Hyewon Lee

Biographical Information

• M.S. (2021-2023)  Mechanical Engineering, Department of Mechanical Engineering, Dongguk University, Seoul, Korea

• B. S. (2017-2021), Department of Mechanical, Robotics and Energy Engineering, Dongguk University, Seoul, Korea 

Academic Experience

• August, 2020-currently, Research Assistant in Dongguk University, Seoul, Korea

Research Interests  

• Artificial Intelligence (AI), Machine Learning, Prognostics, and Health Management (PHM)

Honors and Awards 

1. Best Poster Award - Prognostics and Health Management Asia Pacific 2021 (PHMAP2021) , 2022/12/15

2. Best Poster Award - Prognostics and Health Management Asia Pacific 2021 (PHMAP2021) , 2022/12/15

Korean Patent

1. Kim H. S,. Ali R., Lee H., “Apparatus and method for detecting fault of robot”, 2022.09.27, 10-2449-4130000

2. Kim H. S., Kumar P., Izaz R., Lee H., “Fault diagnosis device and method for strain wave gear detect of industrial robot”, 2022.11.22, 10-2022-0155954

Publication - International Journal

1. Izaz R., Lee H. and Kim H.S., “Mechanical fault detection based on machine learning for robotic RV reducer using electrical current signature analysis: A data-driven approach,” Journal of Computational Design and Engineering, Vol. 9, No. 2, April 2022, pp. 417–433, https://doi.org/10.1093/jcde/qwac015. (SCIE, Q1, IF: 6.167, JCR ranking 10.33%)

2. Izaz R., Lee H., Noh Y.R., Youn B.D., and Kim H.S., “Prognostic health management of the robotic strain wave gear reducer based on the variable speed of operation: a data-driven via deep learning approach,” Journal of Computational Design and Engineering, Vol. 9, No. 5, October 1, 2022, pp. 1775-1788, https://doi.org/10.1093/jcde/qwac091. (SCIE, Q1, IF: 6.167, JCR ranking 10.33%)

3. Lee H., Izaz R., Song J., Kim H.S., and Lee S., “Prognostics and Health Management of the Robotic Servo-Motor under Variable Operating Conditions,” Mathematics, Vol. 11, No. 2, Jan 12, 2023, pp398. https://doi.org/10.3390/math11020398, (SCIE, Q1, IF: 2.592, JCR ranking 6.16%)

Publication - Korean  Journal

1. Asif K., Lee H., Kim H., “PHM Technology based on physical model data augmentation,” Korean Society for Noise and Vibration Engineering(KSNVE), Vol. 30, No. 6, 2020, pp. 13-18.

Publication - International Conference

1. Izaz R., Ali R., Lee H. and Kim H. S., “Mechanical Fault Detection of RV Reducer Based on Machine Learning Using Motor Current Signature Analysis,” Asia Pacific Conference of the Prognostics and Health Management Society 2021(PHMAP 2021), Jeju, Korea, September 8-11, 2021.

2. Lee H., Kim S., Ali R., Izaz R., Kim H.S. and Lee S., “Deep Scattering Coefficient Features based Rotate Vector (RV) Reducer Fault Segregation,” Asia Pacific Conference of the Prognostics and Health Management Society 2021(PHMAP 2021), Jeju, Korea, September 8-11, 2021

Publication - Korean Conference

1. Izaz R., Ali R., Noh Y.R., Hwang H., Lee H., Kim H.S., “Robotic Arm’s reducer fault detection using motor current signature analysis (MCSA)”, Korean Society for Noise and Vibration Engineering(KSNVE), Jeju, Korea, October 28-31, 2020

2. Izaz R., Ali R., Noh Y.R., Hwang H., Lee H., Kim H.S., “Robotic Arm’s reducer fault detection using motor current signature analysis (MCSA)”, Korean Society for Noise and Vibration Engineering(KSNVE), Jeju, Korea, October 28-31, 2020

3. Ali R ., Izaz R., Noh Y.R., Hwang H., Lee H., Jung J., Kim H.S, “Wavelets-based Features Infusion for Machine Learning Classification; Towards a Holistic Rotate Vector (RV) Reducer Fault Detection and Diagnosis system,” Korean Society of Mechanical Engineers (KSME), December 16-19, 2020

4. Izaz R., Lee H., Kim H.S., “Features Selection Mechanism for rotate vector (RV) reducer fault detection using motor current signature analysis (MCSA),” Korean Society for Noise and Vibration Engineering(KSNVE), Pyeongchang, Korea, May 26-29, 2021

5. Lee H., Izaz R., Lee S., Kim H.S., “Fault feature extraction independent of the speed of the robot operation,” 2022 KSME CAE Conference, Busan, Korea, May 18-21, 2022

6. Izaz R., Noh Y.R., Lee H., Kim H.S., “ Condition health monitoring of industrial robotic RV reducer based on the deep learning models: Data-driven approaches,” 2022 KSME CAE Conference, Busan, Korea, May 18-21, 2022

7. Lee H., Izaz R., Lee S., Kim H.S., “Fault feature extraction independent of the speed of the robot’s reducer and fault diagnosis using principal component analysis Optimization of Medical Waste Shredder Blade,” PHM Korea 2022 , Seoul, June 29-July 01, 2022

8. Izaz R., Lee H., Noh Y.R., Kim H.S., “Fault detection of the robotic reducer for variable speed of operation based on deep feature extraction,” PHM Korea 2022 , Seoul, June 29-July 01, 2022

9. Kumar P., Izaz R., Lee H., Kim H.S., “Bearing fault detection of industrial robot servomotor under variable operating conditions,” 2022 KSME Conference, Jeju, Nov 9-11, 2022

10. Izaz R., Kumar P., Lee H., Kim H.S., “Prognostic health management for strain wave gear reducer under different operating conditions,” 2022 KSME Conference, Jeju, Nov 9-11, 2022

11. Lee H., Izaz R., Kumar P., Lee S., Kim H.S., “Speed independent fault detection for robot arm using feature extraction under variable operating speed conditions,” 2022 KSME Conference, Jeju, Nov 9-11, 2022

12. Izaz R., Kumar P., Lee H., Kim H.S., “Component-level mechanical fault detection for the robotic arm under variable working conditions,” The 8th Korea Multi-Scale Mechanics Symposium 2022 (KMSM2022 Symposium), Seoul, Dec 15-16, 2022

13. Lee H., Izaz R., Kim H.S., “Servo motor fault diagnosis using MCSA under various operating conditions,” The 8th Korea Multi-Scale Mechanics Symposium 2022 (KMSM2022 Symposium), Seoul, Dec 15-16, 2022