Industrial Big Data Pipeline for Wind Turbine PHM in a Large Manufacturing Facility

Kevin Leahy, Colm Gallagher, Peter O'Donovan, and Dominic T.J. O'Sullivan
Publication Target: 
IJPHM
Publication Issue: 
1
Submission Type: 
Technical Brief
AttachmentSizeTimestamp
ijphm_19_017.pdf267.16 KBAugust 3, 2019 - 10:18am

Wind turbines generate a wealth of data which can be effectively used to improve maintenance strategies and drive down O&M costs, which account for 20-25% of the cost of generation of wind energy. Data-driven techniques for enabling prognostic and health management (PHM) technologies have seen many successes in the space. However, managing this data, particularly in the context of an industrial facility which may have many other data streams, is a challenge. This technical brief describes the schematic of a proposed system for managing turbine data, ahead of an implementation which will see PHM techniques applied to it. The turbine in this case is attached to a manufacturing facility, so the pipeline is designed to be modular and integrate well with an existing pipeline at that facility.

Publication Year: 
2019
Publication Volume: 
10
Publication Control Number: 
017
Page Count: 
4
Submission Keywords: 
Wind Turbines
PHM
data ingestion
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
Industrial applications
Standards and methodologies
Submitted by: 
  
 
 
 

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