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UBC Theses and Dissertations

Coarse-resolution CT scanning for sawmill logs sorting and grading An, Yuntao

Abstract

Significant economic advantage can be achieved by grading logs at the inlet of a sawmill so that they can be optimally processed to manufacture the highest possible value products from the available raw material. At present, log inspection is mainly based on visual observation of surface defects and optical measurement of external features. Such inspection is time-consuming and many quality-controlling features are not visible on the surface, thus very much prone to error. Computed Tomography (CT) has been extensively used as a medical diagnostic tool, and increasingly used for scientific and industrial research. In the wood industry, there is a growing interest in using the CT technique to assess the quality of logs entering a sawmill. Internal features of interest include knots, heartwood/sapwood boundary, rot and splits. Most commercially available CT scanning systems are modeled on medical designs and provide high spatial and density resolution. However, they are very complex and delicate and their cost is correspondingly high. The extreme scanning speed requirement, moderate affordability and severe working environment in a sawmill make medical style CT scanner unsuited for sorting and grading applications. Log scanning is not as challenging as medical scanning because most targeted internal features are fairly large and have specific geometrical shapes. A suitable log scanner for this task must be simple, rugged and economical. Based on these thoughts, a novel coarse-resolution CT scanning approach is developed in this thesis. The research work includes designing and constructing a practical CT log scanner, developing coarse-resolution log models, customizing log CT data processing techniques and designing and implementing efficient reconstruction algorithms. The prototyped log scanner and the coarse-resolution density reconstruction results will be demonstrated in this thesis. Such reconstructions reveal internal features inside the log and provide rich information such as knot size/location, sapwood/heartwood extent, localized and averaged internal densities. The results also compare well with CT reconstructions using the same measurement with conventional filter-back-projection algorithm. The good comparison gives confidence in the usefulness and applicability of the proposed approach for practical sawmill logs sorting and grading application in the future.

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Attribution-NonCommercial-NoDerivatives 4.0 International

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