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Mechanical Fractionation of Biomass Feedstocks for Enhanced Pretreatment and Conversion
Published in Jaya Shankar Tumuluru, Biomass Preprocessing and Pretreatments for Production of Biofuels, 2018
Optical sorting is one such technology that is used widely in the mining, food, and pharmaceutical industries; however, it has not been tested with biomass feedstocks. Optical sorting is an automated process that uses the optical properties of particles to determine whether to “accept” or “reject” that individual particle. An image is taken of each particle moving down a conveyor, the image is analyzed by a computer, and depending upon the parameters set by the user, the particle is either allowed to proceed to the “accept” stream or the particle is hit with a jet of air and diverted into the “reject” stream. These sorters can be set to select particles based on size, shape, color, UV or IR characteristics, hyperspectral characteristics, or X-ray characteristics. Examples of some of the more simple optical sorting capabilities could include separation of bark from stemwood based on color or isolation of pine needles based on shape. Advanced separations could include the detection of specific chemical signatures such as carbohydrate content or lignin content, using UV, IR, or hyperspectral imaging. The capabilities of this technology in the bioenergy industry are yet to be fully realized.
Optical sorting of lignite and its effects on process economics
Published in International Journal of Coal Preparation and Utilization, 2018
Ergin Gülcan, Özcan Yıldırım Gülsoy
Numerous sensor types and machine configurations have been developed to satisfy the need for quality requirements, recycling, and efficient production for the mining and waste treatment industries (Anselmi and Harbeck 2000; Batchelo et al. 2016; Dehler 2003; John et al. 2015; Salter and Wyatt 1991; Von Ketelhodt 2009; Wotruba and Riedel 2006). The term “sensor-based sorting” (Cutmore and Eberhardt 2002) is also referred to as optical sorting, automated sorting, or photometric sorting (Schapper 1976). Optical sorting technology has a promising potential in the mineral beneficiation industry (Wotruba 2006). This equipment can be implemented to obtain preconcentrate or final product. In practice, optical sorting applications providing finished final product are rare and more preferable (Dehler 2003). On the other hand, in metal ore processing, the primary goal of optical sorting is to increase the head grade of ROM ore and to reduce the amount of the material sent to milling and further processing. Accordingly, Lessard, De Bakker, and McHugh (2014) emphasized that by implementing optical sorting significant capital savings could be achieved as a result of decreased material handling efforts (fuel and electricity), less milling, less crushing stages, smaller equipment sizing, less tailing treatment, reasonable chemical requirement in the case of flotation, and less ancillary operations. Additionally, optical sorting operations are flexible and can be performed in subsequent steps at varying sorting thresholds in order to obtain different product qualities (Ooms et al. 2010; Pascoe, Udoudo, and Glass 2010). A sorting threshold can simply be described as the “cut reflectance value” that directly affects the sorting products’ quality. In effect, the selective sorting with an optical sorter is related to the reflected/absorbed amount of electromagnetic radiation. This quantitative value is translated to a number ranging from 0 (all radiation is absorbed) to 255 (all radiation is reflected) when it is assessed on the gray scale.