A Methodology for Diagnosing Multiple Simultaneous Faults in Vapor-Compression Air Conditioners

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Abstract
Existing methods addressing automated fault detection and diagnosis (FDD) for vapor-compression air-conditioning equipment have good performance for faults that occur individually but have difficulty handling multiple simultaneous faults. In addition, these methods either require high-cost measurements or measurements over a wide range of conditions for training reference models, the development of which can be time consuming and cost prohibitive. This paper formulates model-based FDD in a generic way and demonstrates that decoupling is the key to handling multiple simultaneous faults. To eliminate a cost-prohibitive overall system model, an alternative physical decoupling methodology to mathematical decoupling is developed. During the mathematical development, a previously developed FDD method termed the statistical rule-based method is reexamined and cast within the general mathematical framework. The paper also includes an evaluation of the FDD method in terms of both sensitivity and robustness.

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