MikuniAdvanced Computer Vision Project

DEFECT DETECTION MACHINE

Types of Defects: Cracks, wear, or corrosion on machine parts. Misalignment of components. Deformation or bending in structures. Electrical faults like short circuits or insulation breakdown. Lubrication issues and bearing wear. Excessive vibration, temperature, or noise.

Detection Methods: Visual Inspection: Human or automated systems using cameras and sensors to detect surface defects. Non-Destructive Testing (NDT): Techniques like ultrasonic, X-ray, and magnetic testing to detect internal defects without damaging the machine. Thermography: Using thermal cameras to identify hot spots indicating possible issues such as overheating. Vibration Analysis: Monitoring vibrations to detect misalignment, imbalance, or wear. Acoustic Emission: Listening to high-frequency sound waves produced by crack formation, leaks, or material deformation. Machine Learning: Advanced AI models that analyze data from sensors to detect patterns indicative of defects.

Applications: Manufacturing and assembly lines. Aerospace and automotive industries. Power generation and electrical equipment. Industrial machinery and robotics.

Benefits: Increased Safety: Early detection prevents accidents or breakdowns. Reduced Downtime: Identifying and addressing defects before they lead to machine failure helps in maintaining continuous operations. Cost Savings: Minimizes expensive repairs and replacements by detecting issues early. Improved Product Quality: Ensures machinery functions at optimal levels, leading to higher-quality products.