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Design of a Tree Micro Drill Instrument to Improve the Accuracy of Wood Density Estimation.
- Source :
- Forests (19994907); Oct2023, Vol. 14 Issue 10, p2071, 16p
- Publication Year :
- 2023
-
Abstract
- To improve the estimation accuracy of wood density and study the linear correlation between drill feed resistance and wood density, a new micro drill instrument prototype that can simultaneously measure the rotation resistance and feed resistance of the drill needle was designed. The test tree species included hard and soft broad-leaved trees and coniferous trees, and the absolute dry density of each wood sample was measured. The drill resistance data were tested by our newly proposed prototype and a Resistograph 650-SC, and four linear models were established to define the relation between drill resistance and the absolute dry density of the wood. The results showed that (1) the statistical indicators of each model for our proposed prototype were better than the corresponding indicators of the Resistograph 650-SC for three of the four species tested; (2) the coefficient of determination of the linear regression model between the feed resistance of our proposed prototype and the absolute dry density of wood was 0.946; and (3) the statistical indicators of the model that included rotation resistance and feed resistance were better than those of the model that only including rotation resistance. Although the proposed prototype produced a competitive level of accuracy and explicitly demonstrated that including feed resistance improved wood density measurement accuracy, the prototype should be considered a first iteration as further hardware design changes and in-forest performance assessments across wider diverse set of test species are required before a conclusive evaluation can be rendered. [ABSTRACT FROM AUTHOR]
- Subjects :
- WOOD density
LUMBER drying
TREES
STATISTICAL models
REGRESSION analysis
Subjects
Details
- Language :
- English
- ISSN :
- 19994907
- Volume :
- 14
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- Forests (19994907)
- Publication Type :
- Academic Journal
- Accession number :
- 173264881
- Full Text :
- https://doi.org/10.3390/f14102071