Failure monitoring in a high performance hydrostatic actuation system using the extended Kalman filter

This paper describes the development and evaluation of a fault detection strategy for a high performance hydrostatic actuation system, the electrohydraulic actuator (EHA). The approach makes use of the extended Kalman filter (EKF) technique for parameter estimation purposes and changes in the estimated system parameters were related to faults in the EHA. The hydrostatic system has potential applications in the aerospace industry, in robotics, in machining and as such, failures in the EHA can pose a safety hazard as well as result in costly downtime and unscheduled maintenance. Monitoring failures in the hydrostatic system is achieved by estimating two parameters of interest, namely the viscous friction coefficient and the effective bulk modulus. Changes in the viscous friction coefficient in the actuator indicate deterioration of the hydraulic oil or wear in the seals. Lowering of the effective bulk modulus affects the response of the closed loop system, reduces system bandwidth and may cause instability. A simulation study was conducted to investigate the feasibility of the approach as well as the level of accuracy to be expected. The methodology was then verified using experimental results.