| Citation: | LI Jun, LIU Yongbao, YU Youhong. Application of convolutional neural network and kurtosis in fault diagnosis of rolling bearing[J]. Journal of Aerospace Power, 2019, 34(11): 2423-2431. doi: 10.13224/j.cnki.jasp.2019.11.014
|
| [1] |
吴昭同,杨世锡.旋转机械故障特征提取与模式分类新方法［M］.北京：科学出版社,2012.
|
| [2] |
李永波,滚动轴承故障特征提取与早期诊断方法研究［D］.哈尔滨：哈尔滨工业大学,2017.LI Yongbo.Investigation of fault feature extraction and early fault diagnosis for rolling bearings［D］.Harbin: Harbin Institute of Technology,2017.(inChinese)
|
| [3] |
高艺源,于德介,王好将,等.基于图谱指标的滚动轴承故障特征提取方法［J］.航空动力学报,2018,33(8):2033-2040.GAO Yiyuan,YU Dejie,WANG Haojiang,et al.Fault feature extraction method of rolling bearing based on spectral graph indices［J］.Journal of Aerospace Power,2018,33(8):2033-2040.(in Chinese)
|
| [4] |
王宏超,杜文辽.基于强抗噪威格纳威利分析的滚动轴承故障诊断［J］.航空动力学报,2019,34(4):772-777.WANG Hongchao,DU Wenliao.Fault diagnosis of rolling bearing based on noise-resistant Wigner-Vile analysis［J］.Journal of Aerospace Power,2019,34(4):772-777.(in Chinese)
|
| [5] |
张新鹏,胡茑庆,程哲,等.信号稀疏分解理论在轴承故障检测中的应用［J］.国防科技大学学报,2016,38(3):141-147.ZHANG Xinpeng,HU Niaoqing,CHENG Zhe,et al.Application of signal sparse decomposition theory inbearing fault detection［J］.Journal of National University of Defense Technology,2016,38(3):141-147.(in Chinese)
|
| [6] |
HINTON G E,SALAKHUTDINOV R R.Reducing the dimensionality of data with neural networks［J］.Science,2006,313(5786):504-507.
|
| [7] |
GUO S,YANG T,GAO W.A novel fault diagnosis method for rotating machinery based on a convolutional neural network［J］.Sensors,2018,18(5):1429-1447.
|
| [8] |
XIE J,DU G,SHEN C.An end-to-end model based on improved adaptive deep belief network and its application to bearing fault diagnosis［J］.IEEE Access,2018,6:63584-63596.
|
| [9] |
SHAO H,JIANG H,ZHANG H.Electric locomotive bearing fault diagnosis using a novel convolutional deep belief network［J］.IEEE Transactions on Industrial Electronics,2018,65(3):2727-2736.
|
| [10] |
姜建国,王庆.基于MEEMD和峭度-相关系数电机轴承故障诊断［J］.自动化技术与应用,2018,37(1):65-70.JIANG Jianguo,WANG Qing.Motor bearing fault diagnosis based on MEEMD and kurtosis-relevant coefficient［J］.Techniques of Automation and Applications,2018,37(1):65-70.(in Chinese)
|
| [11] |
李彦冬,郝宗波,雷航.卷积神经网络研究综述［J］.计算机应用,2016,36(9):2508-2515.LI Yandong,HAO Zongbo,LEI Hang.Survey of convolutional neural network［J］.Journal of Computer Applications,2016,36(9):2508-2515.(in Chinese)
|
| [12] |
ZHAO R,YAN R,CHEN Z.Deep learning and its applications to machine health monitoring［J］.Mechanical Systems and Signal Processing,2019,115:213-237.
|
| [13] |
KHAN S,YAIRI T.A review on the application of deep learning in system health management［J］.Mechanical Systems and Signal Processing,2018,107:241-265.
|
| [14] |
HINTON G E,SRIVASTAVA N,KRIZHEVSKY A.Improving neural networks by preventing co-adaptation of feature detectors.［EB/OL］.［2012-07-03］.https://arxiv.org/abs/1207.0580.
|
| [15] |
彭畅.旋转机械轴承振动信号分析方法研究［D］.重庆:重庆大学,2014.PENG Chang.Vibration signal analysis of bearings in the rotating machinery［D］.Chongqing:Chongqing University,2014.(in Chinese)
|
| [16] |
ABADI M.TensorFlow: learning functions at scale［J］.ACM(Association for Computing Machinery) Sigplan Notices,2016,51(9):1.
|
| [17] |
张荣,李伟平,莫同.深度学习研究综述［J］.信息与控制,2018,47(4):385-397.ZHANG Rong,LI Weiping,MO Tong,Review of deep learning［J］.Information and Control,2018,47(4):385-397.(in Chinese)
|
| [18] |
胡越,罗东阳,花奎,等.关于深度学习的综述与讨论［J］.智能系统学报,2019,14(1):1-19.HU Yue,LUO Dongyang,HUA Kui,et al.Overview and discussion on deep learning［J］.Chinese Association of Artificial Intelligence Transactions on Intelligent Systems,2019,14(1):1-19.(in Chinese)
|
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