柔性机构运动参数动态可靠性分析方法研究

Research on Dynamical Reliability Analysis of Flexible MechanismKinematical Parameters

研究目的是提出柔性机构运动参数动态可靠性分析方法,给出了柔性机构运动参数动态可靠性分析的广义模型。将驱动力(矩)、摩擦和阻尼力(矩)等作为随机变量,应用蒙特卡罗方法,取得动态参数样本,再利用人工神经网络方法,根据抽取的样本对网络进行训练,统计网络输出的动态参数分布,得到机构动态可靠度。空间站柔性展开机构动态可靠度计算实例表明该方法减少了计算时间。

The aim of the research is to present methodology of dynamical reliability analysis of flexible mechanism kinematical parameters. A general model of kinematical parameters dynamical reliability was introduced for flexible mechanism analysis. Stochastic variables included driven forces, torques, frictions and damps were considered basically. In the first, Monte Carlo (MC) method was applied to generate stochastic variables and dynamical responds of mechanism. Secondly, the application of Artificial Neural Network (ANN) was motivated by the approximate concepts inherent in reliability analysis and time consuming repeated analyses required for MC. Finally, statistical distribution of kinematical parameters was yielded from the outputs of ANN. As an example, one flexible space station expand mechanism model was employed to test this method. The results proved that this method could be used to account for the complicated dynamical reliability analysis at a reasonable computational cost.