A real-time simulation tool for fault detection and diagnosis of HVAC systems

Faults tend to degrade the performance of HVAC systems by causing occupants' discomfort, increased energy consumption, and shorter life of equipment. Accordingly, it is very important to develop fault detection and diagnosis (FDD) tools for HVAC systems. In this thesis, in consideration of the fact that many faults could be traced back to oversized/undersized equipment, an interactive design tool is first developed to simulate the steady-state performance of a multi-zone variable-air-volume terminal reheat (VAV-TRH) HVAC system. This program is used for verifying HVAC system parameters to ensure that HVAC components are correctly sized. Then, a software program is developed to simulate the dynamic performance of a two-zone variable-air-volume terminal reheat (VAV-TRH) HVAC system. This program runs in two modes: off-line and on-line. Using this program, two control strategies---an optimal control strategy and a reheat control strategy, are studied. Simulation results show that the optimal control strategy leads to more energy savings than the reheat control strategy and is valid most of the operation time. The program is also useful for on-line fault detection and diagnosis for the HVAC system. In order to achieve this goal, an expert rule set for on-line FDD is established using knowledge-based approach. The expert rule set, in which IF-THEN clauses are applied, consists of simple rules that can successfully identify some fairly obvious problems that are often overlooked. The simulation experiments are performed to examine the performance of expert rules using data from real-time simulations. Simulation results show that expert rules are efficient in on-line detection and diagnosis of HVAC faults