Eakkachai WarinsirirukNarit HnoohomWarakorn CharoensukSocheat, Veng, 1997-2024-07-082024-07-08202020202024Thesis (M.Eng. (Industrial Engineering))--Mahidol University, 2020https://repository.li.mahidol.ac.th/handle/123456789/99454Industrial Engineering (Mahidol University 2020)The purpose of this study is to use the data from the Myo hand motion sensor to evaluate the welder performance in Gas Tungsten Arc Welding (GTAW) process. The weld quality produces in this welding process critically depends on how well a welder can maintain the torch evenly to create a good weld bead. It found a direct correlation between hand motion and weld bead appearance. In this research, the Euclidean Norm was used to combine the three axes of accelerometer and gyroscope. The three-axis signals of the accelerometer and the gyroscope were combined respectively, and a relationship was found. It differentiated the normal and abnormal cup-walking pattern of hand motion that is commonly used in a welding process. Moreover, the Continuous Wavelet Transform (CWT) was applied for evaluating the stability of cup-walking motion. The result showed that the expert welder performs cup-walking performance more consistently than the intermediate and beginner welder. By using the quantitative method, the data of accelerometer, gyroscope, and voltage have been transferred to create a scoring system with the multivariable. The results show that it could differentiate between beginner, intermediate, and expert welder.xi, 124 leaves: ill.application/pdfengผลงานนี้เป็นลิขสิทธิ์ของมหาวิทยาลัยมหิดล ขอสงวนไว้สำหรับเพื่อการศึกษาเท่านั้น ต้องอ้างอิงแหล่งที่มา ห้ามดัดแปลงเนื้อหา และห้ามนำไปใช้เพื่อการค้าAccelerometersBody area networks (Electronics)Gas tungsten arc weldingMaster ThesisMahidol University