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机构地区:[1]长沙理工大学桥梁工程安全控制省部共建教育部重点实验室,长沙410004 [2]东南大学土木工程学院,南京210096
出 处:《防灾减灾工程学报》2013年第6期624-630,共7页Journal of Disaster Prevention and Mitigation Engineering
基 金:国家自然科学基金项目(51308073;51378081);教育部博士点新教师基金项目(20124316120002);桥梁工程安全控制省部共建教育部重点实验室开放基金重点项目(12KB02);湖南省自然科学青年基金项目(14JJ3087)资助
摘 要:基于小波包分析技术从悬索桥的加速度振动响应中提取出小波包能量比,进而定量地分析了由环境激励所引起的实测小波包能量比的变异性。首先,采用多样本平均技术消除了由识别算法所带来的小波包能量比的固有随机性,得到了小波包能量比的日平均值;其次,通过建立季节相关性模型得到了温度对小波包能量比影响的定量评价;最后,分别建立交通荷载和风与小波包能量比的相关性模型,并定量评价了交通荷载和风对小波包能量比的影响。分析结果表明,温度和固有随机性是小波包能量比变异性的最主要来源,而交通荷载和风所引起的变异性较小。由于温度和小波包能量比的季节相关性模型可以有效地消除温度和固有随机性对小波包能量比的影响,因此当季节相关性模型偏离这种正常状态的模型时,就可以对悬索桥做出损伤预警。This paper addresses the quantitative evaluation of environmental variability of wavelet packet energy spectrum (WPES) extracted from the ambient dynamic responses of a suspension bridge using wavelet packet transform (WPT). liminate the inherent randomness arising from The daily averaged WPES are first obtained to e- the identification algorithm. Then the effect of temperature on the measured WPES is quantified using the seasonal correlation models. The traf- fic-induced and wind-induced variability are further quantitatively evaluated by the traffic-WPES and wind-WPES correlation models. The results reveal that temperature and inherent random- ness are the governing sources of WPES variability. And the WPES variability caused by wind speed and traffic loadings is negligible compared to temperature and inherent randomness. Con- sidering seasonal correlation models of temperature-WPES can effectively eliminate the tempera- ture effect and inherent randomness, so it is suitable for structural damage alarming of long-span bridges if future seasonal correlation models deviate from these normal models.
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