Nonlinear ultrasonic evaluation of disorderedly clustered pitting damage using an in situ sensor network

Abstract

Pervasive but insidious, pitting damage—from pitting corrosion in maritime structures through electrical pitting in bearings to debris cloud–induced pitting craters in spacecraft—is a typical modality of material degradation and lesion in engineering assets in harsh service environment. Pitting damage may feature hundreds of clustered, localized craters, cracks, and diverse microscopic defects (e.g. dislocation, micro-voids, and cracks) disorderedly scattered over a wide area. Targeting accurate, holistic evaluation of pitting damage (mainly the existence, location, and size of the pitted area), an insight into the generation of nonlinear features in guided ultrasonic waves (i.e. high-order harmonics) that are triggered by pitting damage, is achieved using a semi-analytical finite element approach, based on which a monotonic correlation between the nonlinear ultrasonic features and the holistic severity of pitting damage is established. With such correlation, a structural health monitoring framework is developed, in conjunction with the use of an in situ sensor network comprising miniaturized piezoelectric wafers, to characterize pitting damage accurately and monitor material deterioration progress continuously. The framework is experimentally validated, in which highly complex pitting damage in a space structure, engendered by a hypervelocity debris cloud, is evaluated precisely.