rolling bearing;
residual life prediction;
multi-scale feature extraction;
attention mechanism;
CONVOLUTIONAL NEURAL-NETWORK;
RECOGNITION;
D O I:
10.3390/electronics11213616
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
In response to the problems of difficult identification of degradation stage start points and inadequate extraction of degradation features in the current rolling bearing remaining life prediction method, a rolling bearing remaining life prediction method based on multi-scale feature extraction and attention mechanism is proposed. Firstly, this paper takes the normalized bearing vibration signal as input and adopts a quadratic function as the RUL prediction label, avoiding identifying the degradation stage start point. Secondly, the spatial and temporal features of the bearing vibration signal are extracted using the dilated convolutional neural network and LSTM network, respectively, and the channel attention mechanism is used to assign weights to each degradation feature to effectively use multi-scale information. Finally, the mapping of bearing degradation features to remaining life labels is achieved through a fully connected layer for the RUL prediction of bearings. The proposed method is validated using the PHM 2012 Challenge bearing dataset, and the experimental results show that the predictive performance of the proposed method is superior to that of other RUL prediction methods.
机构:
College of Automation Engineering, Nanjing University of Aeronautics and AstronauticsCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics
LEI Xue
LU Ningyun
论文数: 0引用数: 0
h-index: 0
机构:
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics
State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and AstronauticsCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics
LU Ningyun
CHEN Chuang
论文数: 0引用数: 0
h-index: 0
机构:
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics
College of Electrical Engineering and Control Science, Nanjing Tech UniversityCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics
CHEN Chuang
HU Tianzhen
论文数: 0引用数: 0
h-index: 0
机构:
College of Automation Engineering, Nanjing University of Aeronautics and AstronauticsCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics
HU Tianzhen
JIANG Bin
论文数: 0引用数: 0
h-index: 0
机构:
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics
State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and AstronauticsCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics
机构:
Univ Shanghai Sci & Technol, Sch Energy & Power Engn, Shanghai 200093, Peoples R China
Liverpool John Moores Univ, Dept Maritime & Mech Engn, Byrom St, Liverpool L3 3AF, Merseyside, EnglandUniv Shanghai Sci & Technol, Sch Energy & Power Engn, Shanghai 200093, Peoples R China
Xu, Zifei
Li, Chun
论文数: 0引用数: 0
h-index: 0
机构:
Univ Shanghai Sci & Technol, Sch Energy & Power Engn, Shanghai 200093, Peoples R ChinaUniv Shanghai Sci & Technol, Sch Energy & Power Engn, Shanghai 200093, Peoples R China
Li, Chun
Yang, Yang
论文数: 0引用数: 0
h-index: 0
机构:
Univ Shanghai Sci & Technol, Sch Energy & Power Engn, Shanghai 200093, Peoples R China
Liverpool John Moores Univ, Dept Maritime & Mech Engn, Byrom St, Liverpool L3 3AF, Merseyside, EnglandUniv Shanghai Sci & Technol, Sch Energy & Power Engn, Shanghai 200093, Peoples R China