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Analysis of Acoustic Emission Testing Data using Neural Networks

The Kohonen SOM neural network can be used to classify or sort acoustic emission parameter data into patterns or groupings typically associated with source mechanisms in the material involved. The backpropagation neural network, on the other hand, can correlate the AE failure mechanism data humps that comprise the amplitude histograms with ultimate strengths or loads in various metal and composite structures, burst pressures in composite pressure vessels, and even fatigue lives of metallic components, usually from low proof load AE data.

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