Citation

BibTex format

@article{Cecilio:2014:10.1016/j.jprocont.2014.06.007,
author = {Cecilio, IM and Ottewill, JR and Pretlove, J and Thornhill, NF},
doi = {10.1016/j.jprocont.2014.06.007},
journal = {Journal of Process Control},
pages = {1382--1393},
title = {Nearest neighbors method for detecting transient disturbances in process and electromechanical systems},
url = {http://dx.doi.org/10.1016/j.jprocont.2014.06.007},
volume = {24},
year = {2014}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Transient disturbances are increasingly relevant in process industries which rely on electromechanical equipment. Existing data-driven methods for detecting transient disturbances assume a distinct amplitude or time-frequency component. This paper proposes a detection method which is more generic and handles any short-term deviation of a measurement from its overall trend, regardless of whether the trend incorporates features such as oscillations, noise or changes in operation level. The method is based on a nearest neighbors technique and builds a vector of anomaly indices which are high for the period with the transient disturbance. The paper includes analyses of the statistical significance of the threshold proposed and of the sensitivity of the parameters, and it also suggests a color map to visualize the detection results. The method is demonstrated on experimental and industrial case studies.
AU - Cecilio,IM
AU - Ottewill,JR
AU - Pretlove,J
AU - Thornhill,NF
DO - 10.1016/j.jprocont.2014.06.007
EP - 1393
PY - 2014///
SN - 1873-2771
SP - 1382
TI - Nearest neighbors method for detecting transient disturbances in process and electromechanical systems
T2 - Journal of Process Control
UR - http://dx.doi.org/10.1016/j.jprocont.2014.06.007
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000342256600005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/43309
VL - 24
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