Fault detection and diagnostics analysis of air conditioners using virtual sensors

Abstract

The primary goal of this research is to evaluate, implement, and demonstrate a fault detection and diagnostic based on a number of virtual sensors and a fault impact model in the field. The primary bottlenecks to diagnostic implementation in the field are the high initial costs of additional sensors. The other difficulty in applying existing approach is in handling multiple faults that occur simultaneously because the state variables can depend on more than one fault along with the operating conditions. However, the diagnostic approaches based on virtual sensors can identify and isolate specific faults using a number of low-cost physical sensors. As the first of step, an analysis of data from a number of air conditioners was conducted to understand the impacts of condenser fouling faults on performance in order to set thresholds for diagnostics. The field test for the air conditioners was performed to simulate refrigerant charge faults and condenser fouling. The existing charging method would have difficulty in identifying the proper charge amount under condenser fouling conditions. However, the virtual sensor provides an accurate refrigerant charge estimates within 10% of real measurements regardless of the different operating temperatures and condenser fouling faults. In addition, the implementation and demonstration of the automated fault detection and diagnostic has been developed and connected to data obtained from the air conditioner monitored in the field.