Fault detection and isolation is a potentially powerful tool for achieving security and effective maintenance in various types of processes. The motivation for performing leakage detection in the coal injection plant is mainly the inflammability of pulverized coal. A leakage of air into an injection vessel could have catastrophic consequences. Nonlinear physical gray-box models of the plant are developed. Values of the unknown parameters are estimated by identification. Observers are constructed for these models and the residual is shown to be an estimate of the leakage flow.The Generalized Likelihood Ratio is employed to compare the residual to predefined typical leakage functions. When evaluating the residual, it is desirable to represent the essential dynamics concisely while removing irrelevant behaviour and noise. In order to ease the computational burden while preserving the essential dynamic behaviour of a leakage, a truncated Laguerre series representation of the signals is used. The developed algorithms are implemented in the commercially available product SafePCI and installed at SSAB Tunnplåt, Luleå. / Godkänd; 1999; 20070403 (ysko)
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-17121 |
Date | January 1999 |
Creators | Johansson, Andreas |
Publisher | Luleå tekniska universitet, Signaler och system, Luleå |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Licentiate thesis, comprehensive summary, info:eu-repo/semantics/masterThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | Licentiate thesis / Luleå University of Technology, 1402-1757 ; 1999:37 |
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