Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Building Services Engineering | en_US |
| dc.creator | Cui, Jingtan | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/149 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | A robust fault detection and diagnosis strategy for centrifugal chillers | en_US |
| dcterms.abstract | Building Heating, Ventilating, Air-conditioning and Refrigerating (HVAC&R) systems usually fail to satisfy performance expectations envisioned at design stage for a variety of reasons. FDD (Fault Detection and Diagnosis) methods are needed to identify the faults and help put the systems back into normal operation. However, the performance of FDD methods applied to HVAC&R systems require sensor measurements, which are also susceptible to various faults. Although a great deal of FDD research has been carried out on component faults or sensor faults in HVAC&R systems, not much research has tackled these two different kinds of faults when they occur simultaneously in HVAC&R systems. This thesis presents a robust FDD strategy for centrifugal chillers, which are the core of building HVAC&R systems. The strategy consists of a basic chiller FDD scheme and a PCA-based sensor FDD&E (Fault Detection, Diagnosis and Estimation) scheme, which target chiller component faults (called chiller faults hereafter for conciseness) and sensor faults, respectively. In implementing the strategy, it is important that the measurements of the sensors crucial to the chiller FDD are validated by the sensor FDD&E scheme before the chiller FDD scheme is carried out to detect and diagnose chiller faults. The basic chiller FDD scheme employs six performance indexes which have strong thermophysical meaning to depict the health status of a typical centrifugal chiller. The residual for each performance index is generated by comparing the measured value with its benchmark predicted by a simple reference model. Once residuals of one or more performance indexes are outside the range defined by the corresponding fault detection thresholds, the chiller will be considered to be faulty. Particular faults are diagnosed by a fault diagnostic classifier, which is based on the deviation pattern of the performance indexes when a chiller fault occurs. Robustness of the scheme is achieved by the adoption of an adaptive estimator for the fault detection threshold. The estimator can set reasonable fault detection thresholds by taking account of essential influencing factors. Because the performance of the basic chiller FDD scheme depends on the quality of sensor measurements, a sensor FDD&E scheme is developed to tackle sensor faults. The latter scheme uses a PCA method to capture correlations among key variables in centrifugal chillers. The Q-statistic is used to measure the variance of the correlations, and its upper limit usually defines the normal ranges of the variance. If the Q-statistic exceeds the normal ranges, it will indicate that the correlations among variables are invalid and the sensors are unreliable. Afterwards, the Q-contribution plot and an iterative approach are respectively used to diagnose and correct sensor faults. The PCA-based sensor FDD&E scheme can detect, diagnose and estimate sensor faults even in the presence of most typical chiller faults. The reason for this is that chiller faults are pertinent to performance degradations which are physically explainable and belong to the variance captured by the PCA model. Each of the two schemes is validated using laboratory data provided by an ASHRAE research project as well as field data collected from the BMS of a real building in Hong Kong. In particular, it is the first time in the HVAC&R FDD field that a sensor FDD method has been verified while taking into consideration the possible effects of typical chiller faults. Moreover, validation results of the robust chiller FDD strategy using the laboratory data show that the strategy is capable of handling chiller faults and sensor faults that exist simultaneously. The outcomes of the research reported in this thesis should provide an effective prototype for developing robust FDD strategies that can be applied in the HVAC&R industry. This will in turn help achieve better Indoor Environmental Quality (IEQ) for occupants and lower building energy consumption. | en_US |
| dcterms.extent | xix, 227 leaves : ill. ; 30 cm. | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2005 | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations. | en_US |
| dcterms.LCSH | Air conditioning -- Design and construction. | en_US |
| dcterms.LCSH | Cooling towers -- Design and construction. | en_US |
| dcterms.LCSH | Fault location (Engineering) | en_US |
| dcterms.LCSH | Commercial buildings -- Air conditioning. | en_US |
| dcterms.LCSH | Commercial buildings -- Heating and ventilation. | en_US |
| dcterms.accessRights | open access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b18355262.pdf | For All Users | 2.52 MB | Adobe PDF | View/Open |
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