首页> 外文会议>ASME international conference on ocean, offshore and arctic engineering >PROCESSING OF AMBIENT VIBRATION RESPONSE FOR MODAL PARAMETERS IDENTIFICATION OF A JACKET-TYPE OFFSHORE PLATFORM: SEA TEST STUDY
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PROCESSING OF AMBIENT VIBRATION RESPONSE FOR MODAL PARAMETERS IDENTIFICATION OF A JACKET-TYPE OFFSHORE PLATFORM: SEA TEST STUDY

机译:夹克式海上平台模态参数识别的环境振动响应处理:海试验研究

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Modal parameters identification of offshore structures is important for many engineering applications, such as damage detection, structural health monitoring, etc. Operational modal analysis has been widely used for large structures. However, measured signals are inevitably contaminated with noise and may not be clean enough for identifying the modal parameters with proper accuracy. The traditional methods to estimate modal parameters in noisy situation are based on over-determined system to absorb the "noise modes" firstly, and then using the stability diagrams to distinguish the true modes from the "noise modes". However, it is difficult to sort out true modes when the signal noise ratio is low, especially, the "noise modes" will also tend to be stable as the model order increases. This study develops a noise reduction procedure for polyreference complex exponential (PRCE) modal analysis based on ambient vibration responses. In the procedure, natural excitation technique (NExT) is firstly applied to get free decay responses (auto- and cross-correlation functions) from measured (noisy) ambient vibration data, and then the noise reduction method based on solving the partially described inverse singular value problem (PDISVP) is implemented to reconstruct a filtered data matrix from the measured data matrix. In our case, the measured data matrix is block Hankel structured, which is constructed based on the free decay responses. The filtered data matrix should maintain the block Hankel structure and be lowered in rank. When the filtered data matrix is obtained, the PRCE method is applied to estimate the modal parameters. The proposed NExT-PDISVP-PRCE scheme is applied to field test of a jacket type offshore platform. Results indicate that the proposed method can improve the accuracy of operational modal analysis.
机译:海上结构的模态参数识别对于许多工程应用至关重要,例如损伤检测,结构健康监测等。操作模式分析已广泛用于大型结构。但是,测量信号不可避免地会被噪声污染,并且可能不够干净,无法以适当的精度识别模态参数。传统的在噪声环境下估计模态参数的方法是基于过度确定的系统,首先吸收“噪声模式”,然后使用稳定性图将真实模式与“噪声模式”区分开。但是,当信号噪声比低时,很难挑选出真实的模式,特别是随着模型阶数的增加,“噪声模式”也趋于稳定。这项研究开发了一种基于环境振动响应的多参考复指数(PRCE)模态分析的降噪程序。在该程序中,首先应用自然激励技术(NExT)从测量的(嘈杂的)环境振动数据中获得自由衰减响应(自相关函数和互相关函数),然后基于求解部分描述的反奇异值的降噪方法实施值问题(PDISVP)可以从测量的数据矩阵中重建滤波后的数据矩阵。在我们的案例中,测得的数据矩阵是汉克尔结构的块,它是基于自由衰减响应构建的。过滤后的数据矩阵应保持汉克尔块的结构,并降低其排名。当获得滤波后的数据矩阵时,采用PRCE方法估计模态参数。所提出的NExT-PDISVP-PRCE方案被应用于外套式海上平台的现场测试。结果表明,该方法可以提高操作模态分析的准确性。

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