A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A robust online fault detection and diagnosis strategy of centrifugal chiller systems for building energy efficiency
Highlights A hybrid FDD strategy with RBF model and EWMA control charts is proposed. Radial basis function is adopted to improve the accuracy of reference models. EWMA control charts are used to reduce the Type II error. The proposed strategy improves the FDD performances significantly. The proposed strategy is validated by the operating data from an office building.
Abstract The fault detection and diagnosis (FDD) of centrifugal chillers is always a complex difficulty in HVAC systems. This paper develops an online fault detection and diagnosis strategy based on non-linear radial basis function (RBF) to online detect and diagnose the fault of centrifugal chillers. The RBF is adopted to develop the reference feature parameter (FP) models. Exponentially-weighted moving average (EWMA) residual control charts of FP is used to detect the faults. A rule-based diagnostor is developed to online identify the fault. Seven common faults are taken in account for typical centrifugal chillers. The FDD strategy proposed was validated by using the experimental data from the ASHRAE RP-1043 project and the operating data of a centrifugal chiller in an office building of Hong Kong. The test results show that the RBF-EWMA method has achieved significant improvements in accuracy and reliability by comparing with the previous method with SVR-EWMA. The proposed RBF-EWMA method is robust for fault detection and diagnosis in centrifugal chiller systems.
A robust online fault detection and diagnosis strategy of centrifugal chiller systems for building energy efficiency
Highlights A hybrid FDD strategy with RBF model and EWMA control charts is proposed. Radial basis function is adopted to improve the accuracy of reference models. EWMA control charts are used to reduce the Type II error. The proposed strategy improves the FDD performances significantly. The proposed strategy is validated by the operating data from an office building.
Abstract The fault detection and diagnosis (FDD) of centrifugal chillers is always a complex difficulty in HVAC systems. This paper develops an online fault detection and diagnosis strategy based on non-linear radial basis function (RBF) to online detect and diagnose the fault of centrifugal chillers. The RBF is adopted to develop the reference feature parameter (FP) models. Exponentially-weighted moving average (EWMA) residual control charts of FP is used to detect the faults. A rule-based diagnostor is developed to online identify the fault. Seven common faults are taken in account for typical centrifugal chillers. The FDD strategy proposed was validated by using the experimental data from the ASHRAE RP-1043 project and the operating data of a centrifugal chiller in an office building of Hong Kong. The test results show that the RBF-EWMA method has achieved significant improvements in accuracy and reliability by comparing with the previous method with SVR-EWMA. The proposed RBF-EWMA method is robust for fault detection and diagnosis in centrifugal chiller systems.
A robust online fault detection and diagnosis strategy of centrifugal chiller systems for building energy efficiency
Tran, Dinh Anh Tuan (author) / Chen, Youming (author) / Chau, Minh Quang (author) / Ning, Baisong (author)
Energy and Buildings ; 108 ; 441-453
2015-09-19
13 pages
Article (Journal)
Electronic Resource
English
A Novel Strategy for the Fault Detection and Diagnosis of Centrifugal Chiller Systems
| Taylor & Francis Verlag | 2009