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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。
Based on the wavelet packet analysis, the wavelet packet energy ratio is extracted from the acceleration vibration response of the suspension bridge, and then the variability of the measured wavelet packet energy ratio caused by the environmental excitation is quantitatively analyzed. First of all, by using the multiple sample averaging technique, the inherent randomness of the wavelet packet energy ratio caused by the recognition algorithm is eliminated, and the daily average of the wavelet packet energy ratio is obtained. Secondly, the temperature dependence of the wavelet packet is obtained by establishing the seasonal correlation model. Finally, the correlation model between traffic load and the energy ratio of wind and wavelet packet is established, and the influence of traffic load and wind on the energy ratio of wavelet packet is quantitatively evaluated. The results show that the temperature and the inherent randomness are the most important sources of energy ratio variability of wavelet packet, while the variability caused by traffic load and wind is small. Since the seasonal correlation model of temperature and wavelet packet energy ratio can effectively eliminate the influence of temperature and inherent randomness on the energy ratio of wavelet packet, when the seasonal correlation model deviates from the model of this normal state, the suspension bridge can be made Injury warning.