Softwood Log Shape Modelling with Shadow Scanners
Keywords:Log model, scanning, mathematical representation, accuracy
AbstractThis paper describes and evaluates new and existing models for exterior log geometry. Compatibility with 1, 2, 3, and 4-axis shadow scanners determined which models were selected for evaluation. Models were considered for potential use in sawmilling process simulation and optimization. The accuracy evaluation compared models based upon lost and added fiber percentages. All models tended to overestimate log cross section area. Popular circular and elliptical models provided the poorest accuracy. Elliptical models used with 2-axis or 3-axis scanners generated up to 8% lost fiber and up to 15% added fiber. The 3-axis dyadic and Chaikin models provided the best overall performance: lost fiber under 3.5% and added fiber under 13%. Results from the evaluation recommend a 3-axis scanner system for automatic positioning and breakdown optimization. The small benefit obtained from 4-axis models does not justify their use. Other technologies are recommended where better accuracy is needed.
Alleckson, T. D., H. B. Sanders, A. J. Koivo, and T. J. Williams. 1980. Studies on the optimum production of lumber by computer positioning of logs in sawmills. Report number 79, Purdue Laboratory for Applied Industrial Control, Purdue University, Lafayette, IN.nChaikin, G. M. 1974. An algorithm for high speed curve generation. Computer Graphics and Image Processing 3: 346-349.nColeman, H. W., and W. G. Steele, Jr. 1989. Experimentation and uncertainty analysis for engineers. Wiley, New York, NY.nDrake, E., and L. G. Johansson. 1985. Log positioning—A method for evaluating the possible increase of yield. Paper presented at the 8th Wood Machining Seminar, October 1985, Forest Product Laboratory, Richmond, Virginia.nDubuc, S. 1986. Interpolation through an iterative scheme. J. Math. Anal. Appl. 114(1): 185-204.nFunck, J. W., A. G. Maristany, D. A. Butler, and C. C. Bremer. 1989. Resolution in machine vision — What is it and why is it important? Proceedings of the 3rd International Conference on Scanning Technology in Sawmilling, San Francisco, CA. Pp. XIII-1, XIII-11.nGeerts, J. M. P. 1984. Mathematical solution for optimising the sawing pattern of a log given its dimensions and its defect core. N.Z. J. Forest. Sci. 14(1): 124-134.nHarless, E. G. T. 1990. Impact of defect locations on lumber value yield of hardwood logs. Ph.D. dissertation, Mississippi State University, Mississippi State, MS.nHitrec, V., B. Marijan, and K. Segotic. 1990. A model of computer aided optimization of sawing logs. Proceedings of the IUFRO XIX Congrès Mondial, août 1990, Montréal, Canada. Pp. 216-224.nLeban, J. M., and G. Duchanois. 1990. SIMQUA: Un logiciel de simulation de la qualité du bois. Ann. Sci. For. 47: 483-493.nLewis, D. W. 1985a. Yield losses from sawmill scanner error. Research paper FPL-459, USDA Forest Service, Madison, WI.nLewis, D. W. 1985b. Sawmill simulation and the Best Opening Face System, A user's guide. General Tech. Rep. FPL-48, USDA Forest Service, Madison, WI.nManess T. C., and D. M. Adam. 1991. The combined optimization of log bucking and sawing strategies. Wood Fiber Sci. 23(2): 296-314.nMoen, D. A. 1991. Three-dimensional profile log scanning and optimization for high recovery and production from small logs. Proceedings of the 4th International Conference on Scanning Technology in the Wood Industry, Burlingame, CA. Pp. Moen-1, Moen-9.nMongeau, J. P. 1990. Propriétés de l'interpolation itérative. Ph.D. dissertation, Montréal University, Montreal, Quebec. Canada.nOccena, L. G., and J. M. A. Tanchoco. 1988. Computer graphics simulation of hardwood log sawing. Forest Prod. J. 38(10): 72-76.nRickford, E. N. 1987. Evolution of scanning and computer optimization in sawmilling. Proceedings of the 2nd International Conference on Scanning Technology in Sawmilling, San Francisco, CA. Pp. I-1, I-23.nRickford, E. N. 1989. Scanning for true shape. Proceedings of the 3rd International Conference on Scanning Technology in Sawmilling, San Francisco, CA. Pp. II-1, II-41.nReynolds, H. W. 1970. Sawmill simulation: Data instructions and computer programs. Research Paper NE-152, USDA Forest Service, Northeast Forest Exp. Sta., Princeton, WV.nSampson, S. 1990. Modélisation graphique du débitage du bois. M.Sc. dissertation, Laval University, Quebec, Canada.nTodokori, C. L. 1988. SEESAW: A visual sawing simulator, as developed in version 3.0. NZ J. Forest. Sci. 18(1): 116-123.nWagner F. G., and F. W. Taylor. 1975. Simulated sawing with a chipping headrig. Forest Prod. J. 25(10): 24-28.nZeng, Y. 1991. Log breakdown using dynamic programming and 3-D log shape. M.Sc. dissertation, Oregon State University, Corvallis, OR.n
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