Please use this identifier to cite or link to this item: `http://hdl.handle.net/10397/73962`
 Title: Advanced extremum response surface method for dynamic reliability analysis on flexible mechanism Other Title: 柔性机构动态可靠性分析的先进极值响应面方法 Authors: Zhang, CSong, LFei, C Hao, GLu, C Issue Date: 2017 Source: 機械工程學報 (Chinese journal of mechanical engineering), Apr. 2017, v. 53, no. 7, p. 47-54 Abstract: 为了提高柔性机构可靠性分析的精度和效率,提出动态可靠性分析的先进极值响应面法。该方法将智能算法与可靠性分析的极值响应面法相结合,利用蒙特卡洛法抽取样本,经过网络训练建立先进极值响应面法的数学模型。以柔性机械臂为例,以柔性机械臂材料密度、弹性模量、构件截面尺寸为输入随机变量,构件变形为输出响应;利用蒙特卡罗法、极值响应面法和先进极值响应面法分别进行动态可靠性仿真计算,得出了各自输出响应量的分布特征及可靠度。通过方法比较表明:先进极值响应面法在保证计算精度的前提下,大大提高了计算速度,验证了先进极值响应面法在柔性机构动态可靠性分析中的可行性和适用性;也为柔性机构可靠性优化开辟了有效途径。To improve the precision and efficiency of reliability analysis of flexible mechanism, advanced extremum response surface method of reliability analysis is proposed. Based on the intelligent algorithm and extremum response surface method, the mathematical model of the proposed method is established through the generation of samples by Monte Carlo method and the network training. A flexible robot manipulator is chosen as the target of study in the reliability simulation where its material density, elastic modulus, section size of components are taken as input random variables and deformation of components is taken as output response. Distribution characteristics of output response and reliability are assessed by Monte Carlo method, extremum surface method and advanced extremum surface method respectively. The comparison with various other methods shows that this advanced extremum response surface method has greatly improved the computational speed while keeping acceptable computational accuracy, advanced extremum response surface method is proved to be a high precision and high efficiency in dynamic reliability analysis of flexible mechanism, and this method has opened up an effective way for reliability optimization of flexible mechanism. Keywords: Advanced extremum response surface methodArtificial neural networkFlexible robot manipulatorIntelligent algorithmReliability analysis Publisher: 機械工業出版社 Journal: 機械工程學報 (Chinese journal of mechanical engineering) ISSN: 0577-6686 DOI: 10.3901/JME.2017.07.047 Rights: © 2017 China Academic Journal Electronic Publishing House. It is to be used strictly for educational and research use.© 2017 中国学术期刊电子杂志出版社。本内容的使用仅限于教育、科研之目的。 Appears in Collections: Journal/Magazine Article

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