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Electro-Mechanical Impedance Based Position Identification of Bolt Loosening Using LibSVM

机译:使用LibSVM的基于机电阻抗的螺栓松动位置识别

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Bolt loosening is a common structural failure, which received extensive attention from many industrial departments. Because the uneven stress on different directions of a bolt is the common reason that the bolt becomes loose, it is quite important to carry out the research about sensitive detection of bolt loosening. Using Agilent 4924A instrument, this paper precedes the loosening test of bolts based on Electro-Mechanical Impedance (EMI), on an aluminum plate instead of flange plate for simplification. And the electromechanical admittance is given according to the fundamental equation of Piezo-Material Lead Zirconate Titanate (PZT). Specifically, the paper first studies the detecting sensitivity of EMI on bolt loosening; then, it shows that RMSD can be seen as a good damage index to identify damage; at last, our experiment result shows that by using LibSVM to process big data, the position of a loose bolt can be correctly identified from 12 possible bolt positions. The method mentioned in this paper shows the great potential to be used for the damage monitoring of bolted structure.
机译:螺栓松动是一种常见的结构故障,已引起许多工业部门的广泛关注。由于螺栓不同方向上的应力不均匀是螺栓松动的常见原因,因此进行灵敏的螺栓松动检测研究非常重要。为了简化起见,本文使用Agilent 4924A仪器对基于机电阻抗(EMI)的螺栓进行了松动测试,然后在铝板上而不是法兰板上进行了松动测试。并根据压电材料锆钛酸铅(PZT)的基本方程式给出了机电导纳。具体而言,本文首先研究了EMI对螺栓松动的检测灵敏度。然后,它表明RMSD可以看作是识别损坏的良好损坏指数;最后,我们的实验结果表明,通过使用LibSVM处理大数据,可以从12个可能的螺栓位置正确识别出松动的螺栓位置。本文提到的方法显示了用于螺栓结构损伤监测的巨大潜力。

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