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Fault detection for buildings using uncertain parameters and interacting multiple-model method

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00335591" target="_blank" >RIV/68407700:21230/19:00335591 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Fault detection for buildings using uncertain parameters and interacting multiple-model method

  • Original language description

    Model-based fault detection and diagnosis (FDD) systems for buildings are very demanding on the solution set up eort. One rea- son is the requirement to use a high-delity model which must be created for each building separately. The FDD approach that reduces this bur- den is proposed in this paper. Proposed FDD algorithms are based on the interacting multiple-model (IMM) method and Kalman ltering for systems with uncertain parameters. The uncertain parameters in models enable to use "average" zone models rather than high-delity models, which simplies real applications. Detection of single and multiple faults is demonstrated on an example where faults, that might cause ine- ciency of control, are detected. Results show that the performance of the proposed algorithms with average zone models is comparable to the performance of the conventional IMM with accurate models.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

    <a href="/en/project/GA18-26278S" target="_blank" >GA18-26278S: Incorporation of Prior Knowledge for Identification of Nonlinear Systems</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Lecture Notes in Control and Information Sciences - Proceedings

  • ISBN

  • ISSN

    2522-5383

  • e-ISSN

  • Number of pages

    20

  • Pages from-to

  • Publisher name

    Springer

  • Place of publication

    Wien

  • Event location

    Bologna

  • Event date

    Nov 21, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article