Improved Deep Transfer Auto-Encoder for Fault Diagnosis of Gearbox Under Variable Working Conditions With Small Training Samples
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2936243
Abstract: It is considerable to solve practical fault diagnosis task of gearbox under variable working conditions by introducing sufficient auxiliary data. For this purpose, a new approach called improved deep transfer auto-encoder is proposed for intelligent… read more here.
Keywords: variable working; working conditions; gearbox variable; transfer ... See more keywords
A Novel Data-Driven Fault Feature Separation Method and Its Application on Intelligent Fault Diagnosis Under Variable Working Conditions
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2996713
Abstract: As mechanical fault diagnosis enters the era of big data, the traditional fault diagnosis methods under variable working condition are difficult to be applied because of the massive computation cost and excessive reliance on human… read more here.
Keywords: working condition; diagnosis; variable working; fault diagnosis ... See more keywords
Bearing Fault Diagnosis Under Variable Working Conditions Base on Contrastive Domain Adaptation Method
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3200106
Abstract: Lack of massive-labeled samples may cause the performance degradation of intelligent bearing fault diagnosis methods under variable working conditions. Unsupervised domain adaptation (UDA)-based methods can effectively alleviate this problem by decreasing the distribution discrepancy between… read more here.
Keywords: fault diagnosis; diagnosis; domain; variable working ... See more keywords
A Discriminative Feature-Based Fault Diagnosis Network for Planetary Gearboxes Under Variable Working Conditions
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2025.3548071
Abstract: In planetary gearbox fault diagnosis under variable working conditions, the method based on unsupervised domain adaptive is to correct the data shift between different working conditions. However, the current methods only focus on extracting invariant… read more here.
Keywords: feature; variable working; fault diagnosis; working conditions ... See more keywords
Small Sample-Oriented Variable Working Condition Fault Diagnosis via Nondata-Enhanced Multicategory Contrastive Learning
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2025.3551486
Abstract: In real-world industrial scenarios, production equipment and process systems usually operate under variable working conditions, and abnormal/faulty samples are hard to collect, bringing great challenges in implementing intelligent fault diagnosis. This work presents a novel… read more here.
Keywords: small sample; variable working; fault diagnosis; fault ... See more keywords
DMWMN: A Deep Modulation Network for Gearbox Intelligent Fault Detection Under Variable Working Conditions
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2024.3416674
Abstract: Convolutional neural network (CNN) has shown great potential in real-time gearbox monitoring. In practical engineering, due to the complex multitooth meshing motions and variable working conditions resulting in gearboxes with multiple excitation sources, and the… read more here.
Keywords: fault; variable working; network; modulation ... See more keywords
The optimized local sparse parallel multi-channel deep convolutional neural network-LSTM and the application in bearing fault diagnosis under noise and variable working condition
Sign Up to like & getrecommendations! Published in 2024 at "Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science"
DOI: 10.1177/09544062241281096
Abstract: Since the actual operation of the bearing inevitably exists in both noise and variable working conditions, most of the traditional networks can only deal with them alone, and the fault identification result will be significantly… read more here.
Keywords: variable working; neural network; bearing fault; noise variable ... See more keywords
Ensemble weighted DJPMMD based deep transfer metric learning method for fault diagnosis of bearing under variable working conditions
Sign Up to like & getrecommendations! Published in 2025 at "Structural Health Monitoring"
DOI: 10.1177/14759217251378855
Abstract: Intelligent fault diagnosis of bearings under variable working conditions remains a challenging task. Although the deep transfer learning model can effectively diagnose the faults of bearing under variable working conditions, the diagnosis accuracy and stability… read more here.
Keywords: diagnosis; deep transfer; fault; transfer ... See more keywords