Taking Advantage of Signal Processing Techniques for the Life Management of NPP Components

The long term management of nuclear power plants raises several major issues among which the aging management of key components ranks high, from both technical and economic points of view. In order to detect and characterize potential defects on cast components, a program of in-service inspections is carried out by non-destructive testing (NDT) methods. In general, defect detection is the first step of an inspection procedure. Should a defect be detected, the plant operator must evaluate whether the component should be replaced or repaired (now or later) and will be required to prove that the component still meets regulatory requirements. That is why the characterization of the defect in terms of locating and sizing is essential, especially when the proof relies on mechanical calculations. In this paper we provide an overview of advanced signal processing techniques based on regularization of inverse problems. Those techniques have a strong potential for improving defect positioning and sizing. This has already been demonstrated in several R&D studies in the field of radiography and ultrasonics, leading in some cases to expertise-oriented applications. After a presentation of the general principles, we detail how regularization can be applied to process eddy current probe signals and provide good estimates of the depth of small surface breaking defects. Encouraging laboratory results have been obtained so far, which may lead to re-consider the scope of the eddy current technique as presently used in the nuclear industry. For example, its eligibility as an alternative NDE method could be explored in cases dealing with this kind of defect, if ultrasonics failed to meet the required characterization performance.