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Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles
Due to the limited capacity and voltage of single battery cell, the battery system for electric
vehicles often consists of hundreds or thousands of single cells in series and parallel …
vehicles often consists of hundreds or thousands of single cells in series and parallel …
[HTML][HTML] Intelligent fault diagnosis methods for hydraulic piston pumps: a review
As the modern industry rapidly advances toward digitalization, networking, and intelligence,
intelligent fault diagnosis technology has become a necessary measure to ensure the safe …
intelligent fault diagnosis technology has become a necessary measure to ensure the safe …
A novel deep learning method for intelligent fault diagnosis of rotating machinery based on improved CNN-SVM and multichannel data fusion
Intelligent fault diagnosis methods based on deep learning becomes a research hotspot in
the fault diagnosis field. Automatically and accurately identifying the incipient micro-fault of …
the fault diagnosis field. Automatically and accurately identifying the incipient micro-fault of …
A rotating machinery fault diagnosis method based on multi-scale dimensionless indicators and random forests
Q Hu, XS Si, QH Zhang, AS Qin - Mechanical systems and signal …, 2020 - Elsevier
Fault diagnosis methods based on dimensionless indicators have long been studied for
rotating machinery. However, traditional dimensionless indicators frequently suffer a low …
rotating machinery. However, traditional dimensionless indicators frequently suffer a low …
A data-driven-based fault diagnosis approach for electrical power DC-DC inverter by using modified convolutional neural network with global average pooling and 2 …
W Gong, H Chen, Z Zhang, M Zhang, H Gao - Ieee Access, 2020 - ieeexplore.ieee.org
A novel convolutional neural network namely the modified CNN-GAP model is proposed for
fast fault diagnosis of the DC-DC inverter. This method improves the model structure of the …
fast fault diagnosis of the DC-DC inverter. This method improves the model structure of the …
An optimized variational mode decomposition and symmetrized dot pattern image characteristic information fusion-based enhanced CNN ball screw vibration …
F Yang, X Tian, L Ma, X Shi - Measurement, 2024 - Elsevier
The failure of the ball screw in the machine tool presents various types and complex
coupling characteristics, which pose challenges in extracting fault features from vibration …
coupling characteristics, which pose challenges in extracting fault features from vibration …
A novel quality-related incipient fault detection method based on canonical variate analysis and Kullback–Leibler divergence for large-scale industrial processes
J Dong, L Jiang, C Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Quality-related fault detection is an effective way to ensure the stability of product quality and
the safety of industrial processes. Quality abnormality is often caused by incipient faults …
the safety of industrial processes. Quality abnormality is often caused by incipient faults …
A hybrid signal-based fault diagnosis method for lithium-ion batteries in electric vehicles
A large proportion of electric vehicle accidents are attributed to lithium-ion battery failure
recently, which demands the time-efficient diagnosis and safety warning in advance of …
recently, which demands the time-efficient diagnosis and safety warning in advance of …
A deep belief rule base-based fault diagnosis method for complex systems
BY Zhao, QX Zhang, W He, P Han, Y Cao, GH Zhou - ISA transactions, 2024 - Elsevier
Complex systems are prone to faults due to their intricate structures, potentially impacting
system stability. Therefore, fault diagnosis has become crucial for maintaining stable …
system stability. Therefore, fault diagnosis has become crucial for maintaining stable …
Improved deep PCA and Kullback–Leibler divergence based incipient fault detection and isolation of high-speed railway traction devices
Enhancing the reliability of high-speed railway traction system is critical important to the
safety of entire trains. Data-driven based FDD (Fault Detection and Diagnosis) schemes …
safety of entire trains. Data-driven based FDD (Fault Detection and Diagnosis) schemes …