The Non-probabilistic Reliability Optimization of the Car Frame Based on IRSM and IP-GA
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摘要: 以某牵引车车架为研究对象,对车架进行有限元分析,求车架结构的强度值。制造车架材料的密度和弹性模量存在不确定性,在求解可靠度时,要考虑这些参数的不确定性。运用改进响应面法(IRSM)构建不确定变量、设计变量与强度值之间的近似模型,求得车架原厚度的非概率可靠度指标。以设计变量相关车架部件的质量最轻为目标函数,车架原厚度可靠度指标为约束构建非概率可靠度优化模型。运用隔代遗传算法求解不确定性优化,并与确定性优化相比较。计算结果表明:在不降低车架原厚度可靠度指标的基础上,确定性优化和不确定性优化都能够做到轻量化,且不确定优化比确定性优化多减轻20 kg质量,有重要的优化设计价值。Abstract: This paper took a tractor frame as the research object,analyzed the frame with finite element method,and got the strength of the frame structure value. Because frame materials elasticity and density is uncertain. It is needed to consider these uncertainties to get the reliability. This paper used IRSM to construct the approximation model,then got the reliability. The objective function is the lightest quality which associated with variable frame components and the original thickness of reliability indexes as constraint. Using the IP-GA to solve this uncertain optimization model. Then compared with the probabilistic reliability optimization. The results show that the certainty and uncertainty optimization can be lightweight without reducing the original thickness of the reliability index; uncertain optimization is more than the deterministic optimization to reduce quality of 20 kg,so it has more advantages.
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