4S3F Diagnostic Bayesian Network method: discussion about application and technical design

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Abstract

In practice, automated energy performance fault diagnosis systems are seldom installed in HVAC systems. The main reason is that a specific Fault Detection and Diagnosis (FDD) setup is time-consuming and expensive because the existing methods are component-specific, not aligned with HVAC design practices, and not fully automated. 4S3F (four symptoms three faults) method, based on system engineering and Diagnostic Bayesian Networks (DBN), was proposed to decrease the gap between the design of HVAC systems for buildings and energy performance diagnosis, and proofs of concepts were tested on diverse parts of the HVAC system of one specific building. In order to test the further applicability potential of the method, it is necessary to expand these tests and to study possible problems arising in practice, like the lack of sensors installed in a specific system or practical difficulties in the construction of the 4S3F Bayesian network by HVAC or control. However, due to the small number of validations carried out on the environment, parameters, and installation process of this method still need further discussion and refinements. In this paper, we investigate how to construct the DBN for the quite generic AHU (Air Handling Unit) of a, with mechanical supply and exhaust, heating and cooling coils, and heat recovery. The paper describes the possible DBN's depending on the technical design and the measurement points. The diverse Bayesians networks are compared, and it is concluded that also, with a limited number of sensors, a diagnostic network can be set up. It is also concluded that step-by-step instructions would be needed to facilitate the work of HVAC engineers when setting up the diagnosis model.
Original languageEnglish
Title of host publicationCLIMA 2022 - 14th REHVA HVAC World Congress
Subtitle of host publicationEye on 2030, Towards digitalized, healthy, circular and energy efficient HVAC
PublisherTU Delft Open
Number of pages8
DOIs
Publication statusPublished - 2022
EventCLIMA 2022 - 14th REHVA HVAC World Congress: Towards digitalized, healthy, circular and energy efficient HVAC - Rotterdam, Netherlands
Duration: 22 May 202225 May 2022
https://clima2022.org/

Conference

ConferenceCLIMA 2022 - 14th REHVA HVAC World Congress
Country/TerritoryNetherlands
CityRotterdam
Period22/05/2225/05/22
Internet address

Keywords

  • Bayesian network
  • building energy performance
  • building energy diagnostics

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