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

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.