基于智能双重响应面法的涡轮叶盘可靠性灵敏度分析

推进技术 ›› 2017, Vol. 38 ›› Issue (5): 1155-1164.

基于智能双重响应面法的涡轮叶盘可靠性灵敏度分析

张春宜¹,宋鲁凯¹,费成巍²,郝广平¹,李雪芹³

哈尔滨理工大学机械动力工程学院，黑龙江哈尔滨 150080,哈尔滨理工大学机械动力工程学院，黑龙江哈尔滨 150080,香港理工大学机械工程系，香港 999077,哈尔滨理工大学机械动力工程学院，黑龙江哈尔滨 150080,山东交通学院工程机械学院，山东济南 250000

发布日期:2021-08-15
作者简介:张春宜，男，博士，教授，研究领域为可靠性工程及优化。
基金资助:
国家自然科学基金(51275138)；黑龙江省教育厅自然科学基金项目(12531109)。

Intelligent Dual Response Surface Method for Reliability Sensitivity Analysis of Turbine Blisk

School of Mechanical and Power Engineering，Harbin University of Science and Technology，Harbin 150080，China,School of Mechanical and Power Engineering，Harbin University of Science and Technology，Harbin 150080，China,Department of Mechanical Engineering，The Hongkong Polytechnic University，Hongkong 999077，China,School of Mechanical and Power Engineering，Harbin University of Science and Technology，Harbin 150080，China and School of Construction Machinery，Shandong Jiaotong University，Jinan 250000，China

Published:2021-08-15

摘要/Abstract

摘要： 为了合理进行整体叶盘多失效模式可靠性分析和准确描述各影响参数的重要程度，将智能算法与双重响应面方法相结合提出可靠性灵敏度分析的智能双重响应面方法(Intelligent Dual Response Surface Method，IDRSM)。首先，建立IDRSM的数学模型，给出基于IDRSM的可靠性灵敏度分析的流程。然后，考虑流场和温度场作用，基于IDRSM对整体叶盘径向变形和应力两种失效模式进行可靠性分析和灵敏度分析。可靠性分析显示:当许用径向变形、许用应力的均值和标准差分别取3.8mm和76μm，690MPa和14MPa时，叶盘综合可靠度为0.9926。灵敏度分析显示:整体叶盘综合失效概率的主要影响因素为流速和转速，占叶盘总失效的92%。通过蒙特卡洛法、响应面法、极值响应面法、智能响应面法等四种方法比较显示:IDRSM能在保证计算精度的前提下提高计算效率。实例分析表明该方法在多失效模式综合可靠性灵敏度分析中的可行性和有效性，也为结构多失效模式可靠性优化开辟了有效途径。

关键词: 可靠性分析；整体叶盘；智能算法；人工神经网络；智能双重响应面法

Abstract: To reasonably implement reliability analysis and describe the significance of influencing parameters on turbine blisk with multi-failure modes，intelligent dual response surface method (IDRSM) was proposed by integrating intelligent algorithm and dual response surface method. Firstly，the mathematical model of IDRSM was established and the basic principle of multi-objective reliability sensitivity analysis with IDRSM was given. And then，based on the proposed method，the reliability analysis and sensitivity analysis of two failure modes (radial deformation and stress) were completed considering the interaction of flow field and temperature field. From the reliability analysis，the comprehensive reliability of turbine blisk is 0.9926 when the mean and standard deviation of the allowable radial deformation and the allowable stress are 3.8mm and 76μm，690MPa and 14MPa，respectively. The sensitivity analysis shows that main impact factors influencing turbine blisk failure are gas velocity and rotational speed，accounting for 92% of the total failure probability. Through the comparison of methods(Monte Carlo method，response surface method，Dual Response Surface Method and IDRSM)，it is demonstrated that the proposed IDRSM improves computational efficiency with acceptable computational accuracy. The case study shows the feasibility and effectiveness of this proposed method in multi-failure modes reliability sensitivity analysis，and offers a useful insight into the reliability optimization design of multi-failure mode structure.

Key words: Reliability analysis；Turbine blisk；Intelligent algorithm；Artificial neural network；Intelligent dual response surface method

张春宜,宋鲁凯,费成巍,郝广平,李雪芹. 基于智能双重响应面法的涡轮叶盘可靠性灵敏度分析[J]. 推进技术, 2017, 38(5): 1155-1164.

ZHANG Chun-yi¹,SONG Lu-kai¹,FEI Cheng-wei²,HAO Guang-ping¹,LI Xue-qin³. Intelligent Dual Response Surface Method for Reliability Sensitivity Analysis of Turbine Blisk[J]. Journal of Propulsion Technology, 2017, 38(5): 1155-1164.

参考文献

[1] 孙闯, 何正嘉, 张周锁, 等. 基于状态信息的航空发动机运行可靠性评估[J]. 机械工程学报, 2013, 49(6): 30-37.
[2] 徐家文, 赵建社, 朱永伟, 等. 航空发动机整体构件特种加工新技术[M]. 北京:国防工业出版社, 2011.
[3] 陈予恕, 张华彪. 航空发动机整机动力学研究与进展[J]. 航空学报, 2011, 32(8): 1371-1379.
[4] 陆山, 赵迎春, 范婕. 考虑应力松弛的涡扇发动机高压涡轮持久寿命可靠性[J]. 推进技术, 2011, 32(4): 491-496. (LU Shan, ZHAO Ying-chun , FAN Jie. Rupture Life Reliability of HP-Turbine for a Turbo-Fan Engine with the Influence of the Stress Relaxation[J]. Journal of Propulsion Technology, 2011, 32(4): 491-496.)
[5] 陆山, 高鹏. 考虑应力松弛的涡轮盘蠕变-疲劳寿命可靠性分析方法[J]. 推进技术, 2009, 30(3): 352-384. (LU Shan, GAO Peng. Reliability Analysis Method for Creep-Fatigue Life of Turbine Discs with Effect of Stress Relaxation[J]. Journal of Propulsion Technology, 2009, 30(3): 352-384.)
[6] 胡殿印, 裴月, 王荣桥, 等. 涡轮盘低循环疲劳的概率设计[J]. 推进技术, 2008, 29(4): 481-487. (HU Dian-yin, PEI Yue, WANG Rong-qiao, et al. Probabilistic Design of Low Cycle Fatigue for Turbine Disk[J]. Journal of Propulsion Technology, 2008, 29(4): 481-487.)
[7] 王大伟, 王伟, 冯振宇. 基于灰色理论的航空发动机可靠性指标评估方法[J]. 推进技术, 2014, 35(7): 874-881. (WANG Da-wei, WANG Wei, FENG Zhen-yu. Evaluation Method on Reliability Index of Aero-Engine Based on Gray Theory[J]. Journal of Propulsion Technology, 2014, 35(7): 874-881.)
[8] Lin Kevin K, Brown Eric Sheabrown, Young LaiSang. Reliability of Coupled Oscillators I: Two-Oscillator Systems[J]. Nonlinear Science, 2009, 19(1): 497-545.
[9] Dimitrov Nikolay, Hansen Peter Friis, Berggreen Christian. Reliability Analysis of a Composite Wind Turbine Blade Section Using the Model Correction Factor Method: Numerical Study and Validation[J]. Applied Composite Materials, 2013, 20(1): 17-39.
[10] Hu Zhen, Li Hai-feng, Du Xiao-qing, et al. Simulation-Based Time-Dependent Reliability Analysis for Composite Hydrokinetic Turbine Blades[J]. Structural and Multidisciplinary Optimization, 2013, 47(5): 765-781.
[11] 邓建, 李夕兵, 古德生. 结构可靠性分析的多项式数值逼近法[J]. 计算力学学报, 2002, 19(2): 212-216.
[12] Zhang Chun-yi, Bai Guang-chen. Extremum Response Surface Method of Reliability Analysis on Two-Link Flexible Robot Manipulator[J]. Journal of Central South University of Technology, 2012, 19(1): 101-107.
[13] Fei Cheng-wei, Bai Guang-chen. Distributed Collaborative Extremum Response Surface Method for Mechanical Dynamic Assembly Reliability Analysis[J]. Journal of Central South University, 2013, 20(9): 2414-2422.
[14] Xiong Fen-fen, Liu Yiu, Xiong Ying, et al. A Double Weighted Stochastic Response Surface Method for Reliability Analysis[J]. Journal of Mechanical Science and Technology, 2012, 26(8): 2573-2580.
[15] 王桂华, 费成巍, 白广忱. 基于ERSM涡轮盘径向径向变形的非线性动态可靠性灵敏度分析[J]. 推进技术, 2013, 34(4): 529-536. (Wang Gui-hua, Fei Cheng-wei, Bai Guang-chen. Nonlinear Dynamic Reliability Sensitivity Analysis of Turbine Disk Radical Deformation Based on ERSM[J]. Journal of Propulsion Technology, 2013, 34(4): 529-536.)
[16] Bai Guang-chen, Fei Cheng-wei. Distributed Collaborative Response Surface Method for Mechanical Dynamic Assembly Reliability Design[J]. Chinese Journal of Mechanical Engineering, 2013, 38(4): 1160-1168.
[17] Zhai Xue, Fei Cheng-wei, Zhai Qing-guang, et al. Reliability and Sensitivity Analyses of HPT Blade-Tip Radical Running Clearance Using Multiply Response Surface Model[J]. Journal of Central South University, 2014, 21(11): 4368-4377.
[18] 乔红威, 吕震宙, 赵新攀. 基于随机响应面法的可靠性灵敏度分析及可靠性优化设计[J]. 计算力学学报, 2010, 27(2): 207-212.
[19] Fei Cheng-wei, Bai Guang-chen. Nonlinear Dynamic Reliability Sensitivity Analysis for Turbine Casing Radical Deformation Using Extremum Response Surface Method Based on Support Vector Machine[J]. Journal of Computational and Nonlinear Dynamics, 2013, 8(1): 1-8.
[20] Fei Cheng-wei, Bai Guang-chen. Dynamic Probabilistic Design for Blade Deformation with SVM-ERSM[J]. Aircraft Engineering and Aerospace Technology, 2013, (125): 1-14.
[21] 吕震宙, 杨子政, 赵洁. 基于加权线性响应面法的神经网络可靠性分析方法[J]. 航空学报, 2006, 6(27): 1063-1067.
[22] Ren Yuan, Bai Guang-chen. Network Response Surface Methods for Reliability Analysis[J]. Chinese Journal of Aeronautics, 2011, 24(1): 25-31.
[23] Dai Feng-zhi, Kushida Naoki, Shang Li-qiang, et al. A Survey of Genetic Algorithm-Based Face Recognition[J]. Artificial Life and Robotics, 2011, 16(2): 271-274.
[24] Hua Cheng, Fang Chao. Simulation of Fluid-Solid Interaction on Water Ditching of an Airplane by ALE Method[J]. Science Direct Journal of Hydrodynamics, 2011, 23(5): 637-642.
[25] 张春宜, 路成, 费成巍, 等. 基于双重极值响应面法的叶盘联动可靠性分析[J]. 推进技术, 2016, 37(6). (ZHANG Chun-yi, LU Cheng, FEI Cheng-wei, et al. Linked Reliability Analysis of Aeroengine Blisk with Dual Extreme Response Surface Method[J]. Journal of Propulsion Technology, 2016, 37(6).)
[26] 刘大响, 曹春晓. 航空发动机设计用材料手册[M]. 北京:航空工业出版社, 2010.
[27] 于慧臣, 吴学仁. 航空发动机设计用材料数据手册(第四册)[M]. 北京:航空工业出版社, 2010.　　　　　　　　　　　　　*　收稿日期:2016-03-01；修订日期:2016-03-18。基金项目:国家自然科学基金(51275138)；黑龙江省教育厅自然科学基金项目(12531109)。作者简介:张春宜,男,博士,教授,研究领域为可靠性工程及优化。E-mail: zhangchunyi@hrbust.edu.cn(编辑:史亚红)