为达到桥梁结构损伤识别的目的,基于小波包分析方法提出了小波包能量变化率平方和(the sum square of wavelet packet energy change rate,简称WPERSS)损伤指标。分别将健康与损伤结构的加速度响应信号进行小波包分解得到小波包能量,通...为达到桥梁结构损伤识别的目的,基于小波包分析方法提出了小波包能量变化率平方和(the sum square of wavelet packet energy change rate,简称WPERSS)损伤指标。分别将健康与损伤结构的加速度响应信号进行小波包分解得到小波包能量,通过计算小波包能量变化率平方和损伤指标进行损伤识别。对简支梁模型进行数值模拟,分析单一损伤与两处损伤时不同损伤程度的损伤识别情况,分析不同噪声水平对识别效果的影响。结果表明,该指标可有效识别损伤位置且对噪声具有鲁棒性。对装配式双塔斜拉桥模型进行试验,联合多个测点响应的损伤指标可以判别结构的不同损伤状态,验证了小波包能量变化率平方和指标的有效性。展开更多
Radio-frequency interference （RFI） affects greatly the quality of the data and retrieval products from space-borne microwave radiometry. Analysis of the Advanced Microwave Scanning Radiometer on the Earth Observing ...Radio-frequency interference （RFI） affects greatly the quality of the data and retrieval products from space-borne microwave radiometry. Analysis of the Advanced Microwave Scanning Radiometer on the Earth Observing System （AMSR-E） Aqua satellite observations reveals very strong and widespread RFI contam- inations on the C- and X-band data. Fortunately, the strong and moderate RFI signals can be easily identified using an index on observed brightness temperature spectrum. It is the weak RFI that is diffi- cult to be separated from the nature surface emission. In this study, a new algorithm is proposed for RFI detection and correction. The simulated brightness temperature is used as a background signal （B） and a departure of the observation from the background （O–B） is utilized for detection of RFI. It is found that the O–B departure can result from either a natural event （e.g., precipitation or flooding） or an RFI signal. A separation between the nature event and RFI is further realized based on the scattering index （SI）. A positive SI index and low brightness temperatures at high frequencies indicate precipitation. In the RFI correction, a relationship between AMSR-E measurements at 10.65 GHz and those at 18.7 or 6.925 GHz is first developed using the AMSR-E training data sets under RFI-free conditions. Contamination of AMSR-E measurements at 10.65 GHz is then predicted from the RFI-free measurements at 18.7 or 6.925 GHz using this relationship. It is shown that AMSR-E measurements with the RFI-correction algorithm have better agreement with simulations in a variety of surface conditions.展开更多
文摘为达到桥梁结构损伤识别的目的,基于小波包分析方法提出了小波包能量变化率平方和(the sum square of wavelet packet energy change rate,简称WPERSS)损伤指标。分别将健康与损伤结构的加速度响应信号进行小波包分解得到小波包能量,通过计算小波包能量变化率平方和损伤指标进行损伤识别。对简支梁模型进行数值模拟,分析单一损伤与两处损伤时不同损伤程度的损伤识别情况,分析不同噪声水平对识别效果的影响。结果表明,该指标可有效识别损伤位置且对噪声具有鲁棒性。对装配式双塔斜拉桥模型进行试验,联合多个测点响应的损伤指标可以判别结构的不同损伤状态,验证了小波包能量变化率平方和指标的有效性。
基金Supported by the National Key Basic Research and Development (973) Program of China(2010CB951600)National Natural Science Foundation of China(40875015,40875016,and40975019)+2 种基金Special Fund for University Doctoral Students of China(20060300002)Chinese Academy of Meteorological Sciences"Application of Meteorological Data in GRAPES-3DVar" ProgramNOAA/NESDIS/Center for Satellite Applications and Research (STAR) CalVal Program
文摘Radio-frequency interference （RFI） affects greatly the quality of the data and retrieval products from space-borne microwave radiometry. Analysis of the Advanced Microwave Scanning Radiometer on the Earth Observing System （AMSR-E） Aqua satellite observations reveals very strong and widespread RFI contam- inations on the C- and X-band data. Fortunately, the strong and moderate RFI signals can be easily identified using an index on observed brightness temperature spectrum. It is the weak RFI that is diffi- cult to be separated from the nature surface emission. In this study, a new algorithm is proposed for RFI detection and correction. The simulated brightness temperature is used as a background signal （B） and a departure of the observation from the background （O–B） is utilized for detection of RFI. It is found that the O–B departure can result from either a natural event （e.g., precipitation or flooding） or an RFI signal. A separation between the nature event and RFI is further realized based on the scattering index （SI）. A positive SI index and low brightness temperatures at high frequencies indicate precipitation. In the RFI correction, a relationship between AMSR-E measurements at 10.65 GHz and those at 18.7 or 6.925 GHz is first developed using the AMSR-E training data sets under RFI-free conditions. Contamination of AMSR-E measurements at 10.65 GHz is then predicted from the RFI-free measurements at 18.7 or 6.925 GHz using this relationship. It is shown that AMSR-E measurements with the RFI-correction algorithm have better agreement with simulations in a variety of surface conditions.
