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Artigos de revistas sobre o assunto "Hardwood log defects":
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Miller, Gary W., Aaron T. Graves, Kurt W. Gottschalk e John E. Baumgras. "Accuracy of Tree Grade Projections for Five Appalachian Hardwood Species". Northern Journal of Applied Forestry 25, n.º 1 (1 de março de 2008): 45–51. http://dx.doi.org/10.1093/njaf/25.1.45.
Abstract The potential value increase of individual trees is an important factor in planning effective forest management strategies. Similar to other investments, trees with high potential value increase are retained and allowed to grow, and those with relatively low potential value increaseare harvested so that the proceeds may earn a higher rate of return elsewhere. Tree grade is used to assess the quality and value of wood within a tree; thus, projecting tree grade is an integral part of estimating potential value increase. This study measured the accuracy of projected treegrades over a period of 12–15 years for 588 black cherry, 404 northern red oak, 167 red maple, 191 white and chestnut oaks, and 450 yellow-poplar sawtimber trees in both thinned and unthinned stands. Projected grade was based on surface defects and percent volume deductions for sweep,crook, and rot at the time of the projection with the assumption that the threshold dbh for the highest possible grade would be reached in the future. This approach allows the forest manager to make grade projections based on what is visible and measurable on the tree, even if the tree iscurrently too small to qualify for higher grades. In general, grade projections were somewhat accurate, with 9% of trees higher than the projected grade, 80% projected correctly, and 11% lower than the projected grade. Trees that had a lower-than-projected grade usuallyexhibited additional deductions for percent cull volume and/or new epicormic branches. Grade projections were less accurate for larger, higher-quality trees because requirements for the top grade are more constraining and sensitive to changes in butt log characteristics than lower grades.For black cherry and northern red oak, grade projections in thinned stands were less accurate compared with unthinned stands because of resulting logging wounds or new epicormic branches.
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McGavin, Robert L., John McGrath, Chris Fitzgerald, Chandan Kumar, Chris Oliver e Alex Lindsay. "Sawn timber and rotary veneer processing and grade recovery investigation of northern Australian plantation grown African mahogany". BioResources 16, n.º 1 (26 de janeiro de 2021): 1891–913. http://dx.doi.org/10.15376/biores.16.1.1891-1913.
Over half of the large African mahogany plantation estate in northern Australia has reached the mid-point of the target rotation length of 20 to 25 years. As such, there is increasing interest in understanding the potential volume and grade qualities recovered from these young trees using different processing methods. The objective of this study was to compare the recovery rates and product grade quality for rotary veneer using spindleless lathe technology and sawn boards using traditional sawing techniques. Net veneer recovery ranged between 42% and 55% of log volume, with most veneers being limited to D-grade. Compression, surface roughness, and grain breakout were the most prominent defects limiting veneer grade. The sawn-dried-dressed recovery was low, with less than 20% of the log volume representing a potential saleable product. The small log diameter combined with defects including wane, heart shake, pith, and knots reduced the potential recovery. A high presence of sawn board distortion was observed that negatively impacted the efficiency of sawn timber processing along with product recovery. While low, the recovery of veneers and sawn timber from young African mahogany was like other young plantation grown hardwoods.
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Xu, Feng, Yunfei Liu, Xiping Wang, Brian K. Brashaw, Lon A. Yeary e Robert J. Ross. "Evaluating internal condition of hardwood logs based on AR-minimum entropy deconvolution combined with wavelet based spectral kurtosis approach". Holzforschung, 15 de agosto de 2020. http://dx.doi.org/10.1515/hf-2020-0053.
AbstractThe aim of this research was to explore the potential of acoustic impact test to evaluate the condition of hardwood logs in regard to internal decay, void, crack and defect ratio using an acoustic signal separation and enhancement algorithm. Longitudinal acoustic signals were obtained from 15 logs of four hardwood species through acoustic impact testing. The defect components were separated from the acoustic response signals and enhanced based on the autoregressive minimum entropy deconvolution (AR-MED) method, and from which the kurtosis was derived and used as the global feature parameter for evaluating the internal condition of logs. Compared with the acoustic velocity obtained directly from the original signal, the kurtosis was deemed to be a more powerful predictor of log defect ratio with higher coefficient of determination (R2 = 0.89) and was not affected by log species. To identify the type of defects, a complex Morlet wavelet-based spectral kurtosis (SK) method was proposed. The research results indicated that the SK can not only determine the type and primary and secondary major defects, but also be able to identify those that were not detectable by global acoustic parameters.
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Thomas, R. "Modeling the relationships among internal defect features and external Appalachian hardwood log defect indicators". Silva Fennica 43, n.º 3 (2009). http://dx.doi.org/10.14214/sf.199.
Thomas, Liya. "Automated Detection of Surface Defects on Barked Hardwood Logs and Stems Using 3-D Laser Scanned Data". Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/29038.
This dissertation presents an automated detection algorithm that identifies severe external defects on the surfaces of barked hardwood logs and stems. The defects detected are at least 0.5 inch in height and at least 3 inches in diameter, which are severe, medium to large in size, and have external surface rises. Hundreds of real log defect samples were measured, photographed, and categorized to summarize the main defect features and to build a defect knowledge base. Three-dimensional laser-scanned range data capture the external log shapes and portray bark pattern, defective knobs, and depressions.
The log data are extremely noisy, have missing data, and include severe outliers induced by loose bark that dangles from the log trunk. Because the circle model is nonlinear and presents both additive and non-additive errors, a new robust generalized M-estimator has been developed that is different from the ones proposed in the statistical literature for linear regression. Circle fitting is performed by standardizing the residuals via scale estimates calculated by means of projection statistics and incorporated in the Huber objective function to bound the influence of the outliers in the estimates. The projection statistics are based on 2-D radial-vector coordinates instead of the row vectors of the Jacobian matrix as proposed in the statistical literature dealing with linear regression. This approach proves effective in that it makes the GM-estimator to be influence bounded and thereby, robust against outliers.
Severe defects are identified through the analysis of 3-D log data using decision rules obtained from analyzing the knowledge base. Contour curves are generated from radial distances, which are determined by robust 2-D circle fitting to the log-data cross sections. The algorithm detected 63 from a total of 68 severe defects. There were 10 non-defective regions falsely identified as defects. When these were calculated as areas, the algorithm locates 97.6% of the defect area, and falsely identifies 1.5% of the total clear area as defective. Ph. D.
Livros sobre o assunto "Hardwood log defects":
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Chang, Sun Joseph. External and internal defect detection to optimize cutting of hardwood logs and lumber. Beltsville, MD: U.S. Dept. of Agriculture, National Agricultural Library, Technology Tranfer Information Center, 1992.
Trabalhos de conferências sobre o assunto "Hardwood log defects":
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Thomas, Edward, Liya Thomas, Lamine Mili, Roger W. Ehrich, A. Lynn Abbott e Clifford Shaffer. "Primary detection of hardwood log defects using laser surface scanning". In Electronic Imaging 2003, editado por Martin A. Hunt e Jeffery R. Price. SPIE, 2003. http://dx.doi.org/10.1117/12.474036.
Sarigul, Erol. "Nondestructive rule-based defect detection and identification system in CT images of hardwood logs". In The 27th annual review of progress in quantitative nondestructive evaluation. AIP, 2001. http://dx.doi.org/10.1063/1.1373989.
Relatórios de organizações sobre o assunto "Hardwood log defects":
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Thomas, R. Edward. Hardwood log defect photographic database, software and user's guide. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station, 2009. http://dx.doi.org/10.2737/nrs-gtr-40.
Thomas, Ed. Equations for predicting internal log defect measurements of common Appalachian hardwoods. Madison, WI: U.S. Department of Agriculture, Forest Service, Forest Products Laboratory, 2016. http://dx.doi.org/10.2737/fpl-rp-687.
