基于粒子群优化的硅橡胶拉伸性能检测方法研究

Silicone Rubber Tensile Performance Test Methods Based on Particle Swarm Optimization

硅橡胶拉伸性能检测一直是化工学领域研究的热点问题之一。传统的硅胶伸缩检测方法都是计算较大的拉伸脆弱面积,很难精确到点,主要是因为硅胶面具不规范,承拉能力分布范围较大,弱化了拉伸性能的关联性。为了解决这一问题,提出一种基于粒子群优化的硅橡胶拉伸性能检测方法,通过对硅胶区域进行拉伸信息的计算,代入神经网络,利用神经网络对小区域搜索的能力,对粒子群进行优化,增强对小区域计算的寻优能力,保证硅胶拉伸支撑区域进一步缩小,缩小定位范围。仿真结果表明:该方法对硅橡胶拉伸性能计算的定位效果较好,精度较高。

Silicone rubber tensile performance detection has been the hotspot in research of chemical learning one problem.The traditional silica gel expansion detection method is calculation large tensile fragile area,it is difficult to accurately to point,mainly because silica gel mask is not standard,bearing pull ability distribution range is larger,weakening the tensile properties of relevance.In order to solve this problem,the paper proposes a kind of particle swarm optimization based on the silicone rubber tensile performance test method,through to the silica gel area of tensile information calculation,substituting neural network,using the neural network to small area search ability,to the particle swarm optimization,to increase the calculation of small area optimization ability,assurance silica gel tensile support area further narrowing and narrow scope of positioning.The simulation results show that the method of silicone rubber tensile performance calculation orientation effect is good,the accuracy is higher.