title: Microwave Imaging of Cotton Bales.
abstract: Modern moisture restoration systems are increasingly capable of adding water to cotton bales. However, research has identified large variations in internal moisture within bales that are not readily monitored by current systems. While microwave moisture sensing systems can measure average bale moisture, this can be deceptive where water is unevenly distributed. In some cases, localized internal moisture levels exceed 7.5%, the upper safe limit for cotton bale storage, as determined by the USDA, as above this level, bales degrade and lose value. A high proportion of stored bales containing excess moisture have been discovered throughout the US in increasing numbers over the past several seasons, making the detection and prevention of this occurrence a critical goal. Previous research by the authors resulted in the development of microwave moisture-sensing technology. The current study examines an extension to this technology to allow for detailed cotton bale moisture imaging. The new technique incorporates a narrow beam imaging antenna coupled to a tomographic imaging algorithm. The imaging technique was able to resolve small (< 1 cm) high-permittivity structures against a low permittivity background. Moreover, the system was able to identify structures of known permittivity with high accuracy (coefficient of determination (r²) > 0.99). In preliminary testing on a wet commercial UD bale, the technique was able to accurately image and resolve the location of the pre-placed internal wet layer.
authors.affiliation: United States Department of Agriculture, Agricultural Research Services, Cotton Production and Processing Research Unit, Lubbock, TX. USA. mathew.pelletier@ars.usda.gov.
authors.forename: Mathew G
authors.initials: MG
authors.lastname: Pelletier
authors.affiliation: Cotton Incorporated, Director Agricultural Research, Cary, NC, USA. ebarnes@cottoninc.com.
authors.forename: Edward M
authors.initials: EM
authors.lastname: Barnes
keywords: Cotton; Image processing; Inverse Solution; Machine vision; Moisture; Sensing; Tomography