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首页> 外文会议>Society for Machinery Failure Prevention Technology Meeting; 20050418-21; Virginia Beach,VA(US) >A Time and Frequency Domain On-line Crack Identification of Stiffened Plate Panels
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A Time and Frequency Domain On-line Crack Identification of Stiffened Plate Panels

机译：加筋板的时频域在线裂纹识别

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摘要

This paper describes a methodology for on-line crack identification of a stiffened plate structure. The methodology is based on the measured/computed root mean square (rms) amplitude response obtained from random vibration testing and analysis. The random excitation force simulated the excitation force exerted on the structure due to the modeled wave spectrum (with a dominant frequency of 2 Hz). The fundamental frequency of the structure was 584.3 Hz (flexural-torsional frequency of the main stiffener), whereas the first bending frequency of the stiffened plate system was 1136.7 Hz. The basic idea is that when a crack is present in a structure, the computed/measured rms amplitude of response would change; and by monitoring the rms responses at several locations for several crack cases, the crack location and extent could be identified. A one-twentieth scale model, of a stiffened side shell panel of a tanker ship structure, was tested in the experimental study; a specimen was tested for different crack development scenarios. Since the methodology does not require the measurement of the excitation forces, the measured structural responses were normalized by the computed rms response amplitude [computed for the excitation frequency range (0 to 5 Hz)]. Results of testing carried out on the model and analysis of test results for predicting various damage cases are reported.
机译：本文介绍了一种用于在线识别刚性板结构的方法。该方法基于从随机振动测试和分析获得的测量/计算的均方根（rms）幅度响应。随机激发力模拟了由于建模的波谱（主频为2 Hz）而施加在结构上的激发力。结构的基本频率为584.3 Hz（主加强筋的弯曲扭转频率），而加强板系统的第一弯曲频率为1136.7 Hz。基本思想是，当结构中存在裂缝时，计算/测量的响应均方根值将发生变化；通过监测几个裂纹情况在几个位置的均方根响应，可以确定裂纹的位置和程度。在实验研究中测试了油轮船结构的加劲侧壳板的二十分之一比例模型；对样品进行了不同的裂纹扩展方案测试。由于该方法不需要测量激振力，因此可以通过计算出的均方根响应幅度（针对激振频率范围（0到5 Hz）计算得出）对测量的结构响应进行归一化。报告了在模型上执行的测试结果，以及用于预测各种损坏情况的测试结果分析。

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