Distributed Collaborative Response Surface Method for Mechanical Dynamic Assembly Reliability Design

被引:49
作者
Bai Guangchen [1 ]
Fei Chengwei [1 ]
机构
[1] Beihang Univ, Sch Energy & Power Engn, Beijing 100191, Peoples R China
基金
中国国家自然科学基金; 高等学校博士学科点专项科研基金;
关键词
machinery dynamic assembly; reliability analysis; distributed collaborative response surface method; blade-tip radial running clearance; TOPOLOGY OPTIMIZATION; TIP CLEARANCE; VIBRATION;
D O I
10.3901/CJME.2013.06.1160
中图分类号
TH [机械、仪表工业];
学科分类号
120111 [工业工程];
摘要
Because of the randomness of many impact factors influencing the dynamic assembly relationship of complex machinery, the reliability analysis of dynamic assembly relationship needs to be accomplished considering the randomness from a probabilistic perspective. To improve the accuracy and efficiency of dynamic assembly relationship reliability analysis, the mechanical dynamic assembly reliability(MDAR) theory and a distributed collaborative response surface method(DCRSM) are proposed. The mathematic model of DCRSM is established based on the quadratic response surface function, and verified by the assembly relationship reliability analysis of aeroengine high pressure turbine(HPT) blade-tip radial running clearance(BTRRC). Through the comparison of the DCRSM, traditional response surface method(RSM) and Monte Carlo Method(MCM), the results show that the DCRSM is not able to accomplish the computational task which is impossible for the other methods when the number of simulation is more than 100 000 times, but also the computational precision for the DCRSM is basically consistent with the MCM and improved by 0.40 similar to 4.63% to the RSM, furthermore, the computational efficiency of DCRSM is up to about 188 times of the MCM and 55 times of the RSM under 10000 times simulations. The DCRSM is demonstrated to be a feasible and effective approach for markedly improving the computational efficiency and accuracy of MDAR analysis. Thus, the proposed research provides the promising theory and method for the MDAR design and optimization, and opens a novel research direction of probabilistic analysis for developing the high-performance and high-reliability of aeroengine.
引用
收藏
页码:1160 / 1168
页数:9
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