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基于小波阈值降噪的既有砌体承重墙基本频率识别
引用本文:张玉梅,彭斌,李佳蔓,王卓琳.基于小波阈值降噪的既有砌体承重墙基本频率识别[J].上海理工大学学报,2017,39(3):275-281,306.
作者姓名:张玉梅  彭斌  李佳蔓  王卓琳
作者单位:上海理工大学 环境与建筑学院, 上海 200093,上海理工大学 环境与建筑学院, 上海 200093,上海理工大学 环境与建筑学院, 上海 200093,上海市建筑科学研究院(集团)有限公司, 上海 200032
基金项目:国家自然科学基金资助项目(51208300)
摘    要:识别既有砌体承重墙的基本频率对结构安全性评估有重要意义.为了降低噪声对动力测试信号和基本频率识别结果的不利影响,首先通过人工带噪信号分析获得小波阈值降噪方法的优化参数,再通过拟静力试验在墙体模型中实现不同的损伤,通过环境激励获取加速度信号.分别基于原始加速度信号和小波阈值降噪处理后的加速度信号,获得功率谱密度函数,再运用峰值点法识别基本频率.结果表明,采用优化参数进行小波阈值降噪后,基本频率识别结果的变异性更小.所采用的方法可通过降低噪声影响来提高带损伤砌体承重墙的基本频率识别效率,为既有砌体结构安全性评定提供基础数据.

关 键 词:小波阈值降噪  基本频率  识别  砌体墙  既有结构
收稿时间:2016/10/26 0:00:00

Basic Frequency Identification for Existing Masonry Load-Bearing Walls Based on Wavelet Threshold De-noising
ZHANG Yumei,PENG Bin,LI Jiaman and WANG Zhuolin.Basic Frequency Identification for Existing Masonry Load-Bearing Walls Based on Wavelet Threshold De-noising[J].Journal of University of Shanghai For Science and Technology,2017,39(3):275-281,306.
Authors:ZHANG Yumei  PENG Bin  LI Jiaman and WANG Zhuolin
Institution:School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China,School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China,School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China and Shanghai Research Institute of Building Sciences (Group) Co., Ltd., Shanghai 200032, China
Abstract:The basic frequency identification for existing masonry load-bearing walls is important for structural safety assessments.To mitigate the noise impacts on the dynamic test signals and the frequency identification results,artificial noised signals were adopted in the analysis,so as to obtain optimized parameters for the wavelet threshold de-noising method.Then pseudo-static tests were conducted on a wall specimen and the acceleration signals under ambient excitations were recorded.Moreover,the power spectrum density (PSD) functions of the original signals and wavelet threshold de-noised signals were calculated,and then the basic frequencies were identified respectively by using the peak-picking method.It is shown that the variability of the identified frequency decreases by the wavelet threshold de-noising with optimized parameters.By mitigating the noise impacts,the proposed method can improve the effectiveness of the frequency identification for masonry load-bearing walls with damages,and then give fundamental data for the safety assessment of existing masonry structures.
Keywords:wavelet threshold de-noising  basic frequency  identification  masonry wall  existing structure
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