Nonlinear Kalman Filtering for acoustic emission source localization in anisotropic panels.

摘要: Nonlinear Kalman Filtering is an established field in applied probability and control systems, which plays important role many practical applications from target tracking to weather climate prediction. However, its application for acoustic emission (AE) source localization has been very limited. In this paper, two well-known nonlinear algorithms are presented estimate the location of AE sources anisotropic panels: Extended Filter (EKF) Unscented (UKF). These cases: velocity profile known (CASE I) unknown II). The compared with a more traditional least squares method. Experimental tests carried out on carbon-fiber reinforced polymer (CFRP) composite panel instrumented sparse array piezoelectric transducers validate proposed approaches. simulated using miniature impulse hammer. order evaluate performance algorithms, metrics used: (1) accuracy (2) computational cost. Furthermore, it shown that both EKF UKF can provide confidence interval estimated account uncertainty time flight measurements.