Data characterization for automatic selection of valve stiction detection algorithms

Alexey Zakharov*, Elena Zattoni, Lei Xie, Octavio Pozo Garcia, Sirkka-Liisa Jämsä-Jounela

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

This paper proposes a valve stiction detection system which selects applicable valve stiction detection algorithms based on characterization of the data. Additionally, the proposed system computes the final detection decision, weighting, by means of suitably-defined reliability indexes, the individual decisions provided by the selected algorithms. The paper demonstrates the effectiveness of the proposed valve stiction detection system with benchmark industrial data.

Original languageEnglish
Title of host publication2013 IEEE 52ND ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC)
PublisherIEEE
Pages4355-4360
Number of pages6
DOIs
Publication statusPublished - 2013
MoE publication typeA4 Article in a conference publication
EventIEEE Conference on Decision and Control - Florence, Italy
Duration: 10 Dec 201313 Dec 2013
Conference number: 52

Publication series

NameIEEE Conference on Decision and Control
PublisherIEEE
ISSN (Print)0743-1546

Conference

ConferenceIEEE Conference on Decision and Control
Abbreviated titleCDC
CountryItaly
CityFlorence
Period10/12/201313/12/2013

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