大型结构件应力分布特征及其影响力知识的自动获取
|
摘要
为探究大型结构件应力分布影响因素的影响力差异,建立了应力分布特征及其影响力知识自动获取机制。针对截面尺寸连续变化的大型结构件,提出应力普查法进行结构件区域分割与最大应力提取,通过区域危险评估确定特征区域,获得应力分布特征集;分析结构参数对特征应力与轻量化指标的影响力,建立基于多状态调整策略的知识推理模型,获取各特征应力在不同调整期望的主影响因素及其影响显著度,以此反映满足对应期望应优先调整的结构参数与优先顺序。最后,以鹅颈式动臂为例进行验证,结果表明所提方法可实现大型结构件建模、分析、应力特征提取和影响力知识获取的自动化,能高效、柔性地为大型结构件智能优化提供有价值的知识。
To explore the difference of the factors influencing stress distribution for large-scale component,an automatic mechanism of acquiring stress distribution characteristics and influence knowledge was established. For the large-scale component with continuous changing geometry,a stress survey method was proposed to extract maximum stress of each sub-region for every sample. After evaluating the danger situation,some characteristic regions were determined and the characteristic stress sets were acquired. Furthermore,the influences of structural parameters for characteristic stresses and lightweight index were analyzed. By constructing knowledge reasoning model based on multi-states adjusting strategy,the main influence factors as well as their saliency under different expectations were acquired to reflect the priority of structural parameters for adjusting. Finally,the gooseneck-type boom was taken as an example,which demonstrates that the process of modeling,analysis,feature extraction and knowledge acquisition can be realized automatically and the useful knowledge can be acquired efficiently and flexibly for the intelligent optimization of large-scale component.
To explore the difference of the factors influencing stress distribution for large-scale component,an automatic mechanism of acquiring stress distribution characteristics and influence knowledge was established. For the large-scale component with continuous changing geometry,a stress survey method was proposed to extract maximum stress of each sub-region for every sample. After evaluating the danger situation,some characteristic regions were determined and the characteristic stress sets were acquired. Furthermore,the influences of structural parameters for characteristic stresses and lightweight index were analyzed. By constructing knowledge reasoning model based on multi-states adjusting strategy,the main influence factors as well as their saliency under different expectations were acquired to reflect the priority of structural parameters for adjusting. Finally,the gooseneck-type boom was taken as an example,which demonstrates that the process of modeling,analysis,feature extraction and knowledge acquisition can be realized automatically and the useful knowledge can be acquired efficiently and flexibly for the intelligent optimization of large-scale component.
引文
[1]Mehmet Yener.Design of a Computer Interface for Automatic Finite Element Analysis of an Excavator Boom[D].Turkey:Middle East Technical University,2005:21-29.
[2]郑松林,王彦生,卢曦,等.基于强度变化特征的汽车结构件轻量化设计方法[J].机械工程学报.2008,44(2):129-133.ZHENG SongLin,WANG YanSheng,LU Xi,et al.Weightreduction Design of Auto Structures Based on Strength Features[J].Chinese Journal of Mechanical Engineering.2008,44(2):129-133.
[3]Cevdet Can Uzer.Shape Optimization of an Excavator Boom by Using Genetic Algorithm[D].Turkey:Middle East Technical University,2008:35-73.
[4]张大千,张天侠,张国胜,等.基于灵敏度分析的客车车身骨架轻量化设计[J].机械强度,2011,33(6):913-920.ZHANGDa Qian,ZHANG Tian Xia,ZHANG GuoSheng,et al.Lightweight Design for Bus Body Frame Based on Sensitivity Analysis.[J].Journal of Mechanical Strength,2011,33(6):913-920(In Chinese).
[5]左文杰,陈继顺,李亦文,等.刚度、强度与频率约束下的白车身板厚尺寸优化[J].汽车工程,2017,39(2):145-149.Zuo Wen Jie,Chen Ji Shun,Li Yi Wen,et al.Size Optimization on Plate Thickness of BIW with Constraints of Stiffness,Strength and Frequency[J].Automotive Engineering,2017,39(2):145-149(In Chinese).
[6]那景新,何洪军,闫亚坤,等.基于构件内力优化的车身结构轻量化设计[J].吉林大学学报(工学版).2010,40(6):1492-1496.NA JingXin,HE HongJun,YAN Ya Kun,et al.Lightweight design of vehicle body structure based on internal force optimization[J].Journal of Jilin University(Engineering and Technology Edition)2010,40(6):1492-1496(In Chinese).
[7]谢文华.Spearman相关系数的变量筛选方法[D].北京:北京工业大学.2015:13-29.XIE WenHua.Variable Screening Based on Spearman Correlation[D].Beijing:Beijing University of technology,2015:13-29(In Chinese).
[8]屈志坚,刘明光,刘靖,等.铁道供电系统信息流延时的拉丁超立方抽样蒙特卡洛模拟[J].中国铁道科学.2012,33(5):82-90.QU Zhi Jian,LIU MingGuang,LIUjing,et al.Latin Hypercube Sampling Monte Carlo Simulation for the Information Flow TimeDelay of Railway Power Supply System[J].China Railway Science.2012,33(5):82-90(In Chinese).
[9]花海燕,林述温.可配置的复杂构件结构性能特征知识模型[J].计算机集成制造系统.2014,20(5):1003-1012.HUA Hai Yan,LIN ShuWen.Configurable Knowledge Model of Structural Performance Characteristics for Complex Component[J].Computer Integrated Manufacturing Systems.2014,20(5):1003-1012(In Chinese).
[10]HUA Hai Yan,LIN ShuWen.New Knowledge-based Genetic Algorithm for Excavator Boom Structural Optimization[J].Chinese Journal of Mechanical Engineering.2014,27(2):392-401.
[11]天津工程机械研究所.GB9141-88.液压挖掘机结构强度试验方法[S].北京:国家标准局.1988:7.Tianjin Mechanical Engineering Research Institute.GB9141-88Hydraulic excavators-testing method of structure strength[S].Beijing:Standardization Administration of the People’s Republic of China,1988:7(In Chinese).
[2]郑松林,王彦生,卢曦,等.基于强度变化特征的汽车结构件轻量化设计方法[J].机械工程学报.2008,44(2):129-133.ZHENG SongLin,WANG YanSheng,LU Xi,et al.Weightreduction Design of Auto Structures Based on Strength Features[J].Chinese Journal of Mechanical Engineering.2008,44(2):129-133.
[3]Cevdet Can Uzer.Shape Optimization of an Excavator Boom by Using Genetic Algorithm[D].Turkey:Middle East Technical University,2008:35-73.
[4]张大千,张天侠,张国胜,等.基于灵敏度分析的客车车身骨架轻量化设计[J].机械强度,2011,33(6):913-920.ZHANGDa Qian,ZHANG Tian Xia,ZHANG GuoSheng,et al.Lightweight Design for Bus Body Frame Based on Sensitivity Analysis.[J].Journal of Mechanical Strength,2011,33(6):913-920(In Chinese).
[5]左文杰,陈继顺,李亦文,等.刚度、强度与频率约束下的白车身板厚尺寸优化[J].汽车工程,2017,39(2):145-149.Zuo Wen Jie,Chen Ji Shun,Li Yi Wen,et al.Size Optimization on Plate Thickness of BIW with Constraints of Stiffness,Strength and Frequency[J].Automotive Engineering,2017,39(2):145-149(In Chinese).
[6]那景新,何洪军,闫亚坤,等.基于构件内力优化的车身结构轻量化设计[J].吉林大学学报(工学版).2010,40(6):1492-1496.NA JingXin,HE HongJun,YAN Ya Kun,et al.Lightweight design of vehicle body structure based on internal force optimization[J].Journal of Jilin University(Engineering and Technology Edition)2010,40(6):1492-1496(In Chinese).
[7]谢文华.Spearman相关系数的变量筛选方法[D].北京:北京工业大学.2015:13-29.XIE WenHua.Variable Screening Based on Spearman Correlation[D].Beijing:Beijing University of technology,2015:13-29(In Chinese).
[8]屈志坚,刘明光,刘靖,等.铁道供电系统信息流延时的拉丁超立方抽样蒙特卡洛模拟[J].中国铁道科学.2012,33(5):82-90.QU Zhi Jian,LIU MingGuang,LIUjing,et al.Latin Hypercube Sampling Monte Carlo Simulation for the Information Flow TimeDelay of Railway Power Supply System[J].China Railway Science.2012,33(5):82-90(In Chinese).
[9]花海燕,林述温.可配置的复杂构件结构性能特征知识模型[J].计算机集成制造系统.2014,20(5):1003-1012.HUA Hai Yan,LIN ShuWen.Configurable Knowledge Model of Structural Performance Characteristics for Complex Component[J].Computer Integrated Manufacturing Systems.2014,20(5):1003-1012(In Chinese).
[10]HUA Hai Yan,LIN ShuWen.New Knowledge-based Genetic Algorithm for Excavator Boom Structural Optimization[J].Chinese Journal of Mechanical Engineering.2014,27(2):392-401.
[11]天津工程机械研究所.GB9141-88.液压挖掘机结构强度试验方法[S].北京:国家标准局.1988:7.Tianjin Mechanical Engineering Research Institute.GB9141-88Hydraulic excavators-testing method of structure strength[S].Beijing:Standardization Administration of the People’s Republic of China,1988:7(In Chinese).