Application of Metal Magnetic Memory Testing Technology in Pipeline Defect
Abstract
The metal magnetic memory testing technology can detect the stress concentration area of ferromagnetic materials, and then diagnose the micro defects and early damage. Based on the principle of artificial neural network, 3 single output three layer BP neural networks are designed by using metal magnetic memory testing technology. In this paper, the stress concentration, crack and other pipeline defects are detected and identified. The experimental results show that the recognition rate of pipeline defects is 97.5%.
Keywords
Metal Magnetic Memory Testing, Artificial Neural Network, Stress Concentration, Signal Characteristics.
DOI
10.12783/dtetr/ecame2017/18393
10.12783/dtetr/ecame2017/18393
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