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Abstract

A system for mapping absolute acoustic noise intensity in a three-dimensional acoustic noise field, and using three-dimensional absolute noise intensities to infer operational or performance characteristics of components or structures within the monitored field. Localized noise sources are extracted using a distant array of transducers, and the absolute intensity can be measured even when totally masked by background noise at the transducer locations. The system includes an integrated sensor installation; a neural network detection system algorithm; a zoom system to precisely examine a small region in the steam generator vessel; a fuzzy logic system detection algorithm; and an expert detection system. The signal processing subsystem operates at three different levels of detection. At the top level of detection a trained neural network system monitors the vessel length for any indication of a leak. The proposed approach uses discriminators which do not require any beamforming of the sensor signals. The presence of a leak and its general location in the vessel is determined using a fuzzy logic expert system. The leak indications are passed to a second level of detection: a beamformed system which will monitor the indicated portion of the vessel. A third level of detection systematically monitors the tagged locations to determine if a leak is really present, remaining on the specific locations to detect a leak above the defined threshold to a high degree of accuracy. The actions to be taken will be controlled by a second fuzzy logic expert interface controller.

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