Acoustic sorting models for improved log segregation

Xiping Wang, Steve Verrill, Eini Lowell, Robert J. Ross, Vicki L. Herian

Research output: Contribution to journalArticle

16 Scopus citations

Abstract

In this study, we examined three individual log measures (acoustic velocity, log diameter, and log vertical position in a tree) for their ability to predict average modulus of elasticity (MOE) and grade yield of structural lumber obtained from Douglas-fir (Pseudotsuga menziesii [Mirb. Franco]) logs. We found that log acoustic velocity only had a moderate correlation with average MOE of the lumber produced from the logs (R2 = 0.40). Log diameter had a weak correlation with average lumber MOE (R2 = 0.12). Log vertical position in a tree was found to have a relatively good relationship with lumber MOE (R2 = 0.57). Our analysis also indicated that the combinations of log acoustic velocity and log diameter or log acoustic velocity and log position were better predictors of average lumber MOE and lumber visual grade yield than log acoustic velocity alone. For sorting best quality logs, multivariable models were more effective than the velocity-alone model; however, for sorting poorest quality logs, the velocity-alone model was as effective as multivariable models.

Original languageEnglish (US)
Pages (from-to)343-352
Number of pages10
JournalWood and Fiber Science
Volume45
Issue number4
StatePublished - Oct 1 2013

Keywords

  • Acoustic velocity
  • Log diameter
  • Log position
  • Log sorting
  • Lumber
  • Modulus of elasticity
  • Visual grade

Fingerprint Dive into the research topics of 'Acoustic sorting models for improved log segregation'. Together they form a unique fingerprint.

  • Cite this

    Wang, X., Verrill, S., Lowell, E., Ross, R. J., & Herian, V. L. (2013). Acoustic sorting models for improved log segregation. Wood and Fiber Science, 45(4), 343-352.