kravenvijay04/ConveyorBelt_Fault_Detection
The project uses computer vision, ultrasonic sensors, and machine learning to detect faults in conveyor belts, enhancing efficiency, reducing downtime, and saving costs in industrial settings.
This system helps operations managers and maintenance teams prevent costly production stoppages by automatically checking industrial conveyor belts for damage. It takes live video feeds and ultrasonic measurements as input to detect cracks, tears, and thickness issues, providing real-time alerts and even initiating shutdowns for severe faults. Plant managers and operations engineers who rely on conveyor systems would use this to ensure continuous operation.
No commits in the last 6 months.
Use this if you need to automatically monitor your conveyor belts for wear and tear, ensuring operational efficiency and preventing unexpected downtime due to belt failures.
Not ideal if you require a simple, manual inspection process or if your industrial setting does not involve conveyor belt systems.
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14
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Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 08, 2025
Commits (30d)
0
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