Fiber positioning technology is widely used in spectroscopic telescopes, and the accurate identification of the fiber position on the focal plane directly affects the efficiency of the astronomical spectrum. At present, fiber positioning usually uses the “back-illuminate” technique to illuminate one end of the fiber. The other end of the fiber is used for detection. The fiber could be stressed or twisted during locator motion, resulting in a difference between the detected fiber position and the actual fiber core. However, the fiber-optic back-illuminated device in the spectrometer system increases the complexity of the system and the time loss of fiber positioning. This paper attempts to use a new method combining image processing with deep learning to identify the fiber ferrule by the front-illuminated method. We built an experimental platform in the lab and experimented with a CMOS camera and telecentric lens. We tested the repeated errors and displacement measurement errors of the two methods. A series of comparative experimental results show that the final detection accuracy of this method can meet the needs of optical fiber positioning in the laboratory, although it has not yet reached the accuracy of the back-illuminated approach. In the future, if the light source and fiber ferrule were specifically designed for the front-illuminated method, its accuracy could be further improved.

中文翻译：

---

基于前光源的多目标光纤高精度位置检测方法

光纤定位技术已广泛应用于光谱望远镜中，并且对焦平面上光纤位置的准确识别直接影响到天文光谱的效率。目前，光纤定位通常使用“背照式”技术来照亮光纤的一端。光纤的另一端用于检测。在定位器运动期间，光纤可能会受力或扭曲，从而导致检测到的光纤位置与实际光纤纤芯之间存在差异。然而，光谱仪系统中的光纤背照式设备增加了系统的复杂性并增加了光纤定位的时间损失。本文尝试使用一种将图像处理与深度学习相结合的新方法，通过前照明方法识别光纤插芯。我们在实验室中建立了一个实验平台，并使用CMOS相机和远心镜头进行了实验。我们测试了这两种方法的重复误差和位移测量误差。一系列比较实验结果表明，该方法的最终检测精度可以满足实验室中光纤定位的需求，尽管尚未达到背照式方法的精度。将来，如果为前照式方法专门设计光源和光纤插芯，则可以进一步提高其精度。一系列比较实验结果表明，该方法的最终检测精度可以满足实验室中光纤定位的需求，尽管尚未达到背照式方法的精度。将来，如果为前照式方法专门设计光源和光纤插芯，则可以进一步提高其精度。一系列比较实验结果表明，该方法的最终检测精度可以满足实验室中光纤定位的需求，尽管尚未达到背照式方法的精度。将来，如果为前照式方法专门设计光源和光纤插芯，则可以进一步提高其精度。