A robust fault detection and diagnosis strategy for pressure-independent VAV terminals of real office buildings
► A robust fault detection and diagnosis strategy using a hybrid approach is developed for pressure-independent VAV terminals. ► The residual-based CUSUM control charts detect faults in VAV terminals. ► The standard CUSUM control charts monitor the residuals which are statistically independent. ► A...
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Veröffentlicht in: | Energy and buildings 2011-07, Vol.43 (7), p.1774-1783 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | ► A robust fault detection and diagnosis strategy using a hybrid approach is developed for pressure-independent VAV terminals. ► The residual-based CUSUM control charts detect faults in VAV terminals. ► The standard CUSUM control charts monitor the residuals which are statistically independent. ► A rule-based fault classifier consisting of expert rules and fault isolation algorithms is developed to isolate 15 fault sources. ► The FDD strategy was online tested and validated using in real time data collected from real VAV air-conditioning systems.
A robust fault detection and diagnosis (FDD) strategy using a hybrid approach is presented for pressure-independent variable air volume (VAV) terminals in this paper. The residual-based cumulative sum (CUSUM) control charts are utilized to detect faults in VAV terminals. The residuals between the temperature error and its predication are generated using autoregressive time-series models. The standard CUSUM control charts are used to monitor the residuals which are statistically independent. If the CUSUM value exceeds the chart limits, it means the occurrence of fault or abnormity in the corresponding VAV terminal. The residual-based CUSUM control chart can improve the accuracy of fault detection through eliminating the effects of serial correlation on the performance of control charts. Also, the residual-based CUSUM control chart can enhance the robustness and reliability of fault detection through reducing the impacts of normal transient changes. A rule-based fault classifier consisting of expert rules and fault isolation algorithms is developed to isolate 15 fault sources. The FDD strategy was online tested and validated using in real time data collected from real VAV air-conditioning systems. |
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ISSN: | 0378-7788 |
DOI: | 10.1016/j.enbuild.2011.03.018 |