基于特征识别的汽车复杂零件自校正检测系统
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吉林省优秀青年人才基金项目(No.20200103238JH)资助。


Self correcting detection system of automobile complex parts based on feature recognition
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    摘要:

    为了解决复杂零件在自动化装配过程中位置偏差与位姿偏角造成的装配问题,实现具有反馈调整能力的机械臂扫描控制,设计了基于激光三维扫描的实时检测系统。系统通过光栅扫描方式获取零件的三维面形数据,并利用边缘特征识别完成零件匹配,最终达到在工装环境下自动调整位置与位姿的目的。实验对SP165型机械臂进行控制,以6自由度参数作为检测精度的评价指标,分别对基于零件数模的仿真数据、固定扫描路径测试数据和自动调整扫描路径测试数据进行对比分析。结果显示,采用本系统完成自动路径调整的最大位置偏差和最大位姿偏角分别为0028mm和0026°,明显优于固定路径测试得到的0084mm和0095°,其位置偏差标准差与位姿偏角标准差分别提升了4倍和3倍。总之,本系统在自动化检测与控制领域具有一定的应用价值。

    Abstract:

    In order to solve the assembly problem caused by the position and pose deviation of complex parts in the automated assembly process,and realize the scanning control of the robotic arm with feedback adjustment capability,a real time detection system based on laser three dimensional scanning is designed.The three dimensional surface shape data is obtained by raster scanning.Part matching is done through edge feature recognition.Finally,the goal of automatically adjusting the position and posture in the tooling environment is achieved.The experiment controls the SP165 manipulator,and takes the 6 degree of freedom parameter as the evaluation index of detection accuracy.Compare and analyze the simulation data based on the digital model of the part,the test data of the fixed scan path and the test data of the automatic adjustment scan path respectively.The results show that the maximum position deviation and maximum pose angle of automatic path adjustment using this system are 0.028mm and 0.026°,respectively.And it is significantly better than the 0.084mm and 0.095° obtained by the fixed path test.The standard deviation of the position deviation and the standard deviation of the pose angle of the system are increased by 4 times and 3 times respectively.In short,it has certain application value in the field of automatic detection and control.

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信建杰.基于特征识别的汽车复杂零件自校正检测系统[J].激光与红外,2021,51(9):1160~1164
XIN Jian-Jie. Self correcting detection system of automobile complex parts based on feature recognition[J]. LASER & INFRARED,2021,51(9):1160~1164

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  • 最后修改日期:2021-01-14
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  • 在线发布日期: 2021-10-09
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