AUTOMATED MOTOR FAULT ANTICIPATION SYSTEM

This project is about the design and development of a Motor Fault Detection and Prediction System that uses Artificial Intelligence and Machine Learning. The system was made to check the health of a motor by collecting important information like temperature and current and voltage and vibration and speed and load condition all the time. The system uses sensors to get this information and machine learning to find problems with the motor. This means it can find things the motor is doing and common problems like getting too hot or being overloaded or having issues with the bearings or being out of balance or not moving or vibrating too much. Using Artificial Intelligence and Machine Learning makes the system better at finding faults because it can look at the motor data in a way instead of just looking at it manually or using fixed rules. The system was. It works well. It can check how the motor is doing. Say if it is healthy or not and help find problems early. This system can also help predict when the motor might have a problem which means it can help reduce the time the motor is not working and make it more reliable and cost less to fix in factories and other places where motors are used. Over all this project is a way to check the condition of motors and predict problems because it is cheap and can be used in many places and it is smart. This makes it good for people who are studying motors and for people who use motors in their work. The Motor Fault Detection and Prediction System is a solution, for people who want to keep their motors running well.

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