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基于改进曲率模态的叶盘结构损伤识别研究 被引量:1

Research on damage recognition of blade-disc structure based on improved curvature modal
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摘要 针对曲率模态不能识别结构端部单元损伤的问题,提出了改进的曲率模态识别模型。叶盘是航空发动机结构非常重要的部件之一,若其发生故障将对发动机安全运转造成严重的威胁。而曲率模态对结构故障具有很强的敏感性,运用曲率模态方法,从不同的损伤位置以及不同的损伤程度这两方面比较了叶盘模态振型变化情况,并且用改进的曲率模态方法对结构端部进行计算。数值计算结果表明:当发动机叶盘受到损伤,位移模态和结构频率难以有效反映出结构的损伤位置,各阶固有频率会下降;曲率模态方法能有效反映出结构损伤状况,曲率在损伤处发生突变现象,并能对损伤程度给出定性的描述;而改进的曲率模态识别模型能够识别出结构端部的损伤故障。这为航空发动机叶盘结构的损伤检测提供了理论依据。 An improved model of curvature modal recognition is proposed to solve the problem that the curvature modal cannot recognize the damage of the tip and root of the structures.Blade-disc is one of the most important components of the aero-engine structure,and if it fails,it will cause a serious threat to the safe operation of the engine.The curvature modal method which is strongly sensitive to the structural faults is used to compare the changes of the blade-disc modal from different damage locations and different damage degrees,and the structure end is calculated by using the improved curvature modal method.The numerical results show that when the bladedisc is damaged,the displacement mode and structure frequency are difficult to reflect the damage position of the structure effectively,and the natural frequencies of each order mode will get decreased;the curvature modal method which can reflect the damage condition of the structure effectively gives a qualitative description of the damage degree,and the curvature changes abruptly at the damage place;the improved curvature modal recognition model can identify the damage fault at the end of the structure,which provides a theoretical basis for damage detection of aero-engine blade-disc structures.
作者 彭鸿博 张奇奇 但敏 Hong-bo PENG;Qi-qi ZHANG;Min DAN(Aeronautical Engineering Institute,Civil Aviation University of China,Tianjin 300300,China)
出处 《机床与液压》 北大核心 2020年第6期99-106,共8页 Machine Tool & Hydraulics
基金 中央高校基本科研业务费专项资金(3122014D014,2018CXJJ19)。
关键词 曲率模态 频率 叶盘结构 改进的曲率模态 损伤检测 Curvature modal Frequency Blade-disc structures Improved curvature modal Damage detection
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