Online fatigue detection of a SMA-based control valve using CUSUM algorithm

This paper describes a functional fatigue detection system for nonlinear SMA-based control valve. Any drift from the normal behavior of the valve is revealed using a model-based residual generator by means of a nonlinear auto-regressive with eXogenous input (NARX) model. Based on the optimisation property of cumulative sum (CUSUM), an online system for detecting changes in statistical properties of residuals due to fatigue of the valve is developed. The experimental results suggest that the variance of one step ahead (OSA) error and model predicted error (MPE) is a good indicator of fatigue states of the valve.