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Experimental Study of a Multipoint Random Dynamic Loading Identification Method Based on Weighted Average Technique

机译:基于加权平均技术的多点随机动态加载识别方法的实验研究

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Most of random dynamic loading identification research studies are about the original inverse pseudoexcitation method which does not fundamentally reduce the negative effect of ill-conditioned frequency response function matrix on accuracy of loading identification. This paper describes a new improved method based on weighted average technique to reduce peak errors between identified load spectrum and the actual load spectrum near some natural frequencies. Meanwhile, relative error of root mean square value between identified load and the actual load is reduced. The introduced selection method of threshold value is innovative which is the key of weighted average technique. This improved loading identification method is successfully applied to experiments of cantilever beam and thermal protection composite plate structure. Identification results prove that the proposed method is valid by good agreement between identified power spectrum density and the actual one. Moreover, this method has higher accuracy than inverse pseudoexcitation method in low-frequency band.
机译:大多数随机动态加载识别研究研究是关于原始逆伪渗透方法,它不会从根本上降低不良状态频率响应函数矩阵对加载识别精度的负面影响。本文介绍了一种基于加权平均技术的新改进方法,以减少鉴定的负载谱与一些自然频率附近的实际负载谱之间的峰值误差。同时,识别负载与实际负载之间的根均方值的相对误差减小。介绍的阈值选择方法是创新性,这是加权平均技术的关键。这种改进的加载识别方法成功应用于悬臂梁和热保护复合板结构的实验。鉴定结果证明,所提出的方法在鉴定的功率谱密度与实际良好之间有效。此外,该方法的精度高于低频带中的逆伪透精方法。

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