Zhang Xinman, Gong Weiyong, Xu Xuebin
School of Electronics and Information Engineering MOE Key Lab for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an 710049, China.
Guangdong Xi'an Jiaotong University Academy, Foshan 528000, China.
Sensors (Basel). 2020 Jan 10;20(2):392. doi: 10.3390/s20020392.
Magnetic rings are the most widely used magnetic material product in industry. The existing manual defect detection method for magnetic rings has high cost, low efficiency and low precision. To address this issue, a magnetic ring multi-defect stereo detection system based on multi-camera vision technology is developed to complete the automatic inspection of magnetic rings. The system can detect surface defects and measure ring height simultaneously. Two image processing algorithms are proposed, namely, the image edge removal algorithm (IERA) and magnetic ring location algorithm (MRLA), separately. On the basis of these two algorithms, connected domain filtering methods for crack, fiber and large-area defects are established to complete defect inspection. This system achieves a recognition rate of 100% for defects such as crack, adhesion, hanger adhesion and pitting. Furthermore, the recognition rate for fiber and foreign matter defects attains 92.5% and 91.5%, respectively. The detection speed exceeds 120 magnetic rings per minutes, and the precision is within 0.05 mm. Both precision and speed meet the requirements of real-time quality inspection in actual production.
磁环是工业上应用最为广泛的磁性材料产品。现有的磁环人工缺陷检测方法成本高、效率低且精度低。为解决这一问题，开发了一种基于多相机视觉技术的磁环多缺陷立体检测系统，以完成磁环的自动检测。该系统能够同时检测表面缺陷并测量磁环高度。分别提出了两种图像处理算法，即图像边缘去除算法（IERA）和磁环定位算法（MRLA）。基于这两种算法，建立了针对裂纹、纤维和大面积缺陷的连通域滤波方法，以完成缺陷检测。该系统对裂纹、粘连、挂具粘连和麻点等缺陷的识别率达到100%。此外，对纤维和异物缺陷的识别率分别达到92.5%和91.5%。检测速度超过每分钟120个磁环，精度在0.05毫米以内。精度和速度均满足实际生产中实时质量检测的要求。
