신경망 기법을 이용한 1축 잔류응력장에서 구멍뚫기법의 구멍편심 오차 보정 = Compensation of the Error due to Hole Eccentricity of Hole-drilling Method in Uniaxile Residual Stress Field Using Neural Network

다국어 초록 (Multilingual Abstract)

The measurement of residual stresses by the hole-drilling method has been commonly used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, the error due to the hole eccentricity is compensated using the neural network. The neural network has trained training examples of normalized eccentricity, eccentric direction and direction of maximum stress at eccentric case using backpropagation learning process. The trained neural network could compensated the error of measured residual stress in experiments with hole eccentricity. The proposed neural network is very useful for compensation of the error due to hole eccentricity in hole-drilling method.