Conference proceeding
Using Pattern Matching and Principal Component Analysis Method for Whole Building Fault Detection
2017 ASHRAE ANNUAL CONFERENCE PAPERS
01 Jan 2017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Automated fault detection and diagnosis (AFDD) methods, followed by corrections, have the potential to greatly improve a building and its system's performances. Existing AFDD studies mostly focus on component and sub-system AFDD. Much less efforts have been spent on detecting and diagnosing faults that have a whole building impact. Component diagnosis decouples the connections between building subsystems and may reach local and often incorrect solutions without leading to an overall sustainable and optimally conditioned systems. In this pilot study, a data driven fault detection method that has been successfully applied to component fault detection: Pattern Matching (PM) and Principle Component Analysis (PCA) method is applied for whole building fault detection. Real building data that contain artificially injected faults and naturally occurred faults are used to evaluate the method's accuracy and false alarm rate. The method presents a great potential to be a cost-effective and accurate whole building fault detection strategy.
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Details
- Title
- Using Pattern Matching and Principal Component Analysis Method for Whole Building Fault Detection
- Creators
- Yimin Chen - Drexel Univ, Philadelphia, PA 19104 USAJin Wen - Drexel UniversityAdam Reigner - Drexel Univ, Philadelphia, PA 19104 USAASHRAE
- Publication Details
- 2017 ASHRAE ANNUAL CONFERENCE PAPERS
- Conference
- 2017 ASHRAE ANNUAL CONFERENCE PAPERS
- Series
- ASHRAE Annual Conference Papers
- Publisher
- Amer Soc Heating, Refrigerating And Air-Conditioning Engs
- Number of pages
- 8
- Grant note
- DE-FOA-0001167 / Department of Energy; United States Department of Energy (DOE)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Identifiers
- 991019170566904721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Construction & Building Technology
- Thermodynamics