基于影响系数法的薄板电阻点焊定位点优化

定位点的布置会在很大程度上影响薄板焊接装配在法向的变形。针对传统定位点布置优化仅仅研究薄板在外力作用下的变形,利用有限元分析理论,构建了考虑薄板在外力作用的变形和定位点位置两方面影响的薄板装配模型。采用影响系数法构建了偏差源对装配误差的影响系数矩阵,并创建以影响系数的绝对值最小为目标函数的数学优化模型。利用遗传算法求解模型最优解,提出了考虑边界与夹紧点的新型抽样方法来提高该算法初始点的均布性,计算结果表明偏差源对装配误差的影响系数与优化前相比减小了90%。

基于序列Kriging-GA的薄板件定位点优化方法

为降低车身薄板焊接装夹时的重力以及夹具定位点偏差对柔性薄板件定位精度的影响,提高薄板定位方案的稳健性,基于有限元分析方法对薄板件第一基准面的定位点布置进行了优化。为了建立能反映薄板定位精度对定位点偏差敏感度的定位方案评价指标,引入影响系数法,建立了定位点偏差对薄板件定位精度的影响系数矩阵。基于影响系数平方矩阵的迹,并考虑重力对薄板定位精度的影响建立了多目标优化模型。采用Kriging代理模型构造出优化模型的目标函数,为了解决代理模型预测精度较差的问题,提出了基于序列Kriging-GA的薄板件定位点优化方法,将最优点选点准则和期望改善准则融合使用,反复在兴趣域增加样本点,更新代理模型,提高了代理模型的预测精度并保证了算法的全局搜索能力。结果表明:序列Kriging模型在兴趣域的预测误差可低至1%,具有很高的预测精度;与采用遗传算法相比,所提出的方法能减少75%仿真次数,显著提高设计效率;在不同定位点偏差组合下,零件各关键点位移量的均值与方差都显著减小,定位精度对定位点偏差的敏感度降低,优化后的定位方案具有较高的稳健性。

Improved Algorithm for Distributed Localization in Wireless Sensor Networks

Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.