Damage Detection in Bolted Connections of Power Transmission Towers Using Machine Learning-Based Methods (Bagging Trees)

Authors

Faculty of Civil Engineering, University of Amirkabir University of Technology, Tehran, Iran

Abstract

There have been many studies regarding the health monitoring and detection of transmission towers, among which we can refer to the article by Yen et al. in 2009, who investigated damage detection in transmission towers with a limited number of sensors those modal parameters were obtained from the measured environmental vibration data. In their research, mode shape and frequency were used to identify the system. Also, stiffness reduction was also suggested to damage detection. Structural health monitoring by using features such as natural frequencies and mode shapes has attracted the attention of a number of researchers. Damage detection in power transmission towers using these features and using soft computing methods was also considered by Skarbek et al. in 2014. They have investigated frequency damage indicators by simple processing and using neural network for power transmission tower. In 2019, Zhao et al obtained the natural frequency of the 110 kV power transmission tower using the sub-random space method and found that the detected natural frequency is dependent on the wind speed. However, the current article tries to damage detection in the connections due to the lack of access to real data and experimental data and based on numerical modeling of a limited number of possible damages that occurred in the legs of the splice connection of power transmission tower.

Keywords

Main Subjects

References

"مشخصات فنی عمومی و اجرایی پست­ ها، خطوط فوق توزیع و انتقال، ترکیب بارگذاری نیروها بر سازه ­های پست­ های فشار قوی"، نشریه شماره 457، معاونت برنامه ­ریزی و نظارت راهبردی رئیس­ جمهور، دفتر نظام فنی اجرایی، دی 1387.
Chen JW, Li L, “Investigation on dynamic response of steel tower structure under time-history wind load”, In Applied Mechanics and Materials, Trans Tech Publications Ltd, 2012, 166699-707. https://doi.org/10.4028/www.scientific.net/AMM.166-169.699.
Dyrbye C, Hansen SO, “Wind loads on structures, 1997. ISBN: 978-0-471-95651-8.
Karami-Mohammadi R, Mirtaheri M, Salkhordeh M, Hariri-Ardebili MA, “Vibration anatomy and damage detection in power transmission towers with limited sensors”, Sensors, 2020, 20 (6), 1731. https://doi.org/10.3390/s20061731.
Skarbek L, Zak A, Ambroziak D, “Damage detection strategies in structural health monitoring of overhead power transmission system”, In EWSHM-7th European Workshop on Structural Health Monitoring, 2014. hal-01020412, version 1 (08-07-2014).
Szafran J Rykaluk K, “Steel lattice tower under ultimate load-chosen joint analysis”, Civil and Environmental Engineering Reports, 2017, 25 (2), 199-210. http://dx.doi.org/10.1515/ceer-2017-0030.
Ungkurapinan N, “A study of joint slip in galvanized bolted angle connections (Master's thesis)”, 2000. http://hdl.handle.net/1993/2341.
Yin T, Lam HF, Chow HM, Zhu HP, “Dynamic reduction-based structural damage detection of transmission tower utilizing ambient vibration data”, Engineering Structures, 2009, 31 (9). https://doi.org/10.1016/j.engstruct.2009.03.004.
Zhang T, Biswal S, Wang Y, “SHMnet: Condition assessment of bolted connection with beyond human-level performance”, Structural Health Monitoring, 2020, 19 (4), 1188-1201. https://doi.org/10.1177/1475921719881237.
Zhao L, Huang X, Zhang Y, Tian Y, Zhao Y, “A vibration-based structural health monitoring system for transmission line towers”, Electronics, 8 (5), 515. https://doi.org/10.3390/electronics8050515.
Zhao Y, Xiao Y, Wang H, Wang T, Wu C, Zhang B, “Effect of bolt tightening force on the transmission tower modal parameters and a method for looseness identification”, Energy Reports, 2021, 7, 842-849.
 
Journal of Civil and Environmental Engineering
Volume 53.4, Issue 113 - Serial Number 113
Winter of 2024
February 2024
Pages 53-64

Files

Share

How to cite

Statistics