A model-parameter invariant approach to HVAC fault detection and diagnosis

This thesis develops and experimentally evaluates a model-based detector for detecting actuator failures in HVAC systems which dynamically estimates the model parameters while performing detection. Specifically, this thesis considers actuator failures which result in the actuator valve sticks in an unknown (but constant) position. A first order heat-equation model is assumed to model interactions between adjacent rooms, which is used to formulate a hypothesis testing problem assuming that the inter-room thermal parameters are constant. The detector is formulated to provide performance that asymptotically bounds both the probability of miss and the probability of false alarm. A simulation environment is developed that emulates the building thermal dynamics assuming parameters identified through experimental testing.  Multiple testing scenarios are considered where the inter-room dynamics are physically altered between tests (by opening and closing windows and doors). Results indicate that the ability to accurately detect actuator failures is shown to be dependent on the inter-room thermal dynamics.  Insights into other model-parameter-invariant based detectors is provided based on the results obtained from this thesis.