A Domain Adaptive Method with Orthogonal Constraint for Predicting the Remaining Useful Life of Rolling Bearings under Cross Working Conditions

HAN Yan; LIN Zhichao; HUANG Qingqing; XIANG Min; WEN Rui; ZHANG Yan

doi:10.11999/JEIT230274

Volume 46 Issue 3

Mar. 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(3): 1043-1050

HAN Yan, LIN Zhichao, HUANG Qingqing, XIANG Min, WEN Rui, ZHANG Yan. A Domain Adaptive Method with Orthogonal Constraint for Predicting the Remaining Useful Life of Rolling Bearings under Cross Working Conditions[J]. Journal of Electronics & Information Technology, 2024, 46(3): 1043-1050. doi: 10.11999/JEIT230274

Citation:

HAN Yan, LIN Zhichao, HUANG Qingqing, XIANG Min, WEN Rui, ZHANG Yan. A Domain Adaptive Method with Orthogonal Constraint for Predicting the Remaining Useful Life of Rolling Bearings under Cross Working Conditions[J]. Journal of Electronics & Information Technology, 2024, 46(3): 1043-1050. doi: 10.11999/JEIT230274

Citation:

HAN Yan, LIN Zhichao, HUANG Qingqing, XIANG Min, WEN Rui, ZHANG Yan. A Domain Adaptive Method with Orthogonal Constraint for Predicting the Remaining Useful Life of Rolling Bearings under Cross Working Conditions[J]. Journal of Electronics & Information Technology, 2024, 46(3): 1043-1050. doi: 10.11999/JEIT230274

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A Domain Adaptive Method with Orthogonal Constraint for Predicting the Remaining Useful Life of Rolling Bearings under Cross Working Conditions

doi: 10.11999/JEIT230274 cstr: 32379.14.JEIT230274

HAN Yan^{1, 2},
LIN Zhichao¹,
HUANG Qingqing^{1, 2
,
,},
XIANG Min¹,
WEN Rui¹,
ZHANG Yan^{1, 2}

1.
School of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Industrial Internet Reaearch Institute of Chongqing University of Posts and Telecommunications, Chongqing 401122, China

Funds: National Key Research and Development Program of China (2022YFE0114300), Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN202100612), Chongqing Postdoctoral Science Foundation (cstc2021jcyj-bshX0094)

Received Date: 2023-04-17
Rev Recd Date: 2023-07-14

Available Online: 2023-07-21

Publish Date: 2024-03-27

Abstract

Abstract

To address the problems that blurred decision boundaries and low identifiability of features in the rolling bearing Remaining Useful Life (RUL) prediction under cross working conditions, a domain adaptive method with Maximum Classifier Discrepancy network with Orthogonal Constraints (MCD_OC) is proposed. Firstly, the fast Fourier transform is applied to transform the raw vibration signal into the frequency domain signal and input it to the model. Then, Convolutional Neural Network (CNN) and Gate Recurrent Unit (GRU) are used to extract the depth spatiotemporal features of the bearing signal, the source and target domain feature is aligned using the maximum classifier discrepancy, and the orthogonal constraint is applied to constrain target domain features to increase the identifiability between features of unlabeled target domain feature. Finally, comparative experiments are conducted on the prediction of cross working condition RUL predict based on the bearing life dataset to evaluate the method in this work, and the optimal results are obtained in multiple experiments.
- Rolling bearing,
- Remaining Useful Life(RUL),
- Orthogonal constraint,
- Maximum classifier discrepancy

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References(18)

References

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