Acknowledgement
이 논문은 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2023R1A2C1006332).
References
- A. G. Frank, L. S. Dalenogare, and N. F. Ayala, "Industry 4.0 technologies: Implementation patterns in manufacturing companies," International Journal of Production Economics, Vol.210, pp.15-26, 2019. https://doi.org/10.1016/j.ijpe.2019.01.004
- A. Weiss and A. Huber, "User experience of a smart factory robot: Assembly line workers demand adaptive robots," arXiv preprint arXiv:1606.03846, 2016.
- R. Ahmad and S. Kamaruddin, "An overview of time-based and condition-based maintenance in industrial application," Computers & Industrial Engineering, Vol.63, No.1, pp.135-149, 2012. https://doi.org/10.1016/j.cie.2012.02.002
- T. Gulledge, S. Hiroshige, and R. Iyer, "Condition-based maintenance and the product improvement process," Computers in Industry, Vol.61. No.9, pp.813-832, 2010. https://doi.org/10.1016/j.compind.2010.07.007
- S. Selcuk, "Predictive maintenance, its implementation and latest trends," Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol.231, No.9, pp.1670-1679, 2017. https://doi.org/10.1177/0954405415601640
- L. F. Villa, A. Renones, and J. R. Peran, "Statistical fault diagnosis based on vibration analysis for gear test-bench under non-stationary conditions of speed and load," Mechanical Systems and Signal Processing, Vol.29, pp.436- 446, 2012. https://doi.org/10.1016/j.ymssp.2011.12.013
- S. Vallachira, M. Orkisz, M. Norrlof, and S. Butail, "Data-driven gearbox failure detection in industrial robots," IEEE Transactions on Industrial Informatics, Vol.16, No.1, pp.193-201, 2019. https://doi.org/10.1109/TII.2019.2912809
- D. A. Tobon-Mejia, K. Medjaher, and N. Zerhouni, "CNC machine tool's wear diagnostic and prognostic by using dynamic Bayesian networks," Mechanical Systems and Signal Processing, Vol.28, pp.167-182, 2012. https://doi.org/10.1016/j.ymssp.2011.10.018
- Z. Yu and Y. Zhang, "Diagnosis of the misaligned faults of the vertical test instrument of high-precision industrial robot reducer," Shock and Vibration, Vol.2021, pp.1-17, 2021.
- A. Bonci, S. Longhi, and F. Verdini, "Predictive maintenance system using motor current signal analysis for industrial robot," 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2019.
- Q. Yang, Xi. Li, Yi. Wang, and A. Ainapure, "Fault diagnosis of ball screw in industrial robots using non-stationary motor current signals," Procedia Manufacturing, Vol.48, pp.1102-1108, 2020. https://doi.org/10.1016/j.promfg.2020.05.151
- Y. Kim, J. Park, K. Na, H. Yuan, B. D. Youn, and C. S. Kang, "Phase-based time domain averaging (PTDA) for fault detection of a gearbox in an industrial robot using vibration signals," Mechanical Systems and Signal Processing, Vol.138, pp.106544, 2020.
- C. C. Lo, C. H. Lee, and W. C. Huang, "Prognosis of bearing and gear wears using convolutional neural network with hybrid loss function," Sensors, Vol.20, No.12, pp.3539, 2020.
- J. Long, J. Mou, L. Zhang, S. Zhang, and C. Li, "Attitude data-based deep hybrid learning architecture for intelligent fault diagnosis of multi-joint industrial robots," Journal of Manufacturing Systems, Vol.61, pp.736-745, 2020. https://doi.org/10.1016/j.jmsy.2020.08.010
- L. F. Villa, A. Renones, and J. R. Peran, "Statistical fault diagnosis based on vibration analysis for gear test-bench under non-stationary conditions of speed and load," Mechanical Systems and Signal Processing, Vol.29 pp.436- 446, 2012. https://doi.org/10.1016/j.ymssp.2011.12.013
- Z. Gao, C. Cecati, and S. X. Ding, "A survey of fault diagnosis and fault-tolerant techniques-Part I: Fault diagnosis with model-based and signal-based approaches," IEEE Transactions on Industrial Electronics, Vol.62, No.6, pp.3757-3767, 2015. https://doi.org/10.1109/TIE.2015.2417501
- L. Console and O. Dressler, "Model-based diagnosis in the real world: Lessons learned and challenges remaining," IJCAI, Vol.99, 1999.
- A. Soualhi, M. Lamraoui, B. Elyousfi, and H. Razik, "PHM SURVEY: Implementation of diagnostic methods for monitoring industrial systems," International Journal of Prognostics and Health Management, Vol.10, No.2, pp.6909-6932, 2019.
- D. U. Campos-Delgado and D. R. Espinoza-Trejo, "An observer-based diagnosis scheme for single and simultaneous open-switch faults in induction motor drives," IEEE Transactions on Industrial Electronics, Vol.58, No.2, pp.671-679, 2010. https://doi.org/10.1109/TIE.2010.2047829
- Z. W. Huang, Y. Z. Yang, J. Wang, and Y. Li, "Parity space-based fault diagnosis of CCBII braking system," Journal of Central South University, Vol.20, No.10, pp.2922-2928, 2013. https://doi.org/10.1007/s11771-013-1814-2
- A. T. James, O. P. Gandhi, and S. G. Deshmukh, "Fault diagnosis of automobile systems using fault tree based on digraph modeling," International Journal of System Assurance Engineering and Management, Vol.9, No.2, pp.494- 508, 2018. https://doi.org/10.1007/s13198-017-0693-6
- A. A. Jaber and R. Bicker, "Industrial robot backlash fault diagnosis based on discrete wavelet transform and artificial neural network," American Journal of Mechanical Engineering, Vol.4, No.1, pp.21-31, 2016. https://doi.org/10.1784/insi.2016.58.4.179
- J. Pan, L. Qu, and K. Peng, "Sensor and actuator fault diagnosis for robot joint based on deep CNN," Entropy, Vol.23, No.6, pp.751, 2021.
- P. Zou, B. Hou, J. Lei, and Z. Zhang, "Bearing fault diagnosis method based on EEMD and LSTM," International Journal of Computers Communications & Control, Vol.15, No.1, 2020.
- I. Mitiche, T. McGrail, P. Boreham, A. Nesbitt, and G. Morison, "Data-driven anomaly detection in high-voltage transformer bushings with lstm auto-encoder," Sensors, Vol.21, No.21, pp.7426, 2021.
- S. Hochreiter and J. Schmidhuber, "Long short-term memory," Neural Computation, Vol.9, No.8, pp.1735-1780, 1997. https://doi.org/10.1162/neco.1997.9.8.1735
- "Niryo One - An accessible educational 6 axis robotic arm, just for you - Niryo," Niryo, 2020. [Internet], https://niryo.com/niryo-one/. [Accessed: 15 Oct 2019].