Quantifying and Improving the Reliability of NDE

Lead Research Organisation: Imperial College London
Department Name: Dept of Mechanical Engineering


Two basic approaches have been adopted by industry to establish a reliable Non Destructive Evaluation (NDE) procedure that is fit for purpose. 1. In aerospace and offshore, where many similar defects are found repeatedly through many inspections, the Probability of Detection approach can be used. This approach is based on well-founded receiver operating characteristics theory. 2. Where only a few defects are expected and each may be unique, as in the nuclear industry, then Technical Justification is used. This is a judicious mixture of trials, modelling and physically-based reasoning. The technical justification neither quantifies the likelihood of errors nor gives any guidance on the effectiveness of the inspection should any of these errors occurs. Our proposal will provide a methodology for identifying errors and for quantifying their effect on inspection reliability. A combination of Fault and Event Trees will be used to identify and quantify errors in the entire process. This will enable studies of how best to improve the reliability of any NDT technique within any NDE approach and therefore complements both the Probability of Detection and Technical Justification approaches. The novel aspects of this proposal are: 1. The cause-consequence approach carried through an entire NDT/NDE situation; 2. Making the maximum use of available data, in part through the use of Bayesian networks to establish the causal correctness of the Fault and Event trees without needing to acquire new data through either experiment or modelling; 3. Ensuring that the results are not biased by unwarranted tails in probability distributions of influencing factors; and 4. Development of a framework for any inspection task which is generic but can readily be customised for each specific application.Data libraries will form an important part of the output. A key measure of success will be the degree to which industry can use the tool created to identify cost-effective ways of improving the reliability of their NDT/NDE.


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