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SMT Automatic Optical Inspection Path Planning Based on MDSPSO Algorithm

机译:基于MDSPSO算法的SMT自动光学检测路径规划

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When carrying out the automatic optical inspection (AOI) on the printing circuit board (PCB) adopted surface mounted technology (SMT) , inspecting path planning is a question of combinatorial optimization, every inspecting window exists certain move range. In view of all above problems, this paper studied the standard particle swarm optimization (PSO) algorithm, and based on that, it suggested another algorithm-multi-directional search PSO (MDSPSO) algorithm. The renew of the speed and location of every particle in MDSPSO algorithm, not only considered self individual extremal and overall situation extremal information, but also the information that other particles contained, which changed the unidirectional search in PSO algorithm into multi-directional search, even improved the search accuracy. According to the convergence analysis, reaching the condition of ensuring the overall situation converges. Therefore the MDSPSO algorithm can converge fairly up to optimum result under the control of parameter in appropriate optional algorithm. By using the MDSPSO algorithm in SMT automatic optical inspection path planning, simulate result shows that, not only MDSPSO algorithm has merits of height accuracy and quick convergence speed, but also the quantity of inspecting windows of the path planning is the fewest in this algorithm and the inspecting route is the shortest.
机译:当在印刷电路板(PCB)上进行的自动光学检测(AOI)采用表面安装技术(SMT)时,检测路径规划是组合优化的问题,每个检查窗口都存在某些移动范围。鉴于上述所有问题,本文研究了标准粒子群优化(PSO)算法,并基于此,提出了另一种算法 - 多向搜索PSO(MDSPSO)算法。续订MDSPSO算法中每种粒子的速度和位置,不仅考虑了自我个体极值和整体情况极值信息,而且还有其他粒子的信息,这将PSO算法中的单向搜索变为多向搜索,甚至提高了搜索准确性。根据收敛分析,达到确保整体情况会聚的条件。因此,MDSPSO算法可以在适当的可选算法的参数控制下相当达到最佳结果。通过在SMT自动光学检查路径规划中使用MDSPSO算法,模拟结果表明,不仅MDSPSO算法具有高度精度和快速收敛速度的优点,而且路径规划的检查窗口的数量是本算法中最少的窗口检查路线是最短的。

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