Metering Fault Diagnosis Model Based on Deep Feature Fitting Network with Mixture of Experts

Author:

Liang Lingyu,Huang Wenqi,Zhao Xiangyu,Jiang Xiaotao,Cao Shang,Zhang Huanming,Hou Jiaxuan,Wang Xin

Publisher

Springer Nature Singapore

Reference10 articles.

1. Zhu G, Chen S, Ren N et al (2021) Fault diagnosis and warning design of wind turbines based on expert system. In: IEEE 4th international conference on automation, electronics and electrical engineering (AUTEEE). IEEE, pp 755–758

2. Wang H, Wei J, Li P (2022) Research on fault diagnosis technology based on deep learning. J Phys: Conf Ser 2187(1):012041

3. Teng S, Li J, He S, Fan B, Hu S (2021) On-line fault diagnosis technology and application based on deep learning of fault characteristic of power grid. J Phys: Conf Ser 2023(1):012023

4. Feng F, Wu C, Zhu J et al (2020) Research on multitask fault diagnosis and weight visualization of rotating machinery based on convolutional neural network. J Braz Soc Mech Sci Eng 42(11):603

5. Li X, Zhang W, Ding Q et al (2020) Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation. J Intell Manuf 31:433–452

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