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@inproceedings{Lucke:2019:10.1016/j.ifacol.2019.06.140,
author = {Lucke, M and Mei, X and Stief, A and Chioua, M and Thornhill, NF},
doi = {10.1016/j.ifacol.2019.06.140},
pages = {673--678},
publisher = {International Federation of Automatic Control (IFAC)},
title = {Variable selection for fault detection and identification based on mutual information of alarm series},
url = {http://dx.doi.org/10.1016/j.ifacol.2019.06.140},
year = {2019}
}

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TY  - CPAPER
AB  - Reducing the dimensionality of a fault detection and identification problem is often a necessity, and variable selection is a practical way to do it. Methods based on mutual information have been successful in that regard, but their applicability to industrial processes is limited by characteristics of the process variables such as their variability across fault occurrences. The paper introduces a new estimation strategy of mutual information criteria using alarm series to improve the robustness of the variable selection. The minimal-redundancy-maximal-relevance criterion on alarm series is suggested as new reference criterion, and the results are validated on a multiphase flow facility.
AU  - Lucke,M
AU  - Mei,X
AU  - Stief,A
AU  - Chioua,M
AU  - Thornhill,NF
DO  - 10.1016/j.ifacol.2019.06.140
EP  - 678
PB  - International Federation of Automatic Control (IFAC)
PY  - 2019///
SN  - 1474-6670
SP  - 673
TI  - Variable selection for fault detection and identification based on mutual information of alarm series
UR  - http://dx.doi.org/10.1016/j.ifacol.2019.06.140
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000473270600113&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.sciencedirect.com/science/article/pii/S2405896319302277?via%3Dihub
UR  - http://hdl.handle.net/10044/1/72199
ER  -

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