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ARS Home » Southeast Area » Athens, Georgia » U.S. National Poultry Research Center » Quality and Safety Assessment Research Unit » Research » Publications at this Location » Publication #334883
Title: Density-independent algorithm for sensing moisture content of sawdust based on reflection measurements

Author
item SAKOL, JULRAT - Oak Ridge Institute For Science And Education (ORISE)
item Trabelsi, Samir

Submitted to: Biosystems Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/6/2017
Publication Date: 4/24/2017
Citation: Sakol, J., Trabelsi, S. 2017. Density-independent algorithm for sensing moisture content of sawdust based on reflection measurements. Biosystems Engineering. 158:102-109.

Interpretive Summary: The production of pelleted biomass represents a significant emerging industry in the United States. Solid biomass can be formed from the waste products of many different natural and manufactured products, including sawdust from lumber mills. Moisture content of sawdust is an important factor in determining its behavior in handling, pelleting, and value determination. Dielectric properties are those electrical characteristics of materials that determine their interaction with electric fields, and they have been found useful for sensing the moisture content of such materials. New techniques are needed for sensing or measuring the dielectric properties of materials to improve or provide moisture-sensing equipment for practical applications in agriculture and related industries. This paper describes studies on use of a new technique and type of device for sensing the microwave dielectric properties of sawdust from which moisture content can be rapidly determined. It involves microwave device waveguide components fabricated from double sided substrate material (sheet of dielectric material copper-clad on both sides) similar to PC cards. It uses an open-ended waveguide aperture to sense the dielectric properties of materials placed in contact with the open-ended waveguide aperture. A density-independent algorithm for determining moisture content of sawdust based on a microwave reflection technique was developed and tested. The technique proposed in this paper allows one to determine the moisture content of sawdust from measurement of the dielectric properties determined from measurement of reflections from the new microwave sensing device at a single frequency. The density-independent moisture calibration function based on either moist material bulk density or dry material bulk density provided reliable moisture content measurements. Standard errors of performance for moisture prediction in sawdust samples by using either function were very satisfactory. The reflection-based algorithm, coupled with the low cost of the sensing device, shows potential for use of this method for in-process moisture determination in sawdust during the pelleting operation where moisture content ranges from 10% to 20%. These findings support further work aimed at implementing a microwave moisture meter in an industrial pelleting process, providing benefits for the biomass industry and consumers of biomass products.

Technical Abstract: A density-independent algorithm for moisture content determination in sawdust, based on a one-port reflection measurement technique is proposed for the first time. Performance of this algorithm is demonstrated through measurement of the dielectric properties of sawdust with an open-ended haft-mode substrate-integrated waveguide (HMSIW) sensor. For accurate measurement of the dielectric properties of sawdust, the HMSIW sensor was calibrated by using a three-material calibration technique, with air, water and 25% ethanol aqueous solution. For moisture determination, a density-independent calibration function expressed in terms of the dielectric properties was used. Both moist and dry bulk densities were considered for the complex-plane representation of the dielectric properties. Results of moisture prediction, relative to each complex-plane representation, are compared at 5 GHz and 23 °C.