Optimisation and Validation of an Orbital Dynamic Light Source Defect Detection System Based on Material Surface Roughness

To meet the high standards for surface quality of workpieces in modern industries, there is an urgent need for efficient, low-cost, and adaptable defect detection systems. However, existing bidirectional texture function (BTF) acquisition devices are generally limited by high costs, lengthy acquisition processes, and poor adaptability to different material surfaces, which restrict their practical application. This paper proposes a dynamic light source defect detection system based on material surface roughness, establishes a mapping mechanism between light source elevation angle and roughness, and verifies its adaptability and performance. The system integrates a single angle-adjustable light source (15°, 30°, 45°, 75°), a high-resolution industrial camera, and a rotating sample stage, with a pre-scanning algorithm that automatically determines the optimal elevation angle. Experimental results indicate that the system accurately identifies defects in materials such as glass, wood, and leather, with detection accuracy comparable to multi-camera systems. Meanwhile, hardware cost and acquisition time are significantly reduced, achieving a balance between efficiency, cost, and accuracy, thereby demonstrating strong potential for engineering applications.