Implementation of a mechanics-based system for estimating the strength of timber

TitleImplementation of a mechanics-based system for estimating the strength of timber
Publication TypeJournal Article
Year of Publication2004
AuthorsSaravi, A., P. D. Lawrence, and F. Lam
JournalInstrumentation and Measurement, IEEE Transactions on
Volume53
Pagination284 - 292
Date Publishedapr.
ISSN0018-9456
Keywordsboard strength, correlation r2, destructive strength testing, destructive testing, feature combination, feature determination, feature extraction, feature prediction, feature selection, finite element methods, intelligent mechanics-based system, lumber grading system, lumber strength, lumber-grading system, maximum stress concentration, MSC feature, nondestructive testing, stress field generation, stress fields, tensile strength, timber strength estimation, wood, X-ray image, X-ray-extracted geometric features
Abstract

The most accurate way of determining the strength of lumber requires destructive testing. 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 finite element methods to generate associated stress fields. The stress fields were then fed to a feature-extracting-processor, which produced 26 strength predicting features. The best strength predicting features were determined from the coefficient of determination (correlation r2) between the features and actual strengths of the boards. The coefficients of determination of each feature (or combination of features), with the actual strength of the board, were calculated and compared. A coefficient of determination of 0.4158 was achieved by using a longitudinal (along the local grain angle) maximum stress concentration (MSC) feature to predict the estimated strength of lumber.

URLhttp://dx.doi.org/10.1109/TIM.2003.822474
DOI10.1109/TIM.2003.822474

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