Acknowledgement
본 연구는 경기도의 경기도 지역협력연구센터 사업의 일환으로 수행하였음(GRRC경기2020-B03, 산업통계 및 데이터마이닝 연구).
References
- Cooley JW, and Tukey JW. 1965. An algorithm for the machine calculation of complex Fourier series. Mathematics of Computation 19(90):297-301. https://doi.org/10.1090/S0025-5718-1965-0178586-1
- Gabor D. 1946. Theory of communication. Part 1: The analysis of information. Journal of the Institution of Electrical Engineers-Part III: Radio and Communication Engineering 93(26):429-441. https://doi.org/10.1049/ji-3-2.1946.0074
- Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A and Bengio Y. 2020. Generative adversarial networks. Communications of the ACM 63(11):139-144. https://doi.org/10.1145/3422622
- Han, MS, Yu, SJ. 2022. Forecasting Baltic Dry Index by Implementing Time-Series Decomposition and Data Augmentation Techniques. Journal of the Korean society for Quality Management 50(4):701-716.
- Han, SY, Kim, JG, Hong, SK and Ha, CS. 2004. -Reliability Management of the Rubber-Tired AGT Vehicle System. Journal of the Korea Safety Management and Science 6(4):139-153.
- Hussain F, Abbas SG, Husnain M, Fayyaz UU, Shahzad F, and Shah GA. 2020. IoT DoS and DDoS attack detection using ResNet. In 2020 IEEE 23rd International Multitopic Conference (INMIC):1-6
- Isola P, Zhu JY, Zhou T, and Efros AA. 2017. Image-to-image translation with conditional adversarial networks. In Proceedings of the IEEE conference on computer vision and pattern recognition:1125-1134.
- Kang, KW, and Lee, KM. 2020. CNN-based automatic machine fault diagnosis method using spectrogram images. Journal of the Institute of Convergence Signal Processing 21(3):121-126.
- Karras T, Aila T, Laine S, and Lehtinen J. 2017. Progressive growing of gans for improved quality, stability, and variation. arXiv Preprint arXiv:1710.10196,
- Kim, DK, Park, BN, Song, MO, and Lim, JH. 2022. The Optimal Inspection Period of a System Considering the Probability of Finding Deteriorated Components under the Inspection-Maintenance Model.Journal of Applied Reliability 22(4):309-318.
- Lee, SH, Kim, JY, Lee, JJ, Kim, YJ, Kim, SK, and Lee, TH. 2022. A Study on the Development of Database and Algorithm for Fault Diagnosis for Condition Based Maintenance of Rubber Seal in Ancillary Equipment of Autonomous Ships. Journal of Applied Reliability 22(1):48-58. https://doi.org/10.33162/JAR.2022.3.22.1.048
- Lee, YH, Yong, HY, Jung, JW, and Kim, JW. 2022. Development of Dormant Missile Health Monitoring Methodology based on Environmental Data. Journal of Applied Reliability 22(3):219-228. https://doi.org/10.33162/JAR.2022.9.22.3.219
- Li Z, Zheng T, Wang Y, Cao Z, Guo Z, and Fu H. 2020. A novel method for imbalanced fault diagnosis of rotating machinery based on generative adversarial networks. IEEE transactions on instrumentation and measurement 70:1-17.
- Lim, MW, Lee, JH, Park, GH, Bae, SJ. 2022. Lifetime Estimation of Electric Transformers for Multiple Failure-Modes. Journal of Applied Reliability 22(4):428-435. https://doi.org/10.33162/JAR.2022.12.22.4.428
- Lim, SC, and Kim, JC. 2021. A Study on the Optimization of Convolution Operation Speed through FFT Algorithm. Journal of Korea Multimedia Society 24(11):1552-1559. https://doi.org/10.9717/KMMS.2021.24.11.1552
- Mun, BM, Jeon. YG, Lee, HJ, Kim, JH, Han, SH, and Lee, HJ. 2020. Detection of Display Defects Using a Cluster Index. Journal of Applied Reliability 20(3):277-283. https://doi.org/10.33162/JAR.2020.09.20.3.277
- Salimans T, Goodfellow I, Zaremba W, Cheung V, Radford A, and Chen X. 2016. Improved techniques for training gans. Advances in Neural Information Processing Systems 29.
- Sedigh P, Sadeghian R, and Masouleh MT. 2019. Generating synthetic medical images by using GAN to improve CNN performance in skin cancer classification. In 2019 7th International Conference on Robotics and Mechatronics (ICRoM):497-502.
- Seo, JH, Park, JS, Yoo, JW, and Park HJ. 2021. Anomaly Detection System in Mechanical Facility Equipment: Using Long Short-Term Memory Variational Autoencoder. Journal of the Korean Society for Quality Management, 49(4):581-594. https://doi.org/10.7469/JKSQM.2021.49.4.581
- Shin, JH, Jun, HB, and Kim, DG. 2014. A Study on Several Aspects of Condition Based Maintenance (CBM) Approach and Introduction of Relevant Case Studies. Entrue Journal of Information Technology 13(3):123-138.
- Son, MJ, Kim, YG, Noh, SC, Kim, MH, and Kim, KM. 2022. Exploring the Application of CBM+ in an ISR Weapon System, Thermal Observation Device. Journal of Applied Reliability 22(3):240-247. https://doi.org/10.33162/JAR.2022.9.22.3.240
- Son, MJ and Kim, YG. 2021. A Study on the Reflection of Condition-Based Maintenance Requirement in the Defense Specification. Journal of the Korean Society for Quality Management 49(3):269-279. https://doi.org/10.7469/JKSQM.2021.49.3.269
- Teixeira HN, Lopes I, and Braga AC. 2020. Condition-based maintenance implementation: a literature review. Procedia Manufacturing 51:228-235. https://doi.org/10.1016/j.promfg.2020.10.033
- Zhao R, Yan R, Chen Z, Mao K, Wang P, and Gao RX. 2019. Deep learning and its applications to machine health monitoring. Mechanical Systems and Signal Processing 115:213-237. https://doi.org/10.1016/j.ymssp.2018.05.050