A fault detection and diagnosis approach based on nonlinear parity equations and its application to leakages and blockages in the drying section of a board machine

Alexey Zakharov, Vesa-Matti Tikkala, Sirkka-Liisa Jämsä-Jounela

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)
128 Downloads (Pure)

Abstract

This study aims at providing a fault detection and diagnosis (FDD) approach based on nonlinear parity equations identified from process data. Process knowledge is used to reduce the process nonlinearity from high to low-dimensional nonlinear functions representing common process devices, such as valves, and incorporating the monotonousness properties of the dependencies between the variables. The fault detection approach considers the obtained process model to be nonlinear parity equations, and fault diagnosis is carried
out with the standard structured residual method. The applicability of the approach to complex flow networks controlled by valves is tested on the drying section of an industrial board machine, in which the key problems are leakages and blockages of valves and pipes in the steam-water network. Nonlinear model equations based on the mass balance of different parts of the network are identified and validated. Finally, fault detection and diagnosis algorithms are successfully implemented, tested, and reported.
Original languageEnglish
Pages (from-to)1380-1393
JournalJournal of Process Control
Volume23
Issue number9
DOIs
Publication statusPublished - 2013
MoE publication typeA1 Journal article-refereed

Keywords

  • nonlinear model identification
  • gray-box model identification
  • fault detection and diagnosis
  • nonlinear parity equations
  • flow networks
  • leakages and blockages
  • multicylinder drying

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