Microwave reflectometer for soil moisture and permittivity measurement
Microwave sensors are commonly used for aquametry measurements due to strong tendency of water molecule in absorbing microwave signals. Nowadays, meter-based microwave system is in demand as more applications need concept of being portable and simple. This thesis presents a microwave reflectometer,...
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my-utm-ep.786182018-08-29T07:53:05Z Microwave reflectometer for soil moisture and permittivity measurement 2016-01 Then, Yi Lung TK Electrical engineering. Electronics Nuclear engineering Microwave sensors are commonly used for aquametry measurements due to strong tendency of water molecule in absorbing microwave signals. Nowadays, meter-based microwave system is in demand as more applications need concept of being portable and simple. This thesis presents a microwave reflectometer, which operates between 2.2 GHz and 4.4 GHz. It can measure soil moisture content, m.c. up to 26 % with mean deviation between predicted and actual m.c. determined at ± 2.0 %. Five common soil samples found in southern region of Peninsular Malaysia, Johor were characterized based on macroscopic and microscopic experiments. Throughout the research, four microstrip ring resonantor sensors operating between 2.2 GHz and 4.4 GHz were designed with different angles of microstrip bends. (Conventional Sensor = 0.98 rad., Sensor A = 1.34 rad., Sensor B = 1.57 rad., and Sensor C = 1.64 rad.). Sensor B was chosen as the soil sensor. A critical study on the use of microstrip ring resonator sensors for the determination of both permittivity, er and m.c. from the measured scattering parameters (S-parameters) in conjunction with E5071C vector network analyzer (VNA) was presented. The relationship between the measured er and m.c. obtained from the oven drying method was established. From the results, it was observed that two dielectric relaxation conditions (bound and free water) exist in soil-water mixture. A semi-empirical equivalent lumped element model was created based on simulation data obtained from Microwave Office (AWR) software. The predicted er results from the model agree with the measured data using commercial HP85070D dielectric probe. The model successfully estimated er for the five common soil types with error of 2.5 %. By using inverse algorithm from the model, m.c. was predicted and was in good agreement with the standard oven drying method with its average error within ± 1.5 % for all soil samples. In general, microwave reflectometer with the proposed MRR sensor, provide nondestructive measurement for rapid determination of soil m.c. and er. 2016-01 Thesis http://eprints.utm.my/id/eprint/78618/ http://eprints.utm.my/id/eprint/78618/1/ThenYiLungPFKE2016.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:97492 phd doctoral Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering |
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TK Electrical engineering Electronics Nuclear engineering Then, Yi Lung Microwave reflectometer for soil moisture and permittivity measurement |
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Microwave sensors are commonly used for aquametry measurements due to strong tendency of water molecule in absorbing microwave signals. Nowadays, meter-based microwave system is in demand as more applications need concept of being portable and simple. This thesis presents a microwave reflectometer, which operates between 2.2 GHz and 4.4 GHz. It can measure soil moisture content, m.c. up to 26 % with mean deviation between predicted and actual m.c. determined at ± 2.0 %. Five common soil samples found in southern region of Peninsular Malaysia, Johor were characterized based on macroscopic and microscopic experiments. Throughout the research, four microstrip ring resonantor sensors operating between 2.2 GHz and 4.4 GHz were designed with different angles of microstrip bends. (Conventional Sensor = 0.98 rad., Sensor A = 1.34 rad., Sensor B = 1.57 rad., and Sensor C = 1.64 rad.). Sensor B was chosen as the soil sensor. A critical study on the use of microstrip ring resonator sensors for the determination of both permittivity, er and m.c. from the measured scattering parameters (S-parameters) in conjunction with E5071C vector network analyzer (VNA) was presented. The relationship between the measured er and m.c. obtained from the oven drying method was established. From the results, it was observed that two dielectric relaxation conditions (bound and free water) exist in soil-water mixture. A semi-empirical equivalent lumped element model was created based on simulation data obtained from Microwave Office (AWR) software. The predicted er results from the model agree with the measured data using commercial HP85070D dielectric probe. The model successfully estimated er for the five common soil types with error of 2.5 %. By using inverse algorithm from the model, m.c. was predicted and was in good agreement with the standard oven drying method with its average error within ± 1.5 % for all soil samples. In general, microwave reflectometer with the proposed MRR sensor, provide nondestructive measurement for rapid determination of soil m.c. and er. |
format |
Thesis |
qualification_name |
Doctor of Philosophy (PhD.) |
qualification_level |
Doctorate |
author |
Then, Yi Lung |
author_facet |
Then, Yi Lung |
author_sort |
Then, Yi Lung |
title |
Microwave reflectometer for soil moisture and permittivity measurement |
title_short |
Microwave reflectometer for soil moisture and permittivity measurement |
title_full |
Microwave reflectometer for soil moisture and permittivity measurement |
title_fullStr |
Microwave reflectometer for soil moisture and permittivity measurement |
title_full_unstemmed |
Microwave reflectometer for soil moisture and permittivity measurement |
title_sort |
microwave reflectometer for soil moisture and permittivity measurement |
granting_institution |
Universiti Teknologi Malaysia, Faculty of Electrical Engineering |
granting_department |
Faculty of Electrical Engineering |
publishDate |
2016 |
url |
http://eprints.utm.my/id/eprint/78618/1/ThenYiLungPFKE2016.pdf |
_version_ |
1747818029747535872 |