Citation

BibTex format

@inproceedings{Zagorowska:2019:10.1016/j.ifacol.2019.06.141,
author = {Zagorowska, M and Ditlefsen, A-M and Thornhill, NF and Skourup, C},
doi = {10.1016/j.ifacol.2019.06.141},
pages = {679--684},
publisher = {International Federation of Automatic Control (IFAC)},
title = {Turbomachinery degradation monitoring using adaptive trend analysis},
url = {http://dx.doi.org/10.1016/j.ifacol.2019.06.141},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - 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.
AU - Zagorowska,M
AU - Ditlefsen,A-M
AU - Thornhill,NF
AU - Skourup,C
DO - 10.1016/j.ifacol.2019.06.141
EP - 684
PB - International Federation of Automatic Control (IFAC)
PY - 2019///
SN - 1474-6670
SP - 679
TI - Turbomachinery degradation monitoring using adaptive trend analysis
UR - http://dx.doi.org/10.1016/j.ifacol.2019.06.141
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000473270600114&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - https://www.sciencedirect.com/science/article/pii/S2405896319302289?via%3Dihub
UR - http://hdl.handle.net/10044/1/72195
ER -

Contact us

Nina Thornhill, ABB/RAEng Professor of Process Automation
Centre for Process Systems Engineering
Department of Chemical Engineering
Imperial College London
South Kensington Campus, London SW7 2AZ

Tel: +44 (0)20 7594 6622
Email: n.thornhill@imperial.ac.uk