【作者】 于霖冲； 白广忱；

【Author】 Yu Linchong~(1,2) Bai Guangchen~1(1.School of Energy and Power Engineering,Beijing University of Aeronautics & Astronautics,Beijing 100083,China;2.Department of Computer Science & Technology,Jiaying University,Meizhou Guangdong 514015,China)

【机构】 北京航空航天大学能源与动力工程学院；

【摘要】 提出了摩擦和柔性影响下的机构动态可靠性分析的理论和方法,给出了柔性机构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。通过空间站柔性展开机构实例计算,求出了动态可靠度,减少了计算时间。更多还原

【Abstract】 Theory and methodology of mechanism dynamical reliability analysis considered the influence of friction and flexibleness were presented.A general model of 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 dynamical parameters was yielded from the outputs of ANN.As an example,one expand mechanism model of space station was employed to test this method.The results proved that this method can be used to account for the complicated dynamical reliability analysis at a reasonable computational cost.更多还原