A Method for Automated Cavitation Detection with Adaptive Thresholds

Seth W. Gregg, John P.H. Steele, and Douglas L. Van Bossuyt
Publication Target: 
IJPHM
Publication Issue: 
1
Submission Type: 
Full Paper
Supporting Agencies (optional): 
The information, data, or work presented herein was funded in part by the Office of Energy Efficiency and Renewable En-ergy (EERE), U.S. Department of Energy, under Award Number DE-EE0002668 and the Hydro Research Foundation.
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ijphm_18_005.pdf617.29 KBFebruary 7, 2018 - 10:39am

Hydroturbine operators who wish to collect cavitation intensity data to estimate cavitation erosion rates and calculate remaining useful life (RUL) of the turbine runner face several practical challenges related to long term cavitation detection. This paper presents a novel method that addresses these challenges including: a method to create an adaptive cavitation threshold, and automation of the cavitation detection process. These two strategies result in collecting consistent cavitation intensity data. While domain knowledge and manual interpretation are used to choose an appropriate cavitation sensitivity parameter (CSP), the remainder of the process is automated using both supervised and unsupervised learning methods. A case study based on ramp-down data, taken from a production hydroturbine, is presented and validated using independently gathered survey data from the same hydroturbine. Results indicate that this fully automated process for selecting cavitation thresholds and classifying cavitation performs well when compared to manually selected thresholds. This approach provides hydroturbine operators and researchers with a clear and effective way to perform automated, long term, cavitation detection, and assessment.

Publication Year: 
2018
Publication Volume: 
9
Publication Control Number: 
005
Page Count: 
18
Submission Keywords: 
Hydroturbine
Hydropower
Cavitation
Mahalanobis
health monitoring
Submission Topic Areas: 
Health management system design and engineering
Industrial applications
Submitted by: 
  
 
 
 

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