A BIM-enabled information infrastructure for building energy Fault Detection and Diagnostics

Bing Dong, Zheng O'Neill, Zhengwei Li

Research output: Contribution to journalArticle

70 Scopus citations

Abstract

Although energy-efficient building technologies are emerging, a key challenge is how to effectively maintain building energy performance over the evolving lifecycle of the building. Field experience shows that energy savings of 5-30% are typically achievable simply by applying energy Fault Detection and Diagnostics (FDD) and correcting faults diagnosed in buildings. Model-based FDD in buildings is a challenging task, not only because the task itself is difficult, but also because the workflow and information exchange behind the task is very complex and error prone. This complexity arises from several aspects. Firstly, creating a baseline building energy performance model suitable for FDD is both time and labor consuming. Secondly, the FDD module typically has its own ad-hoc platform, and the integration of this platform with the existing Building Energy Management System (BEMS) is technically challenging due to the incompatible interoperability. Finally, the information exchange itself is complex due to the existence of multiple functioning modules to make FDD workflow happen. To perform an efficient and effective FDD with the BEMS in buildings, information is needed to flow among an as-built building static information module, a building energy performance simulation module, a building operational data acquisition module and a FDD module. In such a complex process, it is challenging to ensure the information integrity and consistence. In this paper, we propose a Building Information Modeling (BIM) enabled information infrastructure for FDD, which streamlines the information exchange process and therefore has the potential to improve the efficiency of similar works in practice. The proposed information infrastructure was deployed and implemented in a real building for a FDD case study.

Original languageEnglish (US)
Pages (from-to)197-211
Number of pages15
JournalAutomation in Construction
Volume44
DOIs
StatePublished - Aug 2014
Externally publishedYes

Keywords

  • Building Information Modeling
  • Data schema
  • Fault Detection and Diagnostics
  • Information infrastructure
  • Real-time implementation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

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