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机构地区:[1]北京金风科创风电设备股份有限公司,北京100176 [2]太原理工大学机械电子研究所,太原030024
出 处:《太原理工大学学报》2011年第4期412-414,共3页Journal of Taiyuan University of Technology
基 金:山西省攻关项目(2010032204)
摘 要:针对传统模态识别方法难以准确识别重频、高阻尼比的模态参数的特点,主要研究了系统在环境激励下不同工况用随机子空间法和Polymax算法识别的模态参数(模态频率、模态阻尼比和模态振型)的变化情况。随机子空间法是一种时域模态参数识别方法,在相邻模态的识别方面,它明显优于一些传统的模态识别方法。Polymax模态识别方法也称为多参考点最小二乘复频域法,在阻尼比的识别方面具有明显的优势。本文通过悬臂梁的对比实验研究验证了它们在不同激励条件下的有效性和可靠性。It is difficult for the traditional methods to identify modal parametes of structures with overlap modal frequencies and high modal damping. With incentive-based environmental ran-dom suhspace method and Polymax algorithm, this paper studied the changes of modal parameters (modal frequencies, modal damping ratios and mode shapes) in different conditions. Random subspace method is a time-domain modal identification method, and in identification of adjacent modes, it is better than some traditional modal identification methods. On the other hand, Polymax, which is also called polyreference least--squares complex frequency domain method,has a clear advantage in damping ratio identification. The comparative experiment study of an cantilever proved their effectiveness and reliability under different excitation conditions.
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