Extended Kalman filter-based prognostic of actuator degradation in two tank system

Rapid growth in the industries need an effective predictive maintenance policy. Failure in the equipment decreases the production rate and thereby, causing a loss to the industry. The equipment especially, the actuator is operated continuously in the industries in order to achieve the desired production rate. Actuator is the key element which undergoes degradation due to frequent control actions. However, degradation is mainly influenced by different operating conditions and other environmental factors. This decreases the lifetime of the equipment and also it increases the maintenance cost. This problem is addressed by carrying out the reliability studies on the actuator by using Gamma process. It is used to describe the system  degradation. In this work, Gamma process based actuator modelling is used to study the deterioration in the actuator. The gamma parameters such as shape and scale parameters are the deciding factors describing the level of degradation in the system. It is then applied to two tank feedback control system. Extended version of Kalman filter estimates the state of noisy measurements which describes the fault trend characteristics in the system. Finally, the evolution of actuator capacity in presence of fault is analyzed and simulated in MATLAB environment.