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References

1 
Su-Jeong Yu, 2017, Fourth Industrial Revolution and Artificial Intelligence, Korea Multimedia Society, Vol. 21, No. 4, pp. 1-8DOI
2 
Song Ju Kim, 2022, Technology Research Trends of Smart Factory through the Keyword Network Analysis, Journal of the Korea Academia-Industrial cooperation Society, Vol. 23, No. 5, pp. 17-23DOI
3 
Byeong-Eob So, 2018, Study on built smart factory using sensors and virtual process design, pp. 22-23DOI
4 
Dae-hoon Kwon, Chang-heon Oh, 2021, Predictive maintenance technology for smart factory, Korean Information and Communication Association's Comprehensive Academi conference Paper Collection, Vol. 25, No. 1, pp. 172-174DOI
5 
, https://min23th.tistory.com/9DOI
6 
Kyung-Won Kang, Kyeong-Min Lee, 2020, CNN-based Automatic Machine Fault Diagnosis Method Using Spectrogram Images, Journal of the Convergence Signal Processing Society, Vol. 21, No. 3, pp. 121-126DOI
7 
Woo-Jin Jang, Ho-Won Yu, Seong-Hyeon Shin, Ho-chong Park, 2016, Audio Genre Classification based on Deep Learning using Spectrogram, Journal of the Korea Broadcasting Media Engineering Association's Academic Presentation Conf, pp. 90-91DOI
8 
Y. K. Oh, W. I. Lee, J. H. Cho, 2018, Development of Sensor Module to Acquire Vibration Signal in Machine Tool, Journal of the Korea Society of Precision Engineering's Academic Presentation, pp. 642-643DOI
9 
Tae-bong Lee, 2007, Condition monitoring and diagnostic techniques using noise signals, Korea Society of Noise and Vibration Engineering Classification, pp. 376-405DOI
10 
Se-won Oh, 2022, IoT-based machine anomaly detection AI technology, The Proceedings of the Korea Electromagnetic Engineering Society, Vol. 33, No. 3, pp. 20-25DOI
11 
Geonkyo Hong, Jeonghoon Choi, Dongjun Suh, 2020, A Study on the Design of Time Series Data-based Deep Learning Model for Detecting Machine Abnormalities, Proceedings of Symposium of the Korean Institute of communications and Information Sciences, pp. 887-888DOI
12 
Seong-Eun Mun, Su-Beom Jang, Jeong-Hyeo k Lee, Jong-Seok Lee, 2016, Technology Trends in Machine Learning and Deep Learning, The Korean Institute of Commucations and Information Sciences, Vol. 33, No. 10, pp. 49-56DOI
13 
, https://itwiki.kr/CNN.DOI
14 
, https://ratsgo.github.io/blog/tags/#rnnDOI
15 
Min su Kim, Jong Pil Yun, Poo Gyeon Park, 2019, Supervised and Unsupervised Learning Based Fault Detection Using Spectrogram, Journal of the Korean Electrical Society, pp. 1575-1576DOI