基于传感网络的桥梁承压信号提取算法研究

Research on bridge pressure-bearing signal extraction algorithm based on sensor network

针对基于时间序列分析算法的桥梁承压信号提取算法容易受到噪声的干扰,信号提取过程存在较高的滞后性,预警性能差的问题,提出基于传感网络的桥梁承压信号提取算法。基于桥梁承压传感器优化布置理论,塑造桥梁承压传感器合理布局数学模型,融合MAC矩阵和传感器布局数学模型,对桥梁承压传感器数目进行高效控制,通过蚁群算法实现桥梁承压传感器的合理布局。完成传感器的合理布局后,在布局的传感器监测点中融合GNSS接收机以及加速度计两种传感器,获取桥梁承压信号,并通过LMS自适应滤波器过滤桥梁承压信号中的随机噪声,提取桥梁承压信号中的关键部分。实验结果表明,所提算法实现了桥梁承压信号的准确采集、桥梁状况整体评估,具有较强的预警性能。

Since the bridge pressure-bearing signal of the traditional signal extraction algorithm based on time series analysis algorithm is easily disturbed by the noise,and the algorithm has high lag and poor early warning performance,the bridge pressure-bearing signal extraction algorithm based on sensor networks is proposed.On the basis of the optimization layout theory of bridge pressure-bearing sensor,the reasonable layout mathematic model of bridge pressure-bearing sensor is constructed.The MAC matrix and sensor layout mathematical model are fused to efficiently control the number of bridge pressure-bearing sensor.The ant colony algorithm is used to realize the reasonable layout of the bridge pressure-bearing sensor,and then the GNSS receiver and accelerometer are fused in the monitoring points of the layout sensors to acquire the bridge pressure-bearing signal.The LMS adaptive filter is adopted to filter the random noise in the bridge pressure-bearing signal,and extract the key part of the bridge pressure-bearing signal.The experimental results show that the proposed algorithm realizes the accurate acquisition of bridge pressure-bearing signal and overall evaluation of bridge condition,and has strong early warning performance.