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Fault Identification and Fault Impact Analysis of The Vapor Compression Refrigeration Systems in Buildings: A System Reliability Approach

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Listed:
  • Mostafa Fadaeefath Abadi

    (Department of Building, Civil and Environmental Engineering (BCEE), Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Mohammad Hosseini Rahdar

    (Department of Building, Civil and Environmental Engineering (BCEE), Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Fuzhan Nasiri

    (Department of Building, Civil and Environmental Engineering (BCEE), Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

  • Fariborz Haghighat

    (Department of Building, Civil and Environmental Engineering (BCEE), Gina Cody School of Engineering and Computer Science, Concordia University, Montréal, QC H3G 1M8, Canada)

Abstract

The Vapor Compression Refrigeration System (VCRS) is one of the most critical systems in buildings typically used in Heating, Ventilation, and Air Conditioning (HVAC) systems in residential and industrial sections. Therefore, identifying their faults and evaluating their reliability are essential to ensure the required operations and performance in these systems. Various components and subsystems are included in the VCRS, which need to be analyzed for system reliability. This research’s objective is conducting a comprehensive system reliability analysis on the VCRS by focusing on fault identification and determining the fault impacts on these systems. A typical VCRS in an office building is selected for this research regarding this objective. The corresponding reliability data, including the probability distributions and parameters, are collected from references to perform the reliability evaluation on the components and subsystems of the VCRS. Then the optimum distribution parameters have been obtained in the next step as the main findings. Additionally, by applying optimization techniques, efforts have been taken to maximize the system’s reliability. Finally, a comparison between the primary and the optimized systems (with new distribution parameters) has been performed over their lifetime to illustrate the system’s improvement percentage.

Suggested Citation

  • Mostafa Fadaeefath Abadi & Mohammad Hosseini Rahdar & Fuzhan Nasiri & Fariborz Haghighat, 2022. "Fault Identification and Fault Impact Analysis of The Vapor Compression Refrigeration Systems in Buildings: A System Reliability Approach," Energies, MDPI, vol. 15(16), pages 1-21, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:5774-:d:883730
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    References listed on IDEAS

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    1. Hamed Ahmadzade & Rong Gao, 2018. "Reversed hazard function of uncertain lifetime," Fuzzy Optimization and Decision Making, Springer, vol. 17(4), pages 387-400, December.
    2. Ilia Frenkel & Lev Khvatskin, 2012. "Reliability Decisions for Supermarket Refrigeration System by using Combined Stochastic Process and Universal Generating Function Method: Case Study," Springer Series in Reliability Engineering, in: Anatoly Lisnianski & Ilia Frenkel (ed.), Recent Advances in System Reliability, chapter 0, pages 97-112, Springer.
    3. Hengjie Zhang & Yucheng Dong & Jing Xiao & Francisco Chiclana & Enrique Herrera-Viedma, 2020. "Personalized individual semantics-based approach for linguistic failure modes and effects analysis with incomplete preference information," IISE Transactions, Taylor & Francis Journals, vol. 52(11), pages 1275-1296, November.
    Full references (including those not matched with items on IDEAS)

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