GB-SAR城市桥梁安全评估大气参数优化改正和信号降噪理论与方法

With the advantages of non-contact measurement, high precision, high sampling frequency and integrated dynamic monitoring, Ground-Based SAR Interferometry (GB-SAR) has been widely applied in monitoring the dynamic deflection of urban bridges. However, during the dynamic deflection monitoring of urban bridges by GB-SAR, it is vulnerable to be influenced by meteorological factors and environmental factors, which may cause some loss of precision of the obtained dynamic deflection of urban bridges. Moreover, there is also a problem of poor reliability for bridge safety assessment. Therefore, first, this project will focus on the influence mechanism of meteorological factors for dynamic deflection of urban bridges by GB-SAR, and further to build an improved atmospheric parameter correction model by considering the microwave transmission distance, which can reduce the impact of meteorological factors for long term urban bridge monitoring by GB-SAR. Second, this project will explore the noise sources together with the characteristics of different noise frequency scale for dynamic deflection monitoring of urban bridges by GB-SAR, and further to build a two-level de-noising algorithm by integrating multi wavelet threshold de-noising and extreme-point symmetric mode decomposition (ESMD), which can reduce the influence of high frequency noise and low frequency noise, respectively. Third, aiming to perform high precision safety assessment of urban bridges, this project will study on damage identification model based on instantaneous frequency by integrating the ESMD method and direct interpolation method, and further to build the relative deformation density model and relative deformation rate model to obtain the spatial association of key locations on urban bridges. This project will provide a set of relatively systematic theory and method for high precision dynamic deflection monitoring and safety evaluation of urban bridges, which has an important theoretical significance and application value to ensure the healthy operation of urban bridges and reduce the cost of inspection and maintenance for health status of urban bridges.

GB-SAR具有非接触、高精度、高频率和整体动态监测的优势，已广泛应用于城市桥梁动挠度监测。但是，GB-SAR城市桥梁动挠度监测易受到气象因素和复杂环境的影响，降低动挠度精度，导致桥梁安全评估可靠性较差。本课题将重点研究气象因素的影响机制，构建顾及微波传输距离的Essen-Froome大气参数优化改正模型，提高动挠度监测精度；探索GB-SAR城市桥梁动挠度监测的噪声来源及频率分布尺度特点，构建集成多小波阈值去噪和ESMD方法的两级降噪模型，分类降低高频和低频噪声的影响；建立集成ESMD和直接插值法的瞬时频率模型，以及城市桥梁局部相对形变密度和相对形变速率模型，获取城市桥梁关键位置的空间关联性，实现城市桥梁高精度安全评估。本课题可建立一套系统的GB-SAR城市桥梁安全评估大气参数优化改正和信号降噪理论与方法，对推进GB-SAR桥梁健康监测和保障城市桥梁健康运营，具有重要的理论意义和应用价值。

桥梁动挠度作为桥梁安全状态评估的一个重要指标，快速、准确的获取桥梁动挠度，以及基于桥梁动挠度的高精确安全评估已经成为当前研究的热点问题。GB-SAR具有非接触、高精度、高频率和整体动态监测的优势，已经广泛应用于城市桥梁动挠度监测。本项目建立了一套系统的GB-SAR城市桥梁动挠度监测的大气参数优化改正和信号降噪理论与方法。首先，揭示了GB-SAR城市桥梁动挠度监测过程中气象因素在时空分布上的影响机制，获取了GB-SAR城市桥梁动挠度监测的最佳气象因素条件，辅助GB-SAR城市桥梁动挠度监测仪器布设和监测时段选择；探索了气象因素在微波传播路径上的影响机制，构建了顾及微波传输距离的Essen-Froome大气参数优化改正模型，提高动挠度监测的精度。其次，揭示了GB-SAR城市桥梁动挠度监测的噪声来源及不同噪声的频率分布尺度特点，构建了集成多小波阈值去噪方法和ESMD方法的城市桥梁动挠度两级降噪模型，分别针对动挠度信号的高频和低频噪声进行降噪处理，有效的降低噪声对GB-SAR城市桥梁动挠度监测精度的影响，为城市桥梁安全评估提供准确的动挠度时程数据。最后，构建了基于ESMD时频分析和直接插值法的瞬时频率计算模型，建立了城市桥梁局部相对形变密度和相对形变速率的计算模型，精确识别城市桥梁是否发生损伤或发生异变趋势的位置，推动了GB-SAR城市桥梁安全评估的发展。本项目研究成果已应用于我国最拥堵高速公路之一京藏高速、第一条高速铁路京津城际、最古老石拱桥赵州桥等50余典型桥梁，成功探测损坏桥梁3座和异变桥梁17座，提升了桥梁安全状况检测的时效性和准确性，推动了行业技术进步，减轻了桥梁安全检测人员的劳动强度，保障了桥梁的安全性。