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Using radio frequency spectral measu...

Iowa State University.

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Using radio frequency spectral measurements for determination of corn mechanical damage.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Using radio frequency spectral measurements for determination of corn mechanical damage./
作者:	Al-Mahasneh, Majdi Ali.
面頁冊數:	151 p.
附註:	Major Professors: Stuart J. Birrell; Carl J. Bern.
Contained By:	Dissertation Abstracts International65-08B.
標題:	Engineering, Agricultural. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoeng/servlet/advanced?query=3143522
ISBN:	9780496017867

Using radio frequency spectral measurements for determination of corn mechanical damage.
Al-Mahasneh, Majdi Ali.

Using radio frequency spectral measurements for determination of corn mechanical damage. - 151 p.

Major Professors: Stuart J. Birrell; Carl J. Bern.

Thesis (Ph.D.)--Iowa State University, 2001.

The technology shows a good potential for developing a mechanical damage sensor. Further testing on additional varieties, types of grains, and more moisture contents is needed.

ISBN: 9780496017867Subjects--Topical Terms:

1019504
Engineering, Agricultural.

Using radio frequency spectral measurements for determination of corn mechanical damage.
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020 $a 9780496017867
035 $a (UMI)AAI3143522
035 $a AAI3143522
040 $a UMI $c UMI
100 1 $a Al-Mahasneh, Majdi Ali. $3 1025143
245 1 0 $a Using radio frequency spectral measurements for determination of corn mechanical damage.
300 $a 151 p.
500 $a Major Professors: Stuart J. Birrell; Carl J. Bern.
500 $a Source: Dissertation Abstracts International, Volume: 65-08, Section: B, page: 4131.
502 $a Thesis (Ph.D.)--Iowa State University, 2001.
520 $a The technology shows a good potential for developing a mechanical damage sensor. Further testing on additional varieties, types of grains, and more moisture contents is needed.
520 $a Dielectric measurements between 10 Hz to 13 MHz were obtained using an HP 4192A Impedance Analyzer for artificially damaged and combine damaged corn samples. For medium and severe artificial damage, the measurements were obtained at two moisture contents (11 and 19 percent), five damage levels (0, 10, 25, 50, and 100 percent), and two bulk densities. The results showed that dielectric properties were able to measure moisture content, bulk density, and mechanical damage level. Using a four-variable model, medium damage level was predicted with R2 = 0.95 and RMSE = 8.8 percent, while severe damage level was predicted with R2 = 0.98 and RMSE = 5.97 percent using a four-variable model. However, when the actual moisture content and bulk density were used along with dielectric variables, the severe damage level prediction was slightly reduced with R2 = 0.97 and RMSE = 6.96 percent although the model used only two dielectric variables in addition to actual moisture content and bulk density of the corn samples. Medium damage level prediction was improved with R2 = 0.98 and RMSE = 5.77 percent, using four-dielectric variable and the actual corn moisture and bulk density.
520 $a Similar analysis was performed on combine damaged corn samples. Four different damage levels were produced. Damage levels were evaluated using Chowdhury's method and visual inspection method. The results from visual inspection were: 0, 10.6, 17.4, and 31.2 percent mechanical damage. Three moisture content levels were prepared (12.5, 18, and 23 percent), and two bulk densities were produced. The damage calibration model was developed for each moisture level separately. For low moisture samples, damage level was predicted with an R 2 = 0.95 and RMSE = 3.36 percent using a six-variable model. For medium moisture samples, damage level was predicted with R2 = 0.95 and RMSE = 3.27 percent, using a five-variable model. Finally, for high moisture samples, damage level was predicted with R2 = 0.97 and RMSE = 2.29 percent using a three-variable model.
590 $a School code: 0097.
650 4 $a Engineering, Agricultural. $3 1019504
690 $a 0539
710 2 $a Iowa State University. $3 1017855
773 0 $t Dissertation Abstracts International $g 65-08B.
790 $a 0097
790 1 0 $a Bern, Carl J., $e advisor
790 1 0 $a Birrell, Stuart J., $e advisor
791 $a Ph.D.
792 $a 2001
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoeng/servlet/advanced?query=3143522