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螺栓松紧程度的受控敲击检测方法
引用本文:向志海,黄俊涛.螺栓松紧程度的受控敲击检测方法[J].实验力学,2012,27(5):545-551.
作者姓名:向志海  黄俊涛
作者单位:清华大学航天航空学院工程力学系,北京,100084
基金项目:国家自然科学基金(10802040)、科技部支撑计划(2011BAK06B03)资助
摘    要:螺栓连接是工程中大量使用的装配形式.在振动等环境因素的作用下,螺栓很可能会发生松动,这样不但会影响结构的正常功能,严重时还会导致安全事故.因此,螺栓松紧程度的无损检测方法一直受到研究者的关注.为了发展一种简单有效的检测方法,本文回避了复杂的非线性动力学分析,而直接根据螺栓敲击装置加速度功率密度谱中的敏感频段来检测螺栓的松动情况.另外,本方法要求对敲击力进行严格控制,以保证激励的可重复性,这样就可以结合支持向量机方法来定量地检测螺栓的松紧程度.实验表明,方法可以较好地实现对螺栓的松紧程度的定量检测,特别是对于螺栓全松和螺栓刚开始松动这两种情况,可以达到较高的检测精度.

关 键 词:敲击检测法  无损检测  螺栓  支持向量机
收稿时间:2/8/2012 12:00:00 AM

A Controlled Tap Detection Method for Bolt Tightness
XIANG Zhi-hai and HUANG Jun-tao.A Controlled Tap Detection Method for Bolt Tightness[J].Journal of Experimental Mechanics,2012,27(5):545-551.
Authors:XIANG Zhi-hai and HUANG Jun-tao
Institution:Department of Engineering Mechanics, School of Aerospace, Tsinghua University, Beijing 100084, China;Department of Engineering Mechanics, School of Aerospace, Tsinghua University, Beijing 100084, China
Abstract:Bolt connection is an assembly form extensively used in engineering. Vibration or other ambient conditions may lead to bolt loosing, therefore the normal structure function may be deteriorated and even lead to severe security accidents. So, non-destructive testing method for bolt tightness has been concerned by researchers. In this paper, the sensitive part of power spectrum density of a bolt tapping device was adopted to detect the bolt loosing state. Since the tapping force is strictly controlled to ensure stimulation repeatability, the bolt loosing state can be quantitatively determined by using support vector machine method. Thus, a simple and effective detection method was developed without using complex nonlinear dynamic analysis. Experimental results demonstrate that good quantitative detection of bolt loosing state is possible by using the proposed method. Especially, when bolt is completely loosened or is at the beginning stage of loosing, a higher detection accuracy can be obtained.
Keywords:tap detection method  non-destructive inspection  bolt  surpport vector machine
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