Fault detection and diagnosis for air conditioners and heat pumps based on virtual sensors
Abstract
The primary goal of this research is to develop and demonstrate an integrated, on-line performance monitoring and diagnostic system with low cost sensors for air conditioning and heat pump equipment. Automated fault detection and diagnostics (FDD) has the potential for improving energy efficiency along with reducing service costs and comfort complaints. To achieve this goal, virtual sensors with low cost measurements and simple models were developed to estimate quantities that would be expensive and or difficult to measure directly. A virtual refrigerant charge sensor (VRC) was extended with three approaches for determining refrigerant charge for equipment having variable-speed compressors and fans. Three different virtual refrigerant mass flow (VRMF) sensors were evaluated for estimating refrigerant mass flow rate. The first model uses a compressor map that relates refrigerant flow rate to measurements of condensing and evaporating saturation temperature, and inlet temperature measurements. The second model uses a compressor energy balance with the power consumption from a virtual compressor power (VCP) sensor and energy heat loss model, which is relatively independent of compressor and expansion valve faults that influence mass flow rate. The third model was developed using an empirical correlation for thermal expansion valves (TXV) and electronic expansion valves (EEV) based on an orifice equation. To assess the impact of faults on system performance, capacity, efficiency, and operating cost were evaluated using data for units tested in the laboratory and for data obtained from manufacturers. The impacts of faults were used in deciding thresholds for the FDD demonstration system. Information about capacity, power consumption, and energy efficiency can be used in real-time monitoring of the economic status of equipment and for decision support. The complete diagnostic FDD system was implemented and demonstrated for a rooftop air conditioner (RTU) that incorporates integrated virtual sensors and fault impact evaluation for decision support. The FDD RTU demonstration system provided the following diagnostic outputs: 1) loss of compressor performance, 2) low or high refrigerant charge, 3) fouled condenser or evaporator filter, 4) faulty expansion device, and 5) liquid-line restriction. The tests also quantified the benefits of this technology with measurements of equipment performance and demonstrated implementation with low sensor costs.
Degree
Ph.D.
Advisors
Braun, Purdue University.
Subject Area
Mechanical engineering
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