Bead geometry measurement for wire and arc additive manufacturing using active-passive composite vision sensing based on regional filter
-
摘要: 设计了电弧增材制造熔敷道成形尺寸主被动联合视觉检测方法,以克服结构光主动视觉传感的滞后性与被动视觉传感的信息单一性. 为了实现极高亮度的熔池与极低亮度的结构光条纹在同一CCD靶面同时清晰成像,提出了分区减光策略,对熔池与结构光条纹进行差异化的减光,使二者光强在减光之后水平相当,进而清晰成像. 相机成像光路分析表明,需要将分区减光元件设置在镜头前方一倍焦距以外或镜头后方焦点与靶面之间. 该方法实现了单CCD在一幅图像中同时清晰拍摄熔池和结构光条纹. 开发了一套图像处理算法,实时提取出了熔敷道尺寸. 结果表明,熔敷道高度检测误差优于0.1 mm,宽度检测误差优于0.2 mm.Abstract: An active-passive composite vision sensing system was designed to overcome the delay of active vision sensing and limited information on passive vision sensing. To capture the high brightness molten pool and low brightness structured light clearly in one image, a regional dimming method was proposed to make their brightness decline to the same level. Lightpath analysis showed that the regional dimming filter must be placed in front of the focal point before the lens, or between the CCD sensor and the focal point behind the lens. The molten pool and structured light have been clearly presented in one image using this system. An image processing algorithm for online measurement of bead geometries is proposed. The experimental results showed that the measurement error of bead height is less than 0.1 mm, and that of bead width is less than 0.2 mm.
-
-
表 1 熔敷道成形尺寸检测结果 (mm)
Table 1 Measurement of bead geometries
检测
位置传感器检测的
宽度W1游标卡尺检测
的宽度W2传感器检测的
高度h1游标卡尺检测
的高度h2A 7.63 7.72 2.62 2.56 B 7.70 7.68 2.54 2.60 C 7.85 7.78 2.53 2.46 D 7.67 7.86 2.46 2.52 -
[1] 杨壮, 王天琪, 李亮玉, 等. 厚壁结构件电弧增材制造成形方法及工艺[J]. 焊接学报, 2019, 40(10): 100 − 105. Yang Zhuang, Wang Tianqi, Li Liangyu, et al. Forming method and technology of arc additive manufacturing for thick wall structural parts[J]. Transactions of the China Welding Institution, 2019, 40(10): 100 − 105.
[2] 王天琪, 杨壮, 李亮玉, 等. 悬空特征结构件电弧增材制造成形及算法优化[J]. 焊接学报, 2019, 40(12): 78 − 82. Wang Tianqi, Yang Zhuang, Li Liangyu, et al. Research on forming and welding technology of thick wall structure arc added material manufacturing[J]. Transactions of the China Welding Institution, 2019, 40(12): 78 − 82.
[3] Xiong J, Zhang G, Qiu Z, et al. Vision-sensing and bead width control of a single-bead multi-layer part: material and energy savings in GMAW-based rapid manufacturing[J]. Journal of Cleaner Production, 2013, 41: 82 − 88. doi: 10.1016/j.jclepro.2012.10.009
[4] Xiong J, Zhang G. Online measurement of bead geometry in GMAW-based additive manufacturing using passive vision[J]. Measurement Science and Technology, 2013, 24(11): 115103. doi: 10.1088/0957-0233/24/11/115103
[5] Han Q, Li Y, Zhang G. Online control of deposited geometry of multi-layer multi-bead structure for wire and arc additive manufacturing[J]. Transactions on Intelligent Welding Manufacturing, 2017, 1(1): 85 − 93.
[6] Zeng J, Chang B, Du D, et al. A weld position recognition method based on directional and structured light information fusion in multi-layer/multi-pass welding[J]. Sensors, 2018, 18(1): 129. doi: 10.3390/s18010129
[7] Jin Z, Li H, Li R, et al. 3D reconstruction of GMAW pool surface using composite sensor technology[J]. Measurement, 2019, 133: 508 − 521. doi: 10.1016/j.measurement.2018.10.043
[8] 龚烨飞, 戴先中, 李新德, 等. 结构光视觉鲁棒焊接接头跟踪[J]. 焊接学报, 2010, 31(12): 61 − 64. Gong Yefei, Dai Xianzhong, Li Xinde, et al. Robust joint tracking with structured-light vision sensing[J]. Transactions of the China Welding Institution, 2010, 31(12): 61 − 64.
[9] 宫建锋, 李慧知, 李俐群, 等. 基于同轴图像传感的激光焊接过程质量监测技术[J]. 焊接学报, 2019, 40(1): 37 − 42. doi: 10.12073/j.hjxb.2019400008 Gong Jianfeng, Li Huizhi, Li Liqun, et al. Quality monitoring technology of laser welding process based on coaxial image sensing[J]. Transactions of the China Welding Institution, 2019, 40(1): 37 − 42. doi: 10.12073/j.hjxb.2019400008
[10] 王志江. 脉冲熔化极气体保护焊接熔深自适应区间模型控制[D]. 哈尔滨: 哈尔滨工业大学, 2010. Wang Zhijiang. Adaptive interval model control for depth of weld penetration in pulsed gas metal arc welding[D]. Harbin: Harbin Institute of Technology, 2010.