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MODELBASED DIAGNOSTICS, MAINTENANCE ON DEMAND AND DECISION SUPPORT ON BOILERS
Mälardalen University, School of Sustainable Development of Society and Technology. (PRO)ORCID iD: 0000-0002-7233-6916
Mälardalen University, School of Sustainable Development of Society and Technology. (PRO)
Mälardalen University, School of Business, Society and Engineering. (MERO)ORCID iD: 0000-0001-8191-4901
2009 (English)In: SIMS, Scandinavian Modelling and Simulation  Society 50, conference in Fredrice, Denmark, October 7-8 (2009)), Fredrice: SIMS electronic , 2009Conference paper, Published paper (Refereed)
Abstract [en]

At a CFB boiler a system has been tested based on a Modelica model together with a decision support system. The model is a physical model including energy and material balances, chemical reactions like combustion and gasification reactions. For the combustion system we primarily consider equilibrium conditions while for gasification the kinetics is important and thus PLS-models built on experimental data in a pilot plant are combined with literature data and a physical model. The simulation model is first developed in Modelica, but then placed as an object in Simulink/Matlab, from which data is communicated to and from the data base through OPC-server. Measured data are collected from the process data base and inserted as initial data into the simulation model, including the boiler, separator, heat exchangers and steam system. A simulation during 300 seconds is performed and the data after this is compared to the initial data. If we have steady state conditions, the values after the simulation will be the same as the initial data, while if the data are not balanced, the difference will correspond to a balanced state between all measured data and the physical correlations in the boiler. This procedure is repeated on a regular basis and the trend of the difference between the measured and the balanced data is plotted and analyzed with respect to slope respectively variance. These data are combined with other type of information like standard deviation of sensors, which corresponds to noise; is the data value changing at all? Input of manual information like lab-data, unexpected events like noise; maintenance actions; activities like how many times a valve has been opening and closing; combination of data like Energy and Mass balances combined with conductivity in blow down from steam drum to detect possible leakages in piping or boiler systems;

All this information is introduced into a BN, Bayesian Net, which has been built from known relations, but where the quantitative data is built from experience and statistics. In this way we can then detect possible faults or probable faults coming up. This information is used by both the operators and maintenance staff. The mathematical simulation model over the CFB boiler and results from the utilization is presented in this paper.

Place, publisher, year, edition, pages
Fredrice: SIMS electronic , 2009.
Keyword [en]
CFB boiler, mathematical model, simulation, diagnostics, decision support
National Category
Engineering and Technology
Research subject
Energy- and Environmental Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-7893OAI: oai:DiVA.org:mdh-7893DiVA: diva2:292683
Conference
SIMS, Scandinavian Modelling and Simulation Society 50, conference in Fredrice, Denmark, October 7-8 (2009))
Projects
Värmeforsk Behovsstyrt Underhåll
Available from: 2010-02-11 Created: 2010-02-09 Last updated: 2013-12-27Bibliographically approved

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http://www.scansims.org/sims2009/

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CiteExportLink to record
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Citation style
  • apa
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