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Motor Bearing and Rotor Fault Detection using Vibration and Current Signature

Approx. component budget: Rs. 5,000 - 10,000

Objective

Detect and identify common motor faults at an early stage using signals.

What you will build

A set-up that records vibration with an accelerometer and motor current, then uses FFT to find signatures of bearing wear, imbalance and a loose mount.

Results you can expect

• FFT peaks for healthy vs faulty cases (added mass, damaged bearing, loose bolt)
• Detection accuracy of a simple classifier
• And amplitude vs fault severity

What you will learn

Signal processing, FFT, condition monitoring and predictive maintenance.

Tools and notes

ADXL345 or MPU6050, ESP32, current sensor, Python (SciPy), small induction motor. Keep guards on the shaft and do not run damaged bearings for long.

Resume points from this project

• Built and tested Motor Bearing and Rotor Fault Detection using Vibration and Current Signature; objective: detect and identify common motor faults at an early stage using signals.
• Measured and analysed fFT peaks for healthy vs faulty cases (added mass, damaged bearing, loose bolt) and detection accuracy of a simple classifier; wrote the report and presented the results in a viva. Add your own numbers: [x].

Replace [x] with your own measured results. Write only what you really did.

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