Tea leaves moisture measurement and prediction using RF waveguide antenna

This paper proposed a microwave reflection method by using a horn antenna at 10.3GHz to determine m.c. of tea leaves from 0% to 10.5%. The tea leaves are filled inside an acrylic container whereas a horn antenna is placed on the open ended of the container. Reflection coefficient, S 11 is collected...

Full description

Saved in:
Bibliographic Details
Main Authors: Shyh Yau, Tein, Yi Lung, Then, Hieng Tiong, Su
Format: Proceeding
Language:English
Published: 2018
Subjects:
Online Access:http://ir.unimas.my/id/eprint/39988/3/Tea%20Leaves%20-%20Copy.pdf
http://ir.unimas.my/id/eprint/39988/
https://ieeexplore.ieee.org/abstract/document/8251535
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimas.ir.39988
record_format eprints
spelling my.unimas.ir.399882022-09-27T01:21:31Z http://ir.unimas.my/id/eprint/39988/ Tea leaves moisture measurement and prediction using RF waveguide antenna Shyh Yau, Tein Yi Lung, Then Hieng Tiong, Su TK Electrical engineering. Electronics Nuclear engineering This paper proposed a microwave reflection method by using a horn antenna at 10.3GHz to determine m.c. of tea leaves from 0% to 10.5%. The tea leaves are filled inside an acrylic container whereas a horn antenna is placed on the open ended of the container. Reflection coefficient, S 11 is collected and its relationship between gravimetric (m.c g ) and volumetric moisture content (m.c v ) are fitted in two polynomial equations respectively. The equations are used to predict m.c. of tea leaves. The maximum error for the predicted m.c g is 0.52% whereas the maximum error of predicted m.c v is 0.233%. 2018 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/39988/3/Tea%20Leaves%20-%20Copy.pdf Shyh Yau, Tein and Yi Lung, Then and Hieng Tiong, Su (2018) Tea leaves moisture measurement and prediction using RF waveguide antenna. In: IEEE Asia Pacific Microwave Conference (APMC), 13-16 November 2017, Kuala Lumpur. https://ieeexplore.ieee.org/abstract/document/8251535
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Shyh Yau, Tein
Yi Lung, Then
Hieng Tiong, Su
Tea leaves moisture measurement and prediction using RF waveguide antenna
description This paper proposed a microwave reflection method by using a horn antenna at 10.3GHz to determine m.c. of tea leaves from 0% to 10.5%. The tea leaves are filled inside an acrylic container whereas a horn antenna is placed on the open ended of the container. Reflection coefficient, S 11 is collected and its relationship between gravimetric (m.c g ) and volumetric moisture content (m.c v ) are fitted in two polynomial equations respectively. The equations are used to predict m.c. of tea leaves. The maximum error for the predicted m.c g is 0.52% whereas the maximum error of predicted m.c v is 0.233%.
format Proceeding
author Shyh Yau, Tein
Yi Lung, Then
Hieng Tiong, Su
author_facet Shyh Yau, Tein
Yi Lung, Then
Hieng Tiong, Su
author_sort Shyh Yau, Tein
title Tea leaves moisture measurement and prediction using RF waveguide antenna
title_short Tea leaves moisture measurement and prediction using RF waveguide antenna
title_full Tea leaves moisture measurement and prediction using RF waveguide antenna
title_fullStr Tea leaves moisture measurement and prediction using RF waveguide antenna
title_full_unstemmed Tea leaves moisture measurement and prediction using RF waveguide antenna
title_sort tea leaves moisture measurement and prediction using rf waveguide antenna
publishDate 2018
url http://ir.unimas.my/id/eprint/39988/3/Tea%20Leaves%20-%20Copy.pdf
http://ir.unimas.my/id/eprint/39988/
https://ieeexplore.ieee.org/abstract/document/8251535
_version_ 1745566060674809856
score 13.209306