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Identification of multiple damage in beams based on robust curvature mode shapes

机译:基于鲁棒曲率模式形状的光束多重损伤识别

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Multiple damage identification in beams using curvature mode shape has become a research focus of increasing interest during the last few years. On this topic, most existing studies address the sensitivity of curvature mode shape to multiple damage. A noticeable deficiency of curvature mode shape, however, is its susceptibility to measurement noise, easily impairing its advantage of sensitivity to multiple damage. To overcome this drawback, the synergy between a wavelet transform (WT) and a Teager energy operator (TEO) is explored, with the aim of ameliorating the curvature mode shape. The improved curvature mode shape, termed the TEO-WT curvature mode shape, has inherent capabilities of immunity to noise and sensitivity to multiple damage. The efficacy of the TEO-WT curvature mode shape is analytically verified by identifying multiple cracks in cantilever beams, with particular emphasis on its ability to locate multiple damage in noisy conditions; the applicability of the proposed curvature mode shape is experimentally validated by detecting multiple fairly thin slots in steel beams with mode shapes acquired by a scanning laser vibrometer. The proposed curvature mode shape appears sensitive to multiple damage and robust against noise, and therefore is well suited to identification of multiple damage in beams in noisy environments.
机译:在最近几年中,使用曲率模式形状的梁的多次损伤识别已成为人们越来越感兴趣的研究重点。关于此主题,大多数现有研究都针对曲率模式形状对多重损伤的敏感性。但是,曲率模式形状的一个明显缺陷是它对测量噪声的敏感性,很容易损害其对多重损伤的敏感性。为了克服此缺点,探索了小波变换(WT)和Teager能量算子(TEO)之间的协同作用,旨在改善曲率模式形状。改进的曲率模态形状(称为TEO-WT曲率模态形状)具有固有的抗噪能力和对多种损伤的敏感性。通过确定悬臂梁中的多个裂纹来分析验证了TEO-WT曲率模态形状的有效性,特别强调了它在嘈杂条件下定位多个损伤的能力;通过检测具有扫描激光测振仪采集的模态形状的钢梁中的多个相当细的缝隙,通过实验验证了所提出的曲率模态形状的适用性。提出的曲率模式形状看起来对多重损伤敏感并且对噪声具有鲁棒性,因此非常适合于在嘈杂环境中识别光束中的多重损伤。

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