Feasibility study of a multi-parameter probability of detection formulation for a Lamb waves–based structural health monitoring approach to light alloy aeronautical plates

In view of an extensive literature about guided waves–based structural health monitoring of plate-like structures made of metallic and composite materials, a lack of information is pointed out regarding an effective and universally accepted approach for characterizing capability and reliability in detecting, localizing and sizing in-service damages. On the other hand, in the frame of traditional non-destructive testing systems, capability is typically expressed by means of suitable ‘probability of detection’ curves based on Berens’ model, where a linear relationship is established between probability of detection and flaw size. Although the uncertain factors are usually different between a non-destructive inspection technique and a structural health monitoring approach, it seems that a similar mathematical framework could be assumed. From this point of view, this research investigates the feasibility of application of the very recent ‘multi-parameter’ probability of detection approach, developed within the traditional non-destructive testing field, to guided waves–based structural health monitoring. In particular, numerical simulations as well as experimental responses from flawed aluminium alloy plates were combined to bring about a ‘master’ probability of detection curve. Once established, this curve can be used to study the intrinsic capability of the system in terms of probability of detection curves, overcoming the intrinsic limitation of a single predictor (like the crack size) and a statistical model typically based upon a linear behaviour between the predictor and the response.