Abstract:

For the strain mode indicators of bridge structure in bridge health monitoring, vibrating string strain sensor is usually to be used, but its noise source is a low-frequency vibration on bridge. The accuracy of information which is collected will be affected by low-frequency noise. In this paper, Adaptive Kalman Filter will be taken in the signal processing of strain mode indication. According to the feature of bridge detection signal to establish adaptive dynamic filtering model, at the same time, using this model to simulink actual strain monitoring data which comes from a bridge of Gansu. The result shows that the model can correctly reflect change of bridge strain modal indicators ,low-frequency noise could be effectively restrained, measurement accuracy could be improved, and could provide reliable data for bridge health assessment.

摘要：

针对桥梁健康监测中的桥梁结构的应变模态指标，一般采用振弦式应变传感器来测量，其噪声源对桥梁检测来说属于低频振动，低频噪声会影响到采集信息的准确性。为此，将自适应卡尔曼滤波用于应变模态指标的信号处理中，根据桥梁检测信号的特征建立自适应动态滤波模型，并用该模型对甘肃某大桥的实际应变监测数据进行仿真。仿真结果表明，该模型能有效抑制低频噪声，正确反映桥梁应变模态指标的变化，提高信号的测量精度，为桥梁健康评估提供可靠数据。

关键词: 振动与波, 应变模态, 振弦式应变传感器, 低频噪声, 自适应卡尔曼滤波