【摘要】 先进树脂基复合材料已成为航空航天领域的热门材料,自动铺放技术是其自动化成型的代表性技术。然而在自动铺放过程中,由于设备精度、轨迹规划、预浸料质量等原因可能会出现各种缺陷,如间隙、搭接和扭转,缺陷不仅会影响构件质量,还会因为需要人工检测导致生产效率难以提高,因此对铺放过程中的缺陷进行自动检测就显得极为重要。本文首先简要介绍了缺陷的成因和影响,然后从不同检测方式出发,介绍了基于红外热成像技术、图像识别技术、轮廓扫描技术等的检测方案和应用,最后对自动铺放表面缺陷检测技术的发展趋势进行了展望。更多还原

【Abstract】 As carbon fiber reinforced plastics(CFRP) become more integrated into the design of large single piece aircraft structures, a new method was developed which is called Automated Fiber Placement(AFP) to improve the efficiency and quality of CFRP manufacturing. AFP systems allow the repeatable placement of uncured, spool fed carbon fiber tape onto substrates in desired thicknesses and orientations. This automated process may incur defects, such as overlapping, gaps, twists which can severely undermine the structural integrity of the part and decrease its property. Current defect detection and abatement methods are very labor intensive, and still mostly rely on human manual inspection. This part of work is time consuming and vulnerable to human error. Studies have shown that manual inspection can consume more than 20% of total production time. The academia is responding to this by focusing on the development of automated inspection systems. This article describes different inspection methods for automated fiber placement process, including traditional methods, laser projectors, thermal camera, profilometers, machine vision and machine learning. Manual inspection with laser projectors can get higher accuracy but still need manual labor. Thermal camera and machine vision basically identify defects from image which might includes noises. Using profilometer is a promising method because the data from it describes accurate profile of surface. Every method has its own advantages and disadvantages, there are still many major problems need to be solved in AFP defect inspection.更多还原