基于经验模式分解的框架结构螺栓松动检测实验研究

周文强,肖黎,屈文忠

振动与冲击 ›› 2016, Vol. 35 ›› Issue (8) : 201-206.

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PDF(1627 KB)
振动与冲击 ›› 2016, Vol. 35 ›› Issue (8) : 201-206.
论文

基于经验模式分解的框架结构螺栓松动检测实验研究

  • 周文强,肖黎,屈文忠
作者信息 +

Detection of bolt looseness in frame structures using empirical mode decomposition

  • Wenqiang Zhou, li Xiao, Wenzhong Qu
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文章历史 +

摘要

螺栓松动损伤具有非线性特征,在低、高频激励共同作用下,结构动力响应会出现高频激励与结构固有频率之间的调制现象。利用该调制现象,本文发展了一种基于经验模式分解(EMD)的螺栓松动检测方法,分别对高频正弦和随机激励下结构响应信号进行EMD分解并作功率谱分析,采用EMD分解后含有调制成分的高频固有模式函数(IMF)构造能量损伤指标来识别结构螺栓松动。采用多尺度法进行单自由度非线性模型分析解释高频调制现象,并通过螺栓连接框架结构的振动实验验证了该方法的有效性。结果表明,螺栓松动时,响应信号频域中出现高频激励与固有频率间的调制成分,所构造的能量损伤指标能够有效识别螺栓松动损伤,并且对于初始松动损伤识别更为敏感。

Abstract

Bolt looseness is a nonlinear damage which would result in the occurrence of modulation between excitation frequency and natural frequencies by a combination of low and high frequency excitations. Using the vibration modulation, this paper develops a vibration-based method for detecting bolt looseness based on empirical mode decomposition (EMD).The response signal is analyzed for nonlinear modulation in frequency domain. Then, using the high-frequency intrinsic mode functions which contain the frequency modulation component based on EMD, an effective energy-based damage index is established to detect the presence of the nonlinear damage, with the analysis of energy distribution. A four-story frame structure vibration testing is carried out to investigate the feasibility of the method. The result of experiments demonstrates that modulation is occurred in the high-frequency component of response signals; the proposed energy-based damage index can be used to accurately detect nonlinear damage caused by bolt looseness and is sensitive to the structural early damage.

关键词

螺栓松动 / 损伤识别 / 经验模式分解 / 能量损伤指标 / 调制

Key words

Bolt Looseness / Damage Detection / Empirical Mode Decomposition / Energy Damage Index / Modulation

引用本文

导出引用
周文强,肖黎,屈文忠. 基于经验模式分解的框架结构螺栓松动检测实验研究[J]. 振动与冲击, 2016, 35(8): 201-206
Wenqiang Zhou, li Xiao, Wenzhong Qu. Detection of bolt looseness in frame structures using empirical mode decomposition[J]. Journal of Vibration and Shock, 2016, 35(8): 201-206

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