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Combining acoustic and laser scanning methods to improve hardwood log segregation

Informally Refereed
Authors: Xiping Wang, Ed Thomas, Feng Xu, Yunfei Liu, Victor Krause, Brian K. Brashaw, Robert J. Ross
Year: 2017
Type: Paper (invited, offered, keynote)
Station: Forest Products Laboratory
Source: In: Wang, X.; Senalik, C.A.; Ross, R.J., eds. Proceedings, 20th international nondestructive testing and evaluation of wood symposium. Gen. Tech. Rep. FPL-GTR-249. Madison, WI: U.S. Department of Agriculture, Forest Service, Forest Products Laboratory: 433-448.

Abstract

The objective of this research was to examine the technical feasibility of combining acoustic wave data with high-resolution laser scanning data to improve accuracy of hardwood log defect detection and segregation. Using acoustic impact testing and high-resolution laser scanning techniques, 21 yellowpoplar logs obtained from the central Appalachian region were evaluated for internal and external defects. These logs were then sawn into boards, and the boards were visually graded based on National Hardwood Lumber Association grading rules. The response signals of the logs from acoustic impact testing were analyzed through moment analysis and continuous wavelet transform to extract time domain and frequency domain parameters. The results indicated that acoustic velocity, time centroid, damping ratio, as well as the combined time and frequency domain parameters are all effective quality predictors for segregating low-end logs. Acoustic data combined with high-resolution laser scanning data provide a more complete picture of the log in terms of size, shape, surface defects, and degree of soundness. Indications of “soundness” in a particular log allow the internal prediction system to flag suspicious defects as potentially unsound. Thus, a combined system would be able to discriminate much more exactly with respect to log quality and potential lumber recovery than either method independently.

Keywords

Acoustic velocity, damping ratio, impact testing, laser scanning, log defects, wavelet analysis, yellow-poplar

Citation

Wang, Xiping; Thomas, Ed; Xu, Feng; Liu, Yunfei; Krause, Victor; Brashaw, Brian K.; Ross, Robert J. 2017. Combining acoustic and laser scanning methods to improve hardwood log segregation. In: Wang, X.; Senalik, C.A.; Ross, R.J., eds. Proceedings, 20th international nondestructive testing and evaluation of wood symposium. General Technical Report. FPL-GTR-249. Madison, WI: U.S. Department of Agriculture, Forest Service, Forest Products Laboratory: 433-448.
https://www.fs.usda.gov/research/treesearch/56943