Dual EKF estimator for fault detection and isolation in Heating Ventilation and Air Conditioning systems

Nowadays to monitor and to control the recent generation of high complexity Heating Ventilation Air Conditioning (HVAC) building systems under a wide variety of occupancy and load related operating conditions represents one of the most difficult and challenging task. The main objective of this study is to develop a new approach of the fault detection, diagnosis and isolation (FDDI) automated techniques applied to the valve actuator failures in HVAC systems. These techniques are based on the dual Extended Kalman Filter that combines state estimation and parameter estimation to detect the faulty valve (stuck opened and stuck closed), to determine the fault severity and finally to isolate it. The superiority of this approach is its simplicity and its application to a wide range of similar applications. This algorithm is implemented in a simulation environment, and the fault diagnosis results could be evaluated for a several fault scenarios in terms of the injection fault, detection time, and its severity.