基于改进HHT理论的大型桥梁动态特性分析
The Dynamic Characteristics Analysis for the Large Bridge Based on the Improved Hilbert-Huang Transformation
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摘要: 针对Hilbert-Huang变换(HHT)中原经验模态分解法在信号存在中断时出现模态混叠问题,研究了利用噪声辅助的分解方法——总体平均经验模态分解法(ensemble empirical mode decomposition,EEMD)的分解过程及其噪声控制。将此改进的分解方法结合随机减量技术获取振动信号的自由衰减响应,为进一步的Hilbert变换识别模态参数提供有效数据。将该方法结合武汉白沙洲长江大桥GPS实测数据进行了模态识别,结果表明,利用噪声辅助的总体平均经验模态分解法(EEMD)能够有效地克服分解过程中的模态混叠现象,使桥梁模态清晰地分解开来。Abstract: To avoid the problem of modes mixing caused by the intermittent in the data,a method of the ensemble empirical mode decompostion(EEMD) is studied in this paper along with its error effects.In this method the white noise is used to improve the decomposion results.Then the free vibration response can by obtained by the random decrement technique(RDT) together with the improved decomposion results.This can provide the available data for Hilbert transformation to identify the modal parameters.Finally,this is applied on the GPS dynimic monitoring data of the Wuhan Baishazhou Bridge.The results show that the mode parameters can be identify by the EEMD together with RDT effectively.
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