Identifying the strength of boards using mixed signals of MOE and X-ray image

TitleIdentifying the strength of boards using mixed signals of MOE and X-ray image
Publication TypeConference Paper
Year of Publication2003
AuthorsSaravi, A. A., P. D. Lawrence, and F. Lam
Conference NameImage and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the 3rd International Symposium on
Pagination1003 - 1008 Vol.2
Date Publishedsep.
Keywordsboard strength estimation, feature extracting processor, feature extraction, FEM, finite element analysis, finite element method, intelligent mechanics-based lumber grading system, modulus of elasticity, MOE, tensile strength, X-ray imaging, X-ray-extracted geometric feature

The most accurate way of identifying the strength of lumber requires destructive testing which is clearly not useful for production of lumber. An intelligent mechanics-based lumber grading system was developed to provide a better estimation of the strength of a board nondestructively. This system processed X-ray-extracted geometric features (of 1080 boards that eventually underwent destructive strength testing) by using physical model of Lumber based on finite element methods (FEM) to generate associated stress fields. The stress fields were then fed to a feature extracting processor, which produced one strength predicting feature. MOE profiles were processed separately and a feature based on the minimum point in the MOE averaged profile, which was cut 15% from each ends. Then, the two MOE and X-ray extracted features were combined (with 4 different algorithms) to a single feature to estimate the strength of the boards. Applying 4 different algorithms to a database of more than 1000 boards, the strength of boards is estimated and coefficient of determination of 0.6365, 0.6510, 0.6514, and 0.6545 are achieved for different algorithms respectively.


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