增压器涡轮叶片疲劳蠕变寿命预测方法

摘要/Abstract

摘要： 根据径流式增压器涡轮的结构与工作特点，分析了涡轮叶片的载荷与应力空间分布特征；针对增压器涡轮由疲劳与蠕变交互作用引起的叶根断裂失效模式，研究了增压器涡轮叶片叶根的载荷与应力变化历程，建立了涡轮叶片叶根的载荷与应力描述方法；然后建立了增压器涡轮叶片叶根疲劳蠕变寿命预测方法及模型，并运用建立的模型对增压器涡轮叶片叶根进行了寿命评估。

关键词: 涡轮增压器, 涡轮叶片, 疲劳, 蠕变, 寿命预测

Abstract: According to the structural characteristics and operation profiles of radial turbines, the spatial distribution characteristics of load and stress of turbine blades were analyzed. For the failure mode of blade root fracture caused by fatigue and creep, the loadings and stress processes of blade roots of turbines were studied, and the methods for describing the load and stress of turbine blade roots were developed. Then, the life prediction methods of turbine blade root of turbochargers were studied and the life prediction model of turbine blade roots with the failure mode of fatigue and creep was derived. Finally, taking the turbine of turbocharger for automobile diesel engine, the model built was applied to analyze the life of turbine blade roots of turbocharger for vehicle applications.

Key words: turbocharger, turbine blade, fatigue, creep, life prediction

中图分类号:

王正;马同玲. 增压器涡轮叶片疲劳蠕变寿命预测方法[J]. 中国机械工程.

WANG Zheng;MA Tongling. Fatigue and Creep Life Prediction Method of Turbine Blades for Turbocharger[J]. China Mechanical Engineering.

参考文献

[1]王增全, 王正. 车用涡轮增压器结构可靠性[M]. 北京：科学出版社, 2013.
WANG Zengquan, WANG Zheng. Structural Reliability of Turbocharger for Vehicle Application [M]. Beijing：Science Press, 2013.
[2]刘瑞林. 柴油机高原环境适应性研究[M]. 北京：北京理工大学出版社，2013.
LIU Ruilin. Research on Plateau Environmental Adaptability of Diesel Engines [M]. Beijing：Beijing Institute of Technology Press, 2013.
[3]BOOYSEN C, HEYNS P S, HINDLEY M P, et al. Fatigue Life Assessment of a Low Pressure Steam Turbine Blade during Transient Resonant Conditions Using a Probabilistic Approach [J]. International Journal of Fatigue, 2015, 73: 17-26.
[4]SENN S M, SEILER M， SCHAEFER O. Blade Excitation in Pulse-charged Mixed-flow Turbocharger Turbines [J]. Journal of Turbomachinery, 2011, 133, 0210121- 0210126.
[5]MAKTOUF W, AMMAR K, NACEUR I B, et al. Multiaxial High-cycle Fatigue Criteria and Life Prediction: Application to Gas Turbine Blade [J]. International Journal of Fatigue, 2016, 92: 25-35.
[6]林海英，陈萌. 小型航空涡轮增压器叶片强度振动研究[J]. 噪声与振动控制, 2009(6): 44-49.
LIN Haiying, CHEN Meng. Analysis of Stress and Vibration of Blade for Aero Turbocharger [J]. Noise and Vibration Control, 2009(6): 44-49.
[7]李磊, 敖良波, 李元生, 等. 船用高压比大流量增压器涡轮多学科设计优化[J]. 兵工学报, 2010, 31(5): 574-579.
LI Lei, AO Liangbo, LI Yuansheng, et al. Multidisciplinary Design Optimization for Marine Supercharger Turbo [J]. Acta Armamentarii, 2010, 31(5): 574-579.
[8]王正, 王增全, 郭凯, 等. 增压器涡轮叶片振动分析及其可靠性评价方法研究[J]. 车用发动机, 2012(4): 63-67.
WANG Zheng, WANG Zengquan, GUO Kai, et al. Study on Vibration Analysis and Reliability Evaluation Method of Turbocharger Turbine Blade [J]. Vehicle Engine, 2012(4): 63-67.
[9]王延荣, 宋兆泓, 候贵仓. 涡轮叶片高温第循环疲劳/蠕变寿命试验评定[J]. 航空动力学报, 2002, 17(4): 407-411.
WANG Yanrong, SONG Zhaohong, HOU Guicang.Experimental Evaluation of High Temperature Low Cycle Fatigue/Creep Life of Turbine Blade [J]. Journal of Aerospace Power, 2012, 17(4): 63-67.
[10]王正，谢里阳.机械时变可靠性理论与方法[M].北京：科学出版社，2012.
WANG Zheng，XIE Liyang.Time-dependent Reliability Theory and Method for Mechanical Products [M]. Beijing：Science Press, 2012.
[11]中国金属学会高温材料分会. 中国高温合金手册[M]. 北京：中国质检出版社，2012.
Academic Committee of the Super Alloys, CSM. China Super Alloys Handbook [M]. Beijing：China Zhijian Publishing House，2012.

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