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

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...

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Published inAutomation in construction Vol. 44; pp. 197 - 211
Main Authors Dong, Bing, O'Neill, Zheng, Li, Zhengwei
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier B.V 01.08.2014
Elsevier
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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. •Developed a BIM enabled information infrastructure for FDD.•Integrate static and operational information based on BIM I2.•Real-time implementation of BIM I2 for FDD, and detect HVAC faults.
AbstractList 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. •Developed a BIM enabled information infrastructure for FDD.•Integrate static and operational information based on BIM I2.•Real-time implementation of BIM I2 for FDD, and detect HVAC faults.
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 (B1M) 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.
Author Dong, Bing
Li, Zhengwei
O'Neill, Zheng
Author_xml – sequence: 1
  givenname: Bing
  surname: Dong
  fullname: Dong, Bing
  email: bing.dong@utsa.edu
  organization: Department of Mechanical Engineering, The University of Texas at San Antonio, San Antonio, TX 78249, USA
– sequence: 2
  givenname: Zheng
  surname: O'Neill
  fullname: O'Neill, Zheng
  email: zoneill@eng.ua.edu
  organization: Department of Mechanical Engineering, The University of Alabama, Tuscaloosa, AL 35401, USA
– sequence: 3
  givenname: Zhengwei
  surname: Li
  fullname: Li, Zhengwei
  email: zhengwei_li@tongji.edu.cn
  organization: School of Mechanical and Energy Engineering, Tongji University, PR China
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Keywords Real-time implementation
Building Information Modeling
Information infrastructure
Fault Detection and Diagnostics
Data schema
Energy analysis
Data analysis
Buildings
Building information modeling
Information management
Maintenance
Real time
Modeling
Implementation
Case study
Simulation
Energetic efficiency
Barrack
Detection
Fault diagnostic
Quantitative analysis
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Snippet Although energy-efficient building technologies are emerging, a key challenge is how to effectively maintain building energy performance over the evolving...
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StartPage 197
SubjectTerms Applied sciences
Building failures (cracks, physical changes, etc.)
Building Information Modeling
Buildings
Buildings. Public works
Computation methods. Tables. Charts
Construction
Data schema
Diagnostic systems
Durability. Pathology. Repairing. Maintenance
Energy conservation
Exact sciences and technology
Exchange
Fault Detection and Diagnostics
Information infrastructure
Infrastructure
Modules
Real-time implementation
Structural analysis. Stresses
Tasks
Types of buildings
Title A BIM-enabled information infrastructure for building energy Fault Detection and Diagnostics
URI https://dx.doi.org/10.1016/j.autcon.2014.04.007
https://www.proquest.com/docview/1567108670
https://www.proquest.com/docview/1677939440
Volume 44
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