Discovering data flow discords for enhancing noise immunity of acoustic-emission testing

A new approach has been suggested to revealing acoustic-emission data-flow discords that are related to the formation and growth of flaws. The discords were discovered using a statistical criterion and the Caterpillar SSA principal components method. The approach has proved its consistency when tested on realistic acoustic-emission data-flow models.