Title | Real-time-intelligent system for estimating the strength of lumber using X-ray image |
Publication Type | Journal Article |
Year of Publication | 2004 |
Authors | Saravi, A., P. D. Lawrence, and F. Lam |
Secondary Authors | Villaneuva, J. J. |
Journal | Proceedings of the 4th IASTED International Conference on Visualization, Imaging, and Image Processing |
Pagination | 31–36 |
Abstract | A real-time-intelligent mechanics-based lumber grading system was developed to provide a better estimation of the strength of a board nondestructively in real-time. This system processed X-Ray-extracted geometric features (of 1080 boards that eventually underwent destructive strength testing) by using a physical model of lumber using a knowledge-based table (which is generated by an FEM model) to generate associated stress fields. The stress fields were then fed to a feature-extracting-processor which produced a single strength predicting feature. By applying two different algorithms to a database of more than 1000 boards, to estimate the strength of boards, a coefficient of determination of 0.4597, and 0.4763 were achieved for different algorithms respectively. |