INVESTIGATION OF ARTIFICIAL NEURAL NETWORK PATTERN RECOGNITION OF ACOUSTIC EMISSION SIGNALS FOR PRESSURE VESSELS

The artificial neural network pattern recognition technique was employed to analyze AE source signals of pressure vessels in site. A concept for quantitative analysis of AE sources of pressure vessels by artificial neural network classification was given and the method for evaluating the severity of an AE source was thus found. The artificial neural network designed and trained gave the percentage of crack growing, slag inclusion cracking, residual stress releasing and structure rubbing signals for a complex AE source. The result made it possible to evaluate the safety condition of pressure vessels by acoustic emission testing.