在基于振动的结构损伤识别中,很多结构动力学的参数可用作损伤特征参数,如共振频率、振型、模态柔度等.结构损伤会引起损伤特征参数发生改变,但环境因素和运营条件的影响也会使这些特征参数发生变化,而且这种变化往往会掩盖结构自身损伤所引起的特征参数变化.如何剔除或减少诸多环境因素的影响,得到结构本身的真实状况(有损或无损),成为了桥梁损伤检测和健康监测中的一个关键问题.选用对结构损伤较为敏感的模态柔度作为损伤特征参数,通过数值模拟算例对比分析了结构局部损伤和温度变化对模态柔度的影响;对结构在不同状态下的模态柔度进行主成分分析,用残差建立其统计分布模式,用统计模式识别的方法识别模式差异,实现考虑环境因素影响的结构异常检测.结果表明,若不考虑温度对模态柔度的影响,易对桥梁结构的健康状况产生误判;运用基于主成分分析的结构异常检测方法可有效剔除温度对模态柔度的影响,实现结构异常的检测.%Damages of a structure are detected through observing changes in vibration features, such as natural frequencies, modal shapes and modal flexibility. Modal parameters are affected by not only damage in structure but also environmental and operational conditions. Compared to changes in modal parameters induced by environmental and operational effect, those by local damage in structure may be much smaller. The subtle changes caused by delicate damage in structure may be masked due to such effect. To get real state of structure, it is highly necessary to eliminate effect ofenvironmental and operational condition on modal parameters. Modal flexibility was chosen as damage parameter for its sensitivity to damage. Via numerical model of a simply supported beam, effect of local structural damage and temperature on modal flexibility was analyzed comparatively. After principal component analysis (PCA) was applied to modal flexibility under different conditions, statistical distribution patterns were established based on the residual errors of the PCA model. The structural novelty under environmental variations could be diagnosed by recognizing difference between the patterns using the method of statistical pattern recognition. It was demonstrated that false damage diagnosis may occur without considering effect of environmental variations; PCA-based novelty detection can effectively eliminate temperature influences on modal flexibility and provide indication of structural novelty.
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