Huan-Chieh Chiu and Hung-Shuo Wu and Chien-Hao Wang and Yu-Cheng Yang and Ching-Ya Tseng and Joe-Air Jiang
A Damage Level Assessment Model for Extra High Voltage Transmission Towers
585 - 590
2017
11
5
International Journal of Energy and Power Engineering
https://publications.waset.org/pdf/10007160
https://publications.waset.org/vol/125
World Academy of Science, Engineering and Technology
Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The ChiChi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10 of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of longterm evaluation of structural characteristics and longterm damage detection.
Open Science Index 125, 2017