基于改进经验模态分解的裂纹Jeffcott转子垂向瞬态响应分析

IF 1.9 Q3 ENGINEERING, MECHANICAL
Vibration Pub Date : 2022-07-02 DOI:10.3390/vibration5030023
H. Khorrami, R. Sedaghati, S. Rakheja
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引用次数: 0

摘要

研究了Jeffcott转子旋转轴盘系统的垂直瞬态响应变化,用于横向裂纹检测。这种裂缝被认为是呼吸裂缝。提出了一种新的呼吸函数,将部分开闭裂纹的呼吸行为插入到完全开闭裂纹的呼吸行为之间。呼吸裂纹激发了瞬态超谐波响应分量和次谐波分量。基于改进的经验模态分解算法,建立了Hilbert-Huang变换,以评估转子垂直瞬态响应的时频表示,从而检测裂纹。结果表明,所提出的呼吸函数可以有效地减少计算量,而不会牺牲小裂纹存在时裂纹呼吸行为的准确性。结果表明,与基于经验模态分解算法的时频表示相比,基于改进的经验模态分解算法的时频表示可以检测到更小的裂纹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vertical Transient Response Analysis of a Cracked Jeffcott Rotor Based on Improved Empirical Mode Decomposition
The crack-induced changes in the vertical transient response of a rotating shaft–disc system, Jeffcott rotor, are investigated for transverse crack detection. The crack is considered as a breathing crack. A novel breathing function is proposed, in which the partially open–closed crack breathing behavior is interpolated between the fully open and closed crack behaviors. The breathing crack excites superharmonic response components of the transient as well as the subharmonic components. A Hilbert–Huang transform based on an improved empirical mode decomposition algorithm is subsequently formulated to evaluate the time–frequency representation of the vertical transient response of the rotor to detect the crack. The results show that the proposed breathing function can effectively reduce the computational effort without sacrificing the accuracy of the crack breathing behavior in the presence of small cracks. It is shown that time–frequency representations based on an improved empirical mode decomposition algorithm can lead to the detection of smaller cracks compared with those based on the empirical mode decomposition algorithm.
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CiteScore
3.20
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