Fault Diagnosis System and Method For Rotating Device Using Deep Learning and Wavelet Transform

• 1. 小波变换域下结合深度学习的光学遥感图像质量提升方法 [P] . 中国专利： CN113012069A . 2021-06-22
• 2. 基于小波变换和深度学习的滚动轴承微弱故障诊断方法 [P] . 中国专利： CN108426713B . 2020.05.01
• 3. Fault Diagnosis System For Rotating Device Using Deep Learning and Wavelet Transform [P] . 韩国专利： KR101998559B1 . 2019-07-10

  机译： 深度学习和小波变换的旋转设备故障诊断系统

• 4. Method for fault diagnosis based on deep learning and fault diagnosis device performing the method [P] . KR20210124783A . 2021-10-15

  机译： 基于深度学习和故障诊断装置进行方法的故障诊断方法

• 5. WAVELET TRANSFORMED WAVEFORM SIGNAL ANALYZING SYSTEM, ANALYZING METHOD BY WAVELET TRANSFORMED WAVEFORM SIGNAL ANALYZING TOOL, AND WAVELET TRANSFORMED WAVEFORM SIGNAL ANALYZING DEVICE FOR THE SAME [P] . 日本专利： JPH0895955A . 1996-04-12

  机译： 小波变换的波形信号分析系统，小波变换的波形信号分析工具的分析方法，小波变换的波形信号分析装置

• 1. A Method for Incipient Fault Diagnosis of Roller Bearings Based on the Wavelet Transform Correlation Filter and Hilbert Transform [J] . ZENG Qing-hu, QIU Jing, LIU Guan-jun 国际设备工程与管理（英文版） . 2007,第004期
• 2. Discrete wavelet transform-based fault diagnosis for driving system of pipeline detection robot arm [J] . Deng Huiyu, Wang Xinli, Ma Peisun 高技术通讯（英文版） . 2005,第004期
• 3. Research on fault diagnosis method of piston rod based on harmonic wavelet and manifold learning [J] . Jiang Zhinong, Zhu Lina, Zhang Jinjie, 高技术通讯（英文版） . 2018,第003期
• 4. Machine　Learning　Method　Applied　to　Acquire　Knowledge　of　a　Fault　Diagnostic　Expert　System　of　Rotating　Machineries [J] . 刘占生, 张嘉钟, 武新华, 哈尔滨工业大学学报：英文版 . 1996,第001期
• 5. On Fault Diagnosis of Rotating Machinery Using Wavelet Time-division Scale Level Moment [J] . YANG Tao, ZHANG Yan-ping, GAO Wei, 国际设备工程与管理（英文版） . 2008,第002期
• 6. An adaptive method based on fractional empirical wavelet transform and its application in rotating machinery fault diagnosis [J] . Zhang Yang, Du Xiaowei, Wen Guangrui, Measurement Science & Technology . 2019,第3期
• 7. Deep Learning-Based Intelligent Fault Diagnosis Methods Toward Rotating Machinery [J] . Tang Shengnan, Yuan Shouqi, Zhu Yong Quality Control, Transactions . 2020,第期
• 8. A sequential feature extraction method based on discrete wavelet transform, phase space reconstruction, and singular value decomposition and an improved extreme learning machine for rolling bearing fault diagnosis [J] . Li D. Z., Zheng X., Xie Q. W., Proceedings of the Institution of Mechanical Engineers, Part E. Journal of Process Mechanical Engineering . 2018,第6期
• 9. Fault diagnosis system of rotating machines using continuous wavelet transform and Artificial Neural Network [C] . Nur Ashar Aditiya, Zaqiatud Darojah, D. Raden Sanggar, 2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing . 2017
• 10. Fault Diagnosis for Wind Turbine Systems by Using Neural Network and Deep Learning Techniques [D] . Rahimilarki, Reihane. 2021
• 11. A Novel Deep Learning Method for Intelligent Fault Diagnosis of Rotating Machinery Based on Improved CNN-SVM and Multichannel Data Fusion [O] . Wenfeng Gong, Hui Chen, Zehui Zhang, 2019
• 12. Knowledge-based approaches to fault diagnosis. The development, implementation, evaluation and comparison of knowledge-based systems, incorporating deep and shallow knowledge, to aid in the diagnosis of faults in complex hydro-mechanical devices. [O] . Doherty Neil Francis 1992

• 1. 基于深度学习的油气设备智能诊断方法研究 [C] . 段礼祥 ,白堂博 ,王洋绅 . 第四届信息化创新克拉玛依国际学术论坛 . -1
• 2. 旋转机械设备故障诊断系统 [A] . 王博 . 2007