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Transmission towers play a critical role in power systems. In this study, we propose an innovative approach for the structural health monitoring of transmission towers with the aim of accurately identifying structural looseness and its location, facilitating timely warnings. By utilizing Micro Inertial Measurement Unit (MIMU) technology, we successfully capture the comprehensive dynamic behavior of transmission towers. Subsequently, we employ the extended Dynamic Mode Decomposition (DMD) to successfully capture the looseness features of transmission towers, leading to the development of looseness features: Dynamic Mode Participation Ratio and Degree of Freedom Mode Shape. This process, developed with signal window, delay embedding and cluster stability diagrams, addresses the shortcomings of the DMD algorithm when dealing with vibration data in complex engineering environments. To further identify the areas of looseness in transmission towers, we introduce the Dempster-Shafer (D-S) evidence theory, enabling the full utilization of information within the looseness indicators. Experimental results demonstrate that our proposed method consistently delivers precise and robust identification results for looseness and its location in various cases. This research not only provides an innovative solution for the detection of looseness in transmission towers but also offers valuable insights for the health monitoring and maintenance of similar structures, contributing to the reduction of potential accidents.

Looseness Identification of Transmission Tower Based on Inertial Measurement