Improving the quality of sorting wood waste is the main problem in the timber industry from the point of view of saving energy resources and preserving the environment, associated with the intensity of forest harvesting. Depending on the required quality characteristics, the sorting of wood chips makes it possible to determine their further use in production or utilization as a fuel. This paper presents the results of the development of a novel approach to sorting wood chips on a conveyor belt using machine learning and scanning technology. The proposed methodology includes functions to analyze the fractional size distribution among wood chips and rot detection. It shows that once a defective unit is detected, the quality control system will automatically remove it from the conveyor belt while it is moving. The minimization of wood waste will reduce logging intensity and increase the profitability of lumber enterprises.
Given the upward trend of deforestation in the world, improving the quality of wood waste sorting operations is a major challenge in forestry from the perspective of energy saving and environmental conservation. The quality of wood chips defines their further application, whether it is production or fuel. The second case study presents a new approach to the problem of sorting wood chips for increasing their quality using machine learning and laser scanning technology. The proposed methodology includes functions to analyse the fractional size distribution among wood chips and rot detection. It shows that once a defective chip is detected, the quality control system will automatically remove it from the conveyor belt while it is moving. The minimization of wood waste will reduce logging intensity and increase the profitability of lumber enterprises.
The paper presents a novel approach to the problem of utilizing wood chips as a valuable raw material. It shows how advances in machine vision can enable the conversion of wood chips from waste to a valuable resource. Empirical dependencies that are used to calculate the slip velocity of wood chips on the walls of the tank have been obtained. The problems of particle–fluid and particle–particle interactions within the flow are solved. Findings may be applied not only in countries with traditionally developed wood industries but also in many others.
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