摘要
为提高某重型柴油机气缸垫的可靠性和疲劳寿命,基于其温度场、热机耦合应力场和变形情况等状态参数利用相关方法对气缸垫的工作参数进行了优化研究。利用正交实验方法分析了缸垫的气缸圆直径、上水孔圆直径、隔热带长度、缸垫厚度和螺栓预紧力等5个工作参数对上述3个状态参数的影响规律,并确定了影响最为显著的4个工作参数。利用所提出的混合神经网络模型建立了工作参数与状态参数的对应关系模型,结合所提出的改进灰狼算法计算确定了气缸垫的最优工作参数值。分析结果表明改进后气缸垫的温度应力和变形情况得到显著改善,证明了改进的有效性和算法的准确性。
In order to improve the reliability and fatigue life of a heavy⁃duty diesel engine cylinder head gasket,based on its state parameters such as temperature field,thermal⁃mechanical coupling stress field and defor⁃mation,the working parameters of the cylinder head gasket are optimized using related methods.The orthogonal ex⁃periment method is used to analyze the influence of the five working parameters of cylinder circle diameter,water hole circle diameter,heat insulation strip length,cylinder gasket thickness and bolt pre⁃tightening force on the above three state parameters,with the four most significant working parameters defined.Using the proposed hybrid neural network model,the corresponding relationship model between the working parameters and the state parame⁃ters is established,and the optimal working parameter value of the cylinder head gasket is calculated and deter⁃mined in combination with the proposed improved gray wolf algorithm.The finite element analysis results show that the temperature stress and deformation of the cylinder head gasket after the improvement have been significantly im⁃proved,which proves the effectiveness of the improvement and the accuracy of the algorithm.
作者
董意
刘建敏
李普
刘艳斌
乔新勇
Dong Yi;Liu Jianmin;Li Pu;Liu Yanbin;Qiao Xinyong(Vehicle Engineering Department,Army Academy of Armored Forces,Beijing 100072;Chinese People’s Liberation Army No.6456 Factory,Nanyang 473000)
出处
《汽车工程》
EI
CSCD
北大核心
2021年第2期232-240,共9页
Automotive Engineering
基金
军内科研项目“数字孪生技术驱动的装备动力系统健康管理研究”(2019ZB124)资助。
关键词
柴油机
气缸垫
优化
混合神经网络
改进灰狼算法
diesel engine
cylinder head gasket
optimization
hybrid neural network
improved grey wolf algorithm
