Turbomachinery degradation monitoring using adaptive trend analysis
File(s)
Published version
Author(s)
Zagorowska, Marta
Ditlefsen, Arne-Marius
Thornhill, Nina F
Skourup, Charlotte
Type
Conference Paper
Abstract
Performance deterioration in turbomachinery is an unwanted phenomenon that changes the behaviour of the system. It can be described by a degradation indicator based on deviations from expected values of process variables. Existing models assume that the degradation is strictly increasing with fixed convexity and that there are no additional changes during the considered operating period. This work proposes the use of an exponential trend approximation with shape adaptation and apply it in a moving window framework. The suggested method of adjustment makes it possible for the model to follow the evolution of the indicator over time. The approximation method is then applied for monitoring purposes, to predict future degradation. The influence of the tuning parameters on the accuracy of the algorithm is investigated and recommendations for the values are derived. Finally directions for further work are proposed.
Date Issued
2019-07-02
Date Acceptance
2019-04-23
Citation
IFAC Proceedings Volumes (IFAC-PapersOnline), 2019, 52 (1), pp.679-684
ISSN
1474-6670
Publisher
International Federation of Automatic Control (IFAC)
Start Page
679
End Page
684
Journal / Book Title
IFAC Proceedings Volumes (IFAC-PapersOnline)
Volume
52
Issue
1
Copyright Statement
© 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Sponsor
Commission of the European Communities
ABB Switzerland Ltd.
ABB Switzerland Ltd.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000473270600114&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
675215
N/A
N/A
Source
12th International-Federation-of-Automatic-Control (IFAC) Symposium on Dynamics and Control of Process Systems including Biosystems (DYCOPS)
Subjects
Trends
Function approximation
Device degradation
Fault detection
Prediction methods
Compressors
Publication Status
Published
Start Date
2019-04-23
Finish Date
2019-04-26
Coverage Spatial
Florianopolis, BRAZIL
Date Publish Online
2019-07-02