Remote fault monitoring platform for rolling bearings based on digital twin

Deep groove ball bearings are crucial components in rotating machinery, and their failures can lead to equipment shutdown and significant economic losses. To address the issue of simulating bearing failures, this article proposes an innovative method to establish a mathematical twin dynamic model that successfully simulates the fault characteristics of various components of deep groove ball bearings. Vibration and acceleration data are simulated using Simulink, and experimental comparisons are conducted to demonstrate the accuracy and practicality of the simulations. Additionally, a digital twin platform is constructed using a web-based front-end to enable data interaction and twins, providing powerful support for the research and prevention of deep groove ball bearing failures. Identify relevant articles in literature searches, great care should be taken in constructing both.