Published November 2002 | Version v1
Journal article

Prediction of error due to eccentricity of hole in hole-drilling method using neural network

  • 1. Sungkyunkwan Univ., Suwon (Korea, Republic of)

Description

The measurement of residual stresses by the hole-drilling method has been 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, we obtained the magnitude of the error due to eccentricity of a hole through the finite element analysis. To predict the magnitude of the error due to eccentricity of a hole in the biaxial residual stress field, it could be learned through the backpropagation neural network. The prediction results of the error using the trained neural network showed good agreement with FE analyzed results

Additional details

Publishing Information

Journal Title
KSME International Journal
Journal Volume
16
Journal Issue
11
Series
12 refs, 13 figs, 3 tabs
Journal Page Range
p. 1359-1366
ISSN
1226-4865

INIS

Country of Publication
Korea, Republic of
Country of Input or Organization
Korea, Republic of
INIS RN
36106269
Subject category
S36: MATERIALS SCIENCE;
Descriptors DEI
DRILLING; FATIGUE; FINITE ELEMENT METHOD; HOLES; NEURAL NETWORKS; NUMERICAL ANALYSIS; RESIDUAL STRESSES; STRAIN GAGES; WAVE PROPAGATION
Descriptors DEC
CALCULATION METHODS; MATHEMATICAL SOLUTIONS; MATHEMATICS; MEASURING INSTRUMENTS; MECHANICAL PROPERTIES; NUMERICAL SOLUTION; STRESSES