DocumentCode
956358
Title
Implementation of a mechanics-based system for estimating the strength of timber
Author
Saravi, Albert ; Lawrence, Peter D. ; Lam, Frank
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada
Volume
53
Issue
2
fYear
2004
fDate
4/1/2004 12:00:00 AM
Firstpage
284
Lastpage
292
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.
Keywords
feature extraction; nondestructive testing; wood; MSC feature; X-ray image; X-ray-extracted geometric features; board 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; nondestructive testing; stress field generation; stress fields; tensile strength; timber strength estimation; Cameras; Computed tomography; Finite element methods; Helium; Humans; Intelligent systems; Nondestructive testing; System testing; Tensile stress; X-ray imaging;
fLanguage
English
Journal_Title
Instrumentation and Measurement, IEEE Transactions on
Publisher
ieee
ISSN
0018-9456
Type
jour
DOI
10.1109/TIM.2003.822474
Filename
1284857
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