Assessment of machine learning algorithm-based grading of Populus x euramericana I-214 structural sawn timber
نویسندگان
چکیده
The efficiency of visual grading standards applied to structural timber is often inappropriate, and properties are either under or over-graded. Although not included in the current UNE 56544 standard, machine learning algorithms represent a promising alternative grade timber. general aim this research was compare performance based on defects, non-destructive techniques sawing systems (“cut type”) with 56544:1997 order predict qualifying Populus x euramericana I-214 Visual evaluation, ultrasound vibrational testing, register (radial, tangential mixed) were characterize 945 beams. In addition, retrieve actual physical-mechanical values, density static bending destructive testing (EN-408:2011 + A1:2012) also carried out. Several then used beams, their predictive accuracy compared that grading. To do so, three scenarios considered: first scenario which only variables used; second “cut type” included; third additional considered. Results showed poor level 56544:1997, an apparent mismatch between strength values assigned for each (established by EN 338 standard) values. On opposite, all performed better than may thus be deemed as tools.
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ژورنال
عنوان ژورنال: Engineering Structures
سال: 2022
ISSN: ['0141-0296', '1873-7323']
DOI: https://doi.org/10.1016/j.engstruct.2021.113826