Prediction of remaining useful life based on t-SNE and LSTM for rotating machinery

被引:0
|
作者
Ge, Yang [1 ,2 ]
Guo, Lanzhong [1 ,2 ]
Niu, Shuguang [1 ,2 ]
Dou, Yan [1 ,2 ]
机构
[1] School of Mechanical Engineering, Changshu Institute of Technology, Changshu,215500, China
[2] Jiangsu elevator intelligent safety key construction laboratory, Changshu,215500, China
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Long short-term memory
引用
收藏
页码:223 / 231
相关论文
共 50 条
  • [1] Remaining useful life prediction of rotating machinery based on KPCA-LSTM
    Cao, Xiangang
    Ye, Yu
    Zhao, Youjun
    Duan, Yong
    Yang, Xinu
    [J]. Zhendong yu Chongji/Journal of Vibration and Shock, 2023, 42 (24): : 81 - 91
  • [2] A fault identification method of rotating machinery based on t-SNE
    Gu, Yuhai
    He, Linfeng
    Deng, Yali
    [J]. Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2016, 37 : 152 - 156
  • [3] A novel prediction network for remaining useful life of rotating machinery
    Lin, Tianjiao
    Wang, Huaqing
    Guo, Xudong
    Wang, Pengxin
    Song, Liuyang
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2023, 124 (11-12): : 4009 - 4018
  • [4] A novel prediction network for remaining useful life of rotating machinery
    Tianjiao Lin
    Huaqing Wang
    Xudong Guo
    Pengxin Wang
    Liuyang Song
    [J]. The International Journal of Advanced Manufacturing Technology, 2023, 124 : 4009 - 4018
  • [5] Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator
    Qin, Aisong
    Zhang, Qinghua
    Hu, Qin
    Sun, Guoxi
    He, Jun
    Lin, Shuiquan
    [J]. SHOCK AND VIBRATION, 2017, 2017
  • [6] An Attention-Based Method for Remaining Useful Life Prediction of Rotating Machinery
    Deng, Yaohua
    Guo, Chengwang
    Zhang, Zilin
    Zou, Linfeng
    Liu, Xiali
    Lin, Shengyu
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (04):
  • [7] Feature reconstruction based on t-SNE: an approach for fault diagnosis of rotating machinery
    Chen, Jiayu
    Zhou, Dong
    Lyu, Chuan
    Lu, Chen
    [J]. JOURNAL OF VIBROENGINEERING, 2017, 19 (07) : 5047 - 5060
  • [8] Dynamic weighted federated remaining useful life prediction approach for rotating machinery
    Qin, Yi
    Yang, Jiahong
    Zhou, Jianghong
    Pu, Huayan
    Zhang, Xiangfeng
    Mao, Yongfang
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 202
  • [9] Remaining useful life prediction of machinery based on K-S distance and LSTM neural network
    Ge, Yang
    Guo, Lanzhong
    Dou, Yan
    [J]. International Journal of Performability Engineering, 2019, 15 (03) : 895 - 901
  • [10] The Prediction of the Remaining Useful Life of Rotating Machinery Based on an Adaptive Maximum Second-Order Cyclostationarity Blind Deconvolution and a Convolutional LSTM Autoencoder
    Gao, Yangde
    Ahmad, Zahoor
    Kim, Jong-Myon
    [J]. SENSORS, 2024, 24 (08)