Author ORCID Identifier
Date Available
12-4-2018
Year of Publication
2018
Degree Name
Master of Science in Electrical Engineering (MSEE)
Document Type
Master's Thesis
College
Engineering
Department/School/Program
Electrical and Computer Engineering
First Advisor
Dr. YuMing Zhang
Abstract
In manual control, the welding gun’s moving speed can significantly influence the welding results and critical welding operations usually require welders to concentrate consistently in order to react rapidly and accurately. However, human welders always have some habitual action which can have some subtle influence the welding process. It takes countless hours to train an experienced human welder. Using vision and IMU sensor will be able to set up a system and allow the worker got more accurate visual feedback like an experienced worker.
The problem is that monitor and measuring of the control process not always easy under a complex working environment like welding. In this thesis, a new method is developed that use two different methods to compensate each other to obtain accurate monitoring results. Vision sensor and IMU sensor both developed to obtain the accurate data from the control process in real-time but don’t influence other. Although both vision and IMU sensor has their own limits, they also have their own advantage which can contribute to the measuring system.
Digital Object Identifier (DOI)
https://doi.org/10.13023/etd.2018.465
Recommended Citation
Yu, Rui, "A REDUNDANT MONITORING SYSTEM FOR HUMAN WELDER OPERATION USING IMU AND VISION SENSORS" (2018). Theses and Dissertations--Electrical and Computer Engineering. 128.
https://uknowledge.uky.edu/ece_etds/128
