationary signal processing algorithms particularly suited for variable speed wind turbines. Highlights: Captures Recent Adavancements in Wind turbine Condition Monitoring. Surveys the Morden Non Stationary Signal Processing Techniques. Describes the data driven and model based signal processing trends. Gives overall picture about the nonstationary signal processing algorithms used in Wind Turbines.