Storage of large amounts of grain post-harvest is common during drying, distribution and preservation of crops. During storage, where grain is usually held in a large metallic container or bin, changes in temperature, moisture, and insect infestation can cause grain to spoil annual post-harvest crop losses are estimated up to 30% in some countries while Canadian losses of 2% exceed a billion dollars. Currently, locally-sensitive temperature and moisture sensors are a common way to monitor grain bins. Sensors are generally strung on heavy duty cables that can withstand the forces generated when unloading grain. This monitoring method provides a coarse sampling of the storage environment due to system cost and the fact that using many sensor cables would require significantly reinforcing the bin. Further, these cables are not suitable for monitoring stored crops that are dried by a combination of stirring and aeration.
Over the past four years, I have developed multiple electromagnetic imaging based grain-monitoring systems with the goals of overcoming the deficiencies of existing sensor technology and allowing farmers and distributors a robust way to preserve our food stores and increase revenue. The proposed technology aims to produce global, quantitative images of grain properties throughout the bin from measurements taken by a few side-mounted antennas used to interrogate the bin contents.
To develop this technology intensive research was put into the design of low profile, robust antennas as well as numerical analysis of the effects of different field distributions within conducting boundaries. Both electric and magnetic field sensitive antennas were built and tested in small lab-scale as well as full-scale grain bins to experimentally evaluate the performance of such imaging system. This thesis provides details on different system designs and analysis and describes the advantages and challenges associated with the techniques described. / October 2016
Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/31503 |
Date | 20 June 2016 |
Creators | Asefi, Mohammad |
Contributors | LoVetri, Joe (Electrical and Computer Engineering), Bridges, Greg (Electrical and Computer Engineering), Paliwal, Jitendra (Biosystems Engineering), Popovic, Milica (University of McGill) |
Source Sets | University of Manitoba Canada |
Detected Language | English |
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