A Review on Convolutional Neural Network in Bearing Fault Diagnosis

¹ Intelligent Dynamics System, Malaysia Japan International Institute of Technology, Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100 Kuala Lumpur, Malaysia
² Institute of Noise and Vibration, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100 Kuala Lumpur, Malaysia
³ CAIRO, Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100 Kuala Lumpur, Malaysia

^* Corresponding author: tiah14@gmail.com

Abstract

As the degradation of bearing yield to an enormous adverse impact on machinery and the damage that comes within could jeopardize human precious life. Hence, the bearing fault diagnosis is indisputably indispensable. This paper is predominantly focused on the utilization of Convolutional Neural Network (CNN) in bearing fault diagnosis of the rolling bearing. By deployment of CNN, an accurate diagnosis can be achieved without the necessity of pre-training the data. The function of CNN in diagnosing the bearing and architecture development of CNN are discussed. Lastly, to establish new and significant contribution in this area, new challenges are pinpointed.