搅拌摩擦焊缝涡流检测
Eddy Current Testing of Friction Stir Welds
摘要: 在搅拌摩擦焊焊接过程中，因为工艺参数和搅拌头设计选择不当等因素，会产生焊接缺陷这样的问题，本文设计了三维运动机械装置对搅拌摩擦焊缝进行C扫实现涡流检测。通过ANSYS和ADAMS对滚珠丝杠进行仿真，分析其在瞬态下的载荷以及其线性关系。为了提高缺陷检测能力，只有依靠分析差分检测信号的特性，进而获得检测到的缺陷信息，故而本文设计了圆台状脉冲涡流传感器，并对其进行磁场解析。借助COMSOL对其进行了电磁仿真，对比了有无缺陷的铝试件磁场分布图像和有无屏蔽罩的磁场图像。基于铁磁性材料存在的磁屏蔽，进行了铁磁性仿真试验研究。接着使用蚁群算法进行轮廓识别，对信号依次进行奇异值分解去噪、卡尔曼滤波、RBF优化卡尔曼滤波。最后建立VB人机操作界面进行有效地控制。
Abstract: In the process of friction stir welding (FSW), due to the improper selection of process parameters and the design of the stir head, there will be welding defects. In this paper, a three-dimensional motion mechanical device is designed to carry out C-scan for friction stir welding to realize eddy current detection. ANSYS and Adams are used to simulate the ball screw, and the transient load and its linear relationship are analyzed. In order to improve the ability of defect detection, only by analyzing the characteristics of differential detection signal, and then obtaining the detected defect information, this paper designs a cone-shaped pulsed eddy current sensor, and analyzes its magnetic field. The electromagnetic simulation was carried out by COMSOL, and the magnetic field distribution images of aluminum specimen with and without defects were compared with those with or without shield cover. Based on the magnetic shielding existing in ferromagnetic materials, the ferromagnetic simulation experiment was carried out. Then, the ant colony algorithm is used for contour recognition, and singular value decomposition (SVD) denoising, Kalman filtering and RBF optimized Kalman filtering are carried out successively. Finally, VB man-machine interface is established for effective control.
文章引用：李佳兵, 高紫韵, 戴钧, 任超群, 李欢. 搅拌摩擦焊缝涡流检测[J]. 图像与信号处理, 2020, 9(4): 226-245. https://doi.org/10.12677/JISP.2020.94027

参考文献

[1] Ma, Z.Y. (2008) Friction Stir Processing Technology: A Review. Metallurgical and Materials Transactions A, 39, 642-658.
[Google Scholar] [CrossRef] 
[2] 栾国红, 郭德伦, 张田仓, 等. 搅拌摩擦焊在飞机制造工业中的应用[J]. 航空制造技, 2002(11): 11-20.
[3] Takeshi, S. (2001) Recent Development of a Friction Stir Welding New Solid State Joining Technology. International Journal of Materials and Product Technology, 2, 453-456.
[4] 王快社, 王训宏, 沈洋, 等. 搅拌摩擦焊技术的最新进展[J]. 热加工工艺, 2004(10): 53-55.
[5] 周万盛, 姚君山. 铝及铝合金的焊接[M]. 北京: 机械工业出版社, 2006.
[6] Kinchen, D.G. and Aldahir, E. (2002) NDE of Friction Stir Welds in Aerospace Applications. Lockheed Martin Michoud Space Systems, New Orleans, 1-7.
[7] Ofune, M.D., et al. (2016) Development of Valve Train Rig for Assessment of Cam/Follow Tribochemistry. Tribology International, 93, 733-744.
[Google Scholar] [CrossRef] 
[8] Mahaut, S., Jenson, F., Calmon, P., Darmon, M. and Chatillon, S. (2009) Recent Advances and Current Trends of in CIVA. Insight-Non-Destructive Testing and Condition Monitoring, 51, 78-81.
[Google Scholar] [CrossRef] 
[9] Sophian, A. (2003) Characterization of Surface and Sub-Surface Discontinuities in Metals Using Pulsed Eddy Current Sensors. The University of Huddersfield in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy, The United Kingdom.
[10] Zhang, J., He, K., Zheng, X., et al. (2010) An Ant Colony Optimization Algorithm for Image Edge Detection. Internal Conference on Artification Intelligence and Compulation Intelligence, Sanya, 23-24 October 2010, 215-219.
[Google Scholar] [CrossRef] 
[11] 王俊, 周德强, 肖俊峰, 等. 铁磁性材料脉冲涡流检测信号的消噪方法[J]. 无损检测, 2016, 38(1): 44-48.
[12] Hassanpour, H., Zehtabian, A. and Sadati, S.J. (2012) Time Domain Signal Enhancement Based on an Optimized Singular Vector Denoising Algorithm. Digital Signal P, 22, 786-794.
[Google Scholar] [CrossRef] 
[13] 宋文尧. 卡尔曼滤波[M]. 北京: 科学出版社, 1991.
[14] 田景文, 高美娟. 人工神经网络算法研究及应用[M]. 北京: 北京理工大学出版社, 2006.