Radar development for tree defect detection
The assessment of tree health has been an important part of maintaining the integrity of the tree. The use of assessment technics, Ground Penetrating Radar (GPR) has been widely accepted and adopted into different field of operation which include GPR for trees. This method was proved to be an...
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sg-ntu-dr.10356-1574372023-07-07T19:18:15Z Radar development for tree defect detection Choo, Yida Abdulkadir C. Yucel School of Electrical and Electronic Engineering acyucel@ntu.edu.sg Engineering::Electrical and electronic engineering The assessment of tree health has been an important part of maintaining the integrity of the tree. The use of assessment technics, Ground Penetrating Radar (GPR) has been widely accepted and adopted into different field of operation which include GPR for trees. This method was proved to be an accurate, non-invasive and non-destructive methods which allowed penetrating the surface without damaging the structure. To increase the efficiency of GPR for tree trunk penetration, automation of GPR for tree trunk data collection is needed. This project aims to develop a prototype testbed, to allow communication between the GPR system and the prototype to automate the whole assessment of tree health collection. This could be done through automation of processes using electronic component. The whole GPR data collection could be further enhanced with the integration of both the automation of testbed and the GPR operating system. Automation procedures included the use of DC motors, stepper motors, and servo motors in conjunction with ultrasonic sensors to assist in the movement and detection of the tree trunk during GPR data collection. The automation procedures would be evaluated in a laboratory setting to verify the system's functionality. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-15T05:35:25Z 2022-05-15T05:35:25Z 2022 Final Year Project (FYP) Choo, Y. (2022). Radar development for tree defect detection. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157437 https://hdl.handle.net/10356/157437 en application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Choo, Yida Radar development for tree defect detection |
description |
The assessment of tree health has been an important part of maintaining the integrity
of the tree. The use of assessment technics, Ground Penetrating Radar (GPR) has been
widely accepted and adopted into different field of operation which include GPR for
trees. This method was proved to be an accurate, non-invasive and non-destructive
methods which allowed penetrating the surface without damaging the structure. To
increase the efficiency of GPR for tree trunk penetration, automation of GPR for tree
trunk data collection is needed.
This project aims to develop a prototype testbed, to allow
communication between the GPR system and the prototype to automate the
whole assessment of tree health collection. This could be done through
automation of processes using electronic component. The whole GPR data
collection could be further enhanced with the integration of both the automation
of testbed and the GPR operating system.
Automation procedures included the use of DC motors, stepper motors,
and servo motors in conjunction with ultrasonic sensors to assist in the
movement and detection of the tree trunk during GPR data collection. The
automation procedures would be evaluated in a laboratory setting to verify the
system's functionality. |
author2 |
Abdulkadir C. Yucel |
author_facet |
Abdulkadir C. Yucel Choo, Yida |
format |
Final Year Project |
author |
Choo, Yida |
author_sort |
Choo, Yida |
title |
Radar development for tree defect detection |
title_short |
Radar development for tree defect detection |
title_full |
Radar development for tree defect detection |
title_fullStr |
Radar development for tree defect detection |
title_full_unstemmed |
Radar development for tree defect detection |
title_sort |
radar development for tree defect detection |
publisher |
Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/157437 |
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1772826077001940992 |