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Defects in FRP structures may be introduced during the processing and fabrication of composite components and can initiate or grow in-service. In the context of this JRP, the term ‚defect‘ refers to imperfections introduced during manufacture/processing and/or secondary machining operations, as well as damage sustained during a component‘s service life. One of the challenges facing accurate and repeatable defect detection in FRP composites is the multitude of defect types that exist, each with characteristics that present different challenges to the NDE practitioner. In order for a particular NDE technique to achieve broad acceptance by industry, it is desirable for the technique to be able to detect a range of defect types with a high level of confidence. Project VITCEA (Validated Inspection Techniques for Composites in Energy Applications) is developing and validating traceable procedures for novel NDE techniques with contrasting detection capabilities, which will underpin the increased use of FRP composites for improved efficiency and reliability in energy related applications e.g. wind and marine turbine blades, nacelles, oil and gas flexible risers.
Nondestructive testing (NDT) is routinely used in the nuclear, rail, aerospace and automotive industries to search for flaws in components. A signal from the flaw, recorded by the NDT device, will vary from measurement to measurement. The sources of this innate signal variation can be categorized into intrinsic, human and application factors. This variation, especially when searching for flaws that are at the limits of the NDT detection capabilities, can result in a failure to detect a flaw. If the inspected components are safety critical, the capability of NDT system to find flaws must be determined in order to avoid the catastrophic consequences of a missed flaw. The NDT system capability to detect flaws is expressed in terms of reliability. The probability of detection (POD) curve is a widespread tool to quantify the reliability of NDT. The POD is determined by series of experiments on specimens containing a range of flaws with known characteristics. The production of a sufficient number of these flaws is time consuming and expensive. In this paper, a multi-parameter POD model that uses both simulation and experimental measurements to calculate the POD curves will be presented. Simulation is used to assess the intrinsic capability of the NDT system and the variability in the system is estimated from experimental measurements. The POD calculated with the multi-parameter model is more comprehensive than the one calculated with the traditional model and the number of costly experiments needed is reduced.