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Predictive Maintenance of Ball Bearing using Digital Twin
- 1. Predictive Maintenance of Bearing through Digitaltwins By Barath kumar S B.Tech Mechanical Engineer
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- 3. Modelling and Simulation Thermo-MechanicalModel of the Bearing proposed Frictional Moment Equation: Heat Flow equation: Where, M – Frictional moment N – Speed of the bearing in RPM P- Load on the bearing (N) D- Mean diameter of the bearing f- Friction factor of the bearing v- Dynamic viscosity of the lubricant (m2/s) 3
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- 5. Reduced Order Model Bearing6203 Speed In Rpm Bearing 6203 Max.temperature 5 A Reduced Order Model (ROM) is a simplification of a high-fidelity dynamical model that preserves essential behavior and dominant effects. For the purpose of reducing solution time or storage capacity required for the more complex model.
- 6. IoT Phase Contactless Temperature Sensor (MLX90614) Arduino Wifi Module (ESP 8266) Thing-speak server integration 6
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- 8. Hardware 8 Connected Circuit ESP8266 WifiModule Mlx90614 I2C sensor
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- 10. Digital Twin Meta data Contextand Characteristics Size Gauge Material Geometry Temperature Environment 10
- 11. Digital twin data Metadata of Bearing SKF 6203 11
- 12. Digital twin data Rawtemperature data of Bearing SKF 6203 12
- 13. Twin Building Architecture Thingspeak data •Speed data • Load condition ROM Life degradation algorithm • Smoothened algorithm for better result 13
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- 16. Life degradation results RemainingLife of Bearing: 16
- 17. Remaining Useful Lifetime Remaining useful lifetime of the bearing for different speed and different load conditions are taken into account. Prediction of failure state can be optimized Increasing smart decision making of physical asset RUL can be easily integrate with the maintenance schedule of the industry 17
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