現代社會經濟和人民生活都須仰賴電力來維持運作，因此電力系統可視為現在生活的基石，尤其台灣地形崎嶇，電力運輸系統大部分都由輸電鐵塔以架空纜線的方式來串聯台灣輸電網，一旦某座輸電鐵塔結構損壞，可能會造成大面積的電力運輸系統中斷，危害到社會經濟及人民生活的損失，這使輸電鐵塔結構會是電力運輸系統中不容忽視的一環，因此對於輸電鐵塔的結構健康診斷為重要的研究方向。
輸電鐵塔監測之工作項目主要有現地微振量測及現地環境因素量測二部分，本研究根據現地微振量測資料進行自動化模態識別分析，取得每小時的模態頻率，並考慮其受到風速、溫度及振動幅度等環境因素之影響進行迴歸分析，根據模態頻率的迴歸值與量測值之誤差設定模態頻率的行動值與警戒值。之後，利用鐵塔有限元素模型之關鍵桿件剛度折減來模擬損傷案例，了解本研究所提出之行動值與警戒值是否可作為判斷損傷發生之依據。
此外，本研究發現颱風事件過後數個月內，鐵塔之數個高頻模態有明顯不同之趨勢，並於平均氣溫開始下降時又恢復原本趨勢。未來研究應考量颱風事件造成之趨勢變化，並據以設定更敏感之行動值與警戒值。

Modern social economy and people's lives must rely on electricity to maintain operations. Once the structure of a transmission tower is damaged, it may cause a large-scale power transmission system to be interrupted, which will endanger the loss of social economy and people's lives. This makes the transmission tower structure be a key point of the electric transportation system. Therefore, for the transmission tower structural health monitoring is an important research.
The work of monitoring the transmission tower mainly includes the local micro-vibration measurement and the local environmental factor measurement. This study identifies the vibration measurement data by automated modal analysis. The regression analysis is performed on the influence of environmental factors such as wind speed, temperature and vibration, and the action value and the alert value are set according to the error of the regression value of the modal frequency and the measured value. After that, the damage case is simulated by using the key member stiffness reduction of the finite element model of the tower to understand whether the action value and the alert value proposed in this study can detect the damage.
In addition, this study found that several high-frequency modals of the tower have a trend within a few months after the typhoon event, and the original trend is restored when the temperature begins to decrease. Future research should consider trends in typhoon events and set more sensitive action and alert values.

1. Devriendt, C., Magalhaes, F., Weijtjens, W., De Sitter, G., Cunha, A., & Guillaume, P. (2014). Structural health monitoring of offshore wind turbines using automated operational modal analysis. Structural Health Monitoring-an International Journal, 13(6), 644-659. doi:10.1177/1475921714556568
2. Peeters, B., & De Roeck, G. (2001). One-year monitoring of the Z24-Bridge: environmental effects versus damage events. Earthquake Engineering & Structural Dynamics, 30(2), 149-171. doi:Doi 10.1002/1096-9845(200102)30:2<149::Aid-Eqe1>3.0.Co;2-Z
3. Reynders, E., Houbrechts, J., & De Roeck, G. (2012). Fully automated (operational) modal analysis. Mechanical Systems and Signal Processing, 29, 228-250. doi:10.1016/j.ymssp.2012.01.007
4. Ubertini, F., Comanducci, G., & Cavalagli, N. (2016). Vibration-based structural health monitoring of a historic bell-tower using output-only measurements and multivariate statistical analysis. Structural Health Monitoring: An International Journal, 15(4), 438-457. doi:10.1177/1475921716643948
5. Van Overschee, P., & De Moor, B. (2012). Subspace identification for linear systems: Theory—Implementation—Applications: Springer Science & Business Media.
6. Verboven, P., Cauberghe, B., Parloo, E., Vanlanduit, S., & Guillaume, P. (2004). User-assisting tools for a fast frequency-domain modal parameter estimation method. Mechanical Systems and Signal Processing, 18(4), 759-780. doi:10.1016/S0888-3270(03)00053-0
7. Weijtjens, W., Verbelen, T., De Sitter, G., & Devriendt, C. (2016). Foundation structural health monitoring of an offshore wind turbinea full-scale case study. Structural Health Monitoring-an International Journal, 15(4), 389-402. doi:10.1177/1475921715586624
8. Wu, W.-H., Wang, S.-W., Chen, C.-C., & Lai, G. (2017). Assessment of environmental and nondestructive earthquake effects on modal parameters of an office building based on long-term vibration measurements. Smart Materials and Structures, 26(5), 055034. doi:10.1088/1361-665X/aa6ae6
9.