A Fault Detection and Diagnosis Method for Low Delta-T Syndrome in a Complex Air-conditioning System

Abstract

Low delta-T syndrome widely exists in the existing air-conditioning systems and results in increased energy consumption. This paper presents a fault detection and diagnosis method (FDD) to detect and diagnose the low delta-T syndrome resulted from the water fouling of cooling coils in a complex cooling system. Performance indices and adaptive thresholds are adopted in the FDD strategy to diagnose the health condition of the system. The adaptive threshold can effectively improve the prediction uncertainty of the reference models and the calculation uncertainty of performance indices under various working conditions. The proposed method was validated in a dynamic simulation platform representing a real complex HVAC system studied. The results show that the proposed FDD strategy can successfully detect the low delta-T syndrome and identify the faults.