Auxiliary Particle Filter–Based Multisensor Data Fusion for Quantification of Corrosion in Aerostructures

Abstract

Abstract The identification of structural flaws and subsequent management is significant for health monitoring of aviation structures. Wall thickness loss can occur because of corrosion in exposed aerostructures, thereby reducing the strength of the structure. This may impose prolonged downtimes for repair and replacement activities if not detected at early stages. Eddy current testing (ECT) is a viable technique to detect such anomalies. Fusing multifrequency data produces better results because of complementary features of each contributing mode. Particle filter–based methods have already been proposed to detect and quantify flaw profiles of corrosion damage to an aircraft structure using a multifrequency ECT data fusion technique. However, to address the associated drawbacks, an auxiliary particle filter (APF) method is proposed here. In APF, the proposed importance density is a mixture of the prior state and the latest measurements, yielding focused estimation into a high-likelihood region. Simulation results are presented to demonstrate effectiveness of the proposed technique to quantify damages in aerostructures.