참고문헌 (24)

1. Journal of Mechanical Engineering GuoBiao 49 63 2013 10.3901/JME.2013.01.063 Basic research on machinery fault diagnosis-what is the prescription 

   상세보기

2. Khan 241 2018 A review on the application of deep learning in system health management 

3. Sensors Li 18 1735 2018 10.3390/s18061735 Planetary gear fault diagnosis via feature image extraction based on multi central frequencies and vibration signal frequency spectrum 

   상세보기

4. Liu 33 2018 Artificial intelligence for fault diagnosis of rotating machinery: A review 

5. Verstraete 1 2017 Deep learning enabled fault diagnosis using time-frequency image analysis of rolling element bearings 

6. Proceedings of the Institution of Mechanical Engineers Part J-Journal of Engineering Tribology Morhain 217 257 2003 10.1243/135065003768618614 Bearing defect diagnosis and acoustic emission 

   상세보기

7. Shock and Vibration Zhiqiang 4 1 2015 Gearbox fault identification and classification with convolutional neural networks 

8. IEEE Transactions on Industrial Electronics Wen 7 5990 2018 10.1109/TIE.2017.2774777 A new convolutional neural networkbased data-driven fault diagnosis method 

   상세보기

9. Wang 65 2018 Convolutional neural network-based hidden Markov models for rolling element bearing fault identification 

10. Structural Health Monitoringan International Journal Taha 5 267 2016 10.1177/1475921706067741 Wavelet transform for structural health monitoring: A compendium of uses and features 

    상세보기

11. Journal of Mechanical Engineering Yaguo 51 49 2015 10.3901/JME.2015.21.049 A deep learning-based method for machinery health monitoring with big data 

    상세보기

12. Nature Cun 521 436 2015 10.1038/nature14539 Deep learning 

    상세보기

13. Neural Networks Schmid 61 85 2015 10.1016/j.neunet.2014.09.003 Deep learning in neural networks: An overview 

    상세보기

14. IEEE Transactions on Pattern Analysis and Machine Intelligence He 37 1904 2015 10.1109/TPAMI.2015.2389824 Spatial pyramid pooling in deep convolutional networks for visual recognition 

    상세보기

15. Communications of the Acm Krizhevsky 60 84 2017 10.1145/3065386 Image net classification with deep convolutional neural networks 

    상세보기

16. Jiang 1 2018 Multiscale convolutional neural networks for fault diagnosis of wind turbine gearbox 

17. Guo 1429 2018 A novel fault diagnosis method for rotating machinery based on a convolutional neural network 

18. Kiranyaz 10 2018 Real-time fault detection and identification for MMC using 1d convolutional neural networks 

19. Eren 179 2018 A generic intelligent bearing fault diagnosis system using compact adaptive 1d CNN classifier 

20. Abdeljaber 1308 2018 1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data 

21. Eren 1 2017 Bearing fault detection by one-dimensional convolutional neural networks 

22. Liu 191 2017 eMulti-focus image fusion with a deep convolutional neural network 

23. IEEE Transactions on Geoscience and Remote Sensing Xu 56 937 2018 10.1109/TGRS.2017.2756851 Multisource remote sensing data classification based on convolutional neural network 

    상세보기

24. Mechanical Systems and Signal Processing Jia 110 349 2018 10.1016/j.ymssp.2018.03.025 Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization 

    상세보기