Fault Diagnosis of Motor Bearing Based on Current Bi-Spectrum and Convolutional Neural Network

Author:

Ma Jiaojiao1ORCID,Jiang Lingli1ORCID,Li Shuhui1ORCID,Sheng Heshan1ORCID,Zhou Cheng2ORCID,Li Xuejun1ORCID

Affiliation:

1. Foshan University, China

2. Chengdu CRRC Electric Motor Co. Ltd, China

Publisher

FapUNIFESP (SciELO)

Subject

Mechanical Engineering,Mechanics of Materials,Ocean Engineering,Aerospace Engineering,Automotive Engineering,General Materials Science,Civil and Structural Engineering

Reference30 articles.

1. Electrical Signature Analysis-Based Detection of External Bearing Faults in Electromechanical Drivetrains;Rifat S. M.;IEEE Transactions on Industrial Electronics,2018

2. Fault Detection in High Speed Helical Gears Considering Signal Processing Method in Real Simulation;Adnani A A T;Latin American Journal of Solids and Structures,2016

3. A torque-based method for the study of roller bearing degradation under poor lubrication conditions in a lead-bismuth environment;Gesseneck J. J. v.;Nuclear Engineering and Design,2016

4. Rotor Speed-Based Bearing Fault Diagnosis (RSB-BFD) Under Variable Speed and Constant Load;Hamadache Moussa;IEEE Transactions on Industrial Electronics,2015

5. Bearing Fault Diagnosis Using Motor Current Signature Analysis and the Artificial Neural Network;Dhomad T. A.;International Journal on Advanced Science, Engineering and Information Technology,2020

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on convolutional neural networks in motor fault diagnosis;Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023);2024-04-01

2. A novel bearing current signal diagnosis method combining variational modal decomposition and improved random forests;Review of Scientific Instruments;2024-02-01

3. LiteFDNet: A Lightweight Network for Current Sensor-Based Bearing Fault Diagnosis;IEEE Access;2024

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