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1.潍柴动力股份有限公司,潍坊 261061
2.内燃机可靠性国家重点实验室,潍坊 261061
3.天津大学 建筑工程学院,天津 300354
李卫,男,1987年生,山东潍坊人,高级工程师;主要研究方向为机械结构疲劳寿命预测分析;E-mail:15929952680@163.com。
杜尊峰,男,1984年生,山东泰安人,教授;主要研究方向为机械结构设计及可靠性分析;E-mail:dzf@tju.edu.cn。
收稿日期:2023-09-22,
修回日期:2023-11-17,
纸质出版日期:2025-05-15
移动端阅览
李卫,李连升,杜尊峰,等. 基于PC-Kriging模型的发动机活塞低周疲劳可靠性分析[J]. 机械强度,2025,47(5):131-139.
LI Wei,LI Liansheng,DU Zunfeng,et al. Low-cycle fatigue reliability analysis of engine pistons based on PC-Kriging model[J]. Journal of Mechanical Strength,2025,47(5):131-139.
李卫,李连升,杜尊峰,等. 基于PC-Kriging模型的发动机活塞低周疲劳可靠性分析[J]. 机械强度,2025,47(5):131-139. DOI: 10.16579/j.issn.1001.9669.2025.05.015.
LI Wei,LI Liansheng,DU Zunfeng,et al. Low-cycle fatigue reliability analysis of engine pistons based on PC-Kriging model[J]. Journal of Mechanical Strength,2025,47(5):131-139. DOI: 10.16579/j.issn.1001.9669.2025.05.015.
低周疲劳是发动机活塞的典型失效模式,为研究多源不确定性因素对活塞低周疲劳可靠性的影响,提高可靠性分析效率,基于Polynomial-Chaos-based Kriging(PC-Kriging)模型和蒙特卡洛模拟(Monte Carlo Simulation
MCS),构建了一种新的可靠性计算方法,并通过数值算例证明了该方法的准确性和高效性。以某型柴油发动机活塞组结构为研究对象,基于热-机耦合分析建立活塞有限元模型,综合考虑关键尺寸、材料属性及载荷的不确定性,运用该方法对活塞进行了低周疲劳可靠性分析。可靠性分析结果表明,与同类型方法相比,该方法计算效率更高,仅需要有限元计算20+93次,当活塞的期望设计寿命为1.4×10
4
时,其疲劳失效概率为1.053%;灵敏度
分析结果表明,活塞高度、活塞直径、材料弹性模量和疲劳计算模型参数对可靠性的影响较大,分析结果可为活塞的可靠性设计提供指导。
Low-cycle fatigue is a typical failure mode of engine pistons. In order to study the influence of multi-source uncertainty factors on the reliability of low-circumference fatigue of pistons and improve the efficiency of the reliability analysis
a new reliability calculation method is constructed based on the polynomial-chaos-based Kriging (PC-Kriging) model and the Monte Carlo simulation (MCS)
and the accuracy and efficiency of this method are proved by numerical examples. Taking the piston group structure of a certain diesel engine as the research object
a finite element model of the piston is established based on the thermal-mechanical coupling analysis
and the reliability analysis of the piston for low-cycle fatigue is carried out by using this method
taking into account the critical dimensions
the material properties
and the uncertainty of the load. The results of the reliability analysis show that
compared with the same type of method
this method is more efficient in calculation
requiring only 20+93 finite element calculations
and the probability of fatigue failure is 1.053% when the expected design life of the piston is 1.4×10
4
. The sensitivity analysis shows that, the height of the piston
the piston diameter
the elasticity modulus of the material
and the parameters of the fatigue calculation model have a greater influence on the reliability. The analysis results can provide a guidance for the reliability design of the piston.
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