Results 211 to 220 of about 8,705 (267)

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Research on Bearing Fault Diagnosis Based on GMNR and ResNet-CABA-MAGRU. [PDF]

Sensors (Basel)
Chen L, Meng N, Sun W, Yang S, Tian S, Li Y.   +5 more
europepmc   +1 more source

A Multi-Channel Multi-Scale Spatiotemporal Convolutional Cross-Attention Fusion Network for Bearing Fault Diagnosis. [PDF]

Sensors (Basel)
Li R, Zhang G, Niu Y, Rong K, Liu W, Hong H.   +5 more
europepmc   +1 more source

A Spectral Interpretable Bearing Fault Diagnosis Framework Powered by Large Language Models. [PDF]

Sensors (Basel)
Bao P, Yi W, Zhu Y, Shen Y, Peng H.
europepmc   +1 more source

Research on Open-Set Recognition Methods for Rolling Bearing Fault Diagnosis. [PDF]

Sensors (Basel)
Xu J, Wang Y, Xu R, Wang H, Zhou X.
europepmc   +1 more source

A Bearing Fault Diagnosis Method Based on Dual-Stream Hybrid-Domain Adaptation. [PDF]

Sensors (Basel)
Jiao X, Zhang J, Cao J.
europepmc   +1 more source

An improved bistable stochastic resonance method and its application in early bearing fault diagnosis. [PDF]

Sci Rep
Zhao Y, Jiang A, Jiang W, Tang E, Jiang X, Gu X.   +5 more
europepmc   +1 more source

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Bearing Fault Diagnosis Based on Labview

International Journal of Advanced Pervasive and Ubiquitous Computing, 2015
This function of wavelet packet decomposition and the energy of each band to strike is achieved within the Labview module. Signal energy in different frequency bands within the change reflects a change in the operating state. Extract wavelet packet energy spectrum of each band, making it as a feature vector. Finally the fault are classified by SVM. The
Wan-Ye Yao, Xue-Li Jiang
openaire   +1 more source

A fault diagnosis method based on ANFIS and bearing fault diagnosis

2014 International Conference on Information Science, Electronics and Electrical Engineering, 2014
An integrated method of fuzzy clustering, rough sets theory, and adaptive neuro-fuzzy inference system (ANFIS) for fault diagnosis was presented. Xie-Beni cluster-validity was introduced into fuzzy c-means clustering algorithm, and a combination of genetic algorithm and gradient descent approach was applied, to discretize the feature parameters and ...
Junhong Zhang, Wenpeng Ma, Liang Ma
openaire   +1 more source

Bearing fault diagnosis based on feature fusion

2020 IEEE 18th International Conference on Industrial Informatics (INDIN), 2020
Locally linear embedding algorithm is widely utilized to feature extraction, and it is also an effective tool for fault diagnosis. However, locally linear embedding is sensitive to redundancy dimensions, that is, too high dimensions may degrade the performance of it.
Fan Liu, Yansheng Zhang, Zebiao Hu, Xin Li   +3 more
openaire   +1 more source