Semi-supervised adversarial discriminative learning approach for intelligent fault diagnosis of wind turbine
Wind turbines play a crucial role in renewable energy generation systems and are frequently
exposed to challenging operational environments. Monitoring and diagnosing potential …
exposed to challenging operational environments. Monitoring and diagnosing potential …
A new multi-sensor fusion with hybrid Convolutional Neural Network with Wiener model for remaining useful life estimation
With the development of smart manufacturing, the health monitoring of the machines has
become important. Remaining useful life (RUL) estimation, which could predict the future …
become important. Remaining useful life (RUL) estimation, which could predict the future …
A unified out-of-distribution detection framework for trustworthy prognostics and health management in renewable energy systems
With the advances in artificial intelligence, there is a growing expectation of more automatic
and intelligent prognostics and health management (PHM) systems for the real-time …
and intelligent prognostics and health management (PHM) systems for the real-time …
Fault diagnosis of wind turbine gearbox under limited labeled data through temporal predictive and similarity contrast learning embedded with self-attention …
Y Zhu, B Xie, A Wang, Z Qian - Expert Systems with Applications, 2024 - Elsevier
Data-driven models for wind turbine (WT) gearbox health monitoring have garnered
significant attention. However, these models usually depend on extensive manually labeled …
significant attention. However, these models usually depend on extensive manually labeled …
WSAFormer-DFFN: A model for rotating machinery fault diagnosis using 1D window-based multi-head self-attention and deep feature fusion network
Q Wei, X Tian, L Cui, F Zheng, L Liu - Engineering Applications of Artificial …, 2023 - Elsevier
Fault diagnosis is of great importance for rotating machinery maintenance. Deep learning is
an intelligent diagnosis technology that attracts more attention at present. The ability to learn …
an intelligent diagnosis technology that attracts more attention at present. The ability to learn …
Residual attention temporal recurrent network for fault diagnosis of gearboxes under limited labeled data
J Zhuang, J Yan, CG Huang, M Jia - Engineering Applications of Artificial …, 2024 - Elsevier
Data-driven fault diagnosis methods have significantly contributed to the rapid development
of prognostics and health management of gearboxes. However, these methods require …
of prognostics and health management of gearboxes. However, these methods require …
[HTML][HTML] A deep convolutional neural network for vibration-based health-monitoring of rotating machinery
The gearbox is a critical component in the mechanical system, requiring vigilant monitoring
to prevent adverse consequences on safety and quality due to malfunction. Therefore, early …
to prevent adverse consequences on safety and quality due to malfunction. Therefore, early …
Multi-modal data cross-domain fusion network for gearbox fault diagnosis under variable operating conditions
Gearbox fault diagnosis is a critical aspect of machinery maintenance and reliability, as it
ensures the safe and efficient operation of various industrial systems. The cross-domain fault …
ensures the safe and efficient operation of various industrial systems. The cross-domain fault …
Generative adversarial networks driven by multi-domain information for improving the quality of generated samples in fault diagnosis
The performance of intelligent fault diagnosis models is often hindered by the lack of
available samples, a common issue in both the few-shot learning and imbalanced learning …
available samples, a common issue in both the few-shot learning and imbalanced learning …
Dynamic model-driven intelligent fault diagnosis method for rotary vector reducers
J Zheng, H Wang, A Kumar, J Xiang - Engineering Applications of Artificial …, 2023 - Elsevier
The diagnosis of faults in rotary vector (RV) reducers using machine data-driven artificial
intelligence (AI) models plays an important role, but it is difficult to obtain complete fault …
intelligence (AI) models plays an important role, but it is difficult to obtain complete fault …