基于动态模态分解的输电杆塔松动检测

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振动与冲击 ›› 2023, Vol. 42 ›› Issue (19) : 204-211.

论文

基于动态模态分解的输电杆塔松动检测

杨金显1,2，申刘阳1,2，郑泽南1,2，李田田1,2，杨雨露1,2

作者信息 +

Transmission tower looseness detection based on dynamic mode decomposition

YANG Jinxian1,2, SHEN Liuyang1,2, ZHENG Zenan1,2, LI Tiantian1,2, YANG Yulu1,2

Author information +

文章历史 +

摘要

为了识别输电杆塔的松动状态，提出分段高阶动态模态分解（SHDMD）的检测方法。为减小振动耦合对检测的影响，利用三轴加速度和三轴角速度构造时间-空间矩阵，从中提取准确的方向振型作为松动特征，首先将时间-空间矩阵在时间维度上划分为若干子矩阵，对每个子矩阵进行空间维度扩展，避免DMD分解时得到错误结果，对扩展后的子矩阵进行DMD分解，得到不同时段的振动模态，利用稳定图筛选出不同时段共有的模态作为真实模态，提取与模态一一对应的方向振型。最后建立灰色关联检测模型，通过计算方向振型的几何特征关联度，识别当前松动状态。模拟杆塔实验与真实杆塔实验结果证明，所提方法能够很好地实现输电杆塔松动位置与松动程度的识别。

Abstract

In order to identify the looseness of transmission towers, a segment high-order dynamic mode decomposition (SHDMD) algorithm is proposed. To reduce the impact of vibration coupling, directional mode shapes are extracted from the time-space matrix using three-axis acceleration and three-axis angular velocity as the feature. First, the time-space matrix is divided into several sub-matrices in time dimension, and each sub-matrix is expanded in space dimension to avoid error results from the DMD decomposition. Expanded sub-matrixes in different periods are decomposed by DMD algorithm for obtaining the vibration modes. The common modes in different periods are selected as the real modes by using the stability diagram, and the directional vibration modes corresponding to the modes are extracted. Finally, the grey correlation detection model is established to identify the current looseness state by calculating the geometric feature correlation degree of the directional vibration mode. The results of model and real tower experiments show that the proposed method can well identify the loose position and degree of transmission towers.

导出引用

杨金显1,2，申刘阳1,2，郑泽南1,2，李田田1,2，杨雨露1,2. 基于动态模态分解的输电杆塔松动检测[J]. 振动与冲击, 2023, 42(19): 204-211

YANG Jinxian1,2, SHEN Liuyang1,2, ZHENG Zenan1,2, LI Tiantian1,2, YANG Yulu1,2. Transmission tower looseness detection based on dynamic mode decomposition[J]. Journal of Vibration and Shock, 2023, 42(19): 204-211

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