New methods of leak detection and location by acoustic emission.

Summary Real-time monitoring of pressurized water nuclear power plant piping systems is moving towards the integration of numerical processing systems. In this respect, the acoustic emission method shows promising performances. Its principle is based on the passive listening of noises emitted by internal microdisplacements of a material under constraints which propagate in the form of elastic waves. The small amount of a priori information available about leakage signals has led us to deepen our understanding of the physical phenomena underlying the generation of noise induced by a flow. We gather all these results in the form of a leakage model linked to the geometry and the type of flow of the crack. The detection and localization problems are formulated according to the maximum likelihood principle. In detection, methods based on similarity information (correlation, tricorrelation) seem to give better results than classical methods (rms, envelope, filter bank). For localization, we propose a range of classical (generalized intercorrelation) and innovative (convolution, adaptive, higher order) methods. A last part is devoted to the study of higher order statistics. The analysis of estimators of higher order quantities for a family of nonlinear non-Gaussian random processes, the improvement of the performance of nonlinear prediction, the choice of an optimal order are discussed in simple analytical cases. Finally, some applications to leakage signals are presented.