Identifying strength of boards using mechanical modeling and a Weibull-based 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 seven strength predicting features. The best strength predicting features were determined from the coefficient of determination (r²) between the features and actual strengths of the boards. A coefficient of determination of 0.4732 was achieved by using a Weibul-based feature and using a linear transformation of the same feature to predict the estimated strength, respectively.