Intelligent fault diagnosis of bearings under small samples: A mechanism-data fusion approach

Author:

Xu Kun,Kong Xianguang,Wang Qibin,Han Bing,Sun LiqiangORCID

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference57 articles.

1. A review of artificial intelligence methods for condition monitoring and fault diagnosis of rolling element bearings for induction motor;AlShorman;Shock Vib.,2020

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3. Domain adversarial transfer network for cross-domain fault diagnosis of rotary machinery;Chen;IEEE Trans. Instrum. Meas.,2020

4. Remaining useful life prediction combined dynamic model with transfer learning under insufficient degradation data;Cheng;Reliab. Eng. Syst. Saf.,2023

5. An innovative deep anomaly detection of building energy consumption using energy time-series images;Copiaco;Eng. Appl. Artif. Intell.,2023

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