MotorShield
Project Overview
MotorShield is an AI tool that predicts motor failure before it happens. Instead of waiting for breakdowns, we use motor signal data to estimate risk early, saving money and keeping systems running smoothly.
Less downtime
Unexpected motor failure can shut down an entire operation. MotorShield helps catch warning signs early so teams can act before things go down.
Lower cost
Predicting issues early helps reduce emergency repair costs, delays, and part replacement caused by waiting too long.
Clear decisions
Instead of raw sensor graphs, we summarize motor condition into a simple health score and trend that's easy to read fast.
How it works
MotorShield follows a simple pipeline: simulate motor data, train the model, validate with sensors, and show results through a dashboard.
Simulate
Learn
Collect
Predict
Simulink Simulation
We generate motor behavior in a controlled environment. This creates realistic data with both healthy and failing conditions.
Deep Learning Model
We train a model to detect patterns that appear before failure happens. Our current best approach is a CNN -> Transformer pipeline for time-series data.
Microcontroller + Sensors
Eventually, we'll collect real motor readings using sensors and a microcontroller, then run predictions in real time to validate performance outside simulation.
Website Dashboard
The web app visualizes motor health, trends, and failure risk in a clean format that's easy to understand.
Example Output
Motor Health
82
out of 100
Status
Healthy