Neural network applications in determining the fatigue crack opening load

Abstract

A neural network approach is developed to determine the crack opening load from differential displacement signal curves. A backpropagation neural network of three layers was employed. In order to examine the measurement accuracy and precision of the neural network method, computer simulation was extensively performed for various combinations of crack opening levels and signal-to-noise (S/N) ratios. For all crack opening levels examined, the method shows good accuracy and precision. The proposed method was applied in practical to constant amplitude loading tests and is found to provide good results.