基于小波包分析的输电塔螺栓松动损伤识别方法

高压输电铁塔结构健康监测对保证输电线路安全运行具有重要意义，输电塔结构发生破坏时，节点板螺栓首先会发生松脱，有必要对节点板上的螺栓进行损伤识别。用ABAQUS有限元分析软件建立输电塔结构多尺度模型，利用小波包变换，引入小波包能量变化率作为损伤识别指标，提取出螺栓周围测点的动应变数据，对塔腿处一块节点板螺栓松动的不同工况进行损伤识别；以基于物联网技术的传感器为信号传输设备，利用高精度的PVDF压电薄膜应变片为数据采集设备，在实际输电塔结构底部施加激励荷载，提取节点板上测点的动应变对该损伤识别方法进行试验验证。结果表明，该损伤识别指标对测点附近的螺栓松动较敏感，并且在所有测点处的最小值能较好地识别出节点板的损伤程度。

Damage identification of bolt looseness in transmission tower based on wavelet packet analysis

The structure health monitoring of high voltage transmission tower was very important to ensure the safe operation of the transmission line. When the transmission tower structure was damaged, the gusset plate bolts would be loosened first. The multiscale model of the transmission tower structure is established by using ABAQUS finite element analysis software. The energy change rate of the wavelet packet was taken as the damage index. The damage identification was carried out under different working conditions when bolt looseness of a joint plate at the tower leg. The signal transmission equipment was a sensor based on Internet of Things technology. The data acquisition equipment was PVDF piezoelectric film strain gauge. Applying excitation loads at the bottom of the actual transmission tower structure, the dynamic strain of the measured points on the gusset plate was extracted to verify the damage identification method. The test results show that the damage index can accurately identify the damage degree of the gusset plate. It is also sensitive to bolt looseness near the measuring point.