Aging Prediction of Composite Tower Based on FBG Sensing Technology
Li Shanshan1, Wang Linong1, Fang Yaqi1, Guo Zhenping2, Song Bin1
1. School of Electrical Engineering Wuhan University Wuhan 430072 China; 2. Jingzhou Power Supply Company of State Grid Hubei Electric Power Company Jingzhou 434007 China
Abstract:5 000 h multi-factor aging test data show that the cyclic loading of aging factor gave rise to certain rules of daily strain curve at each fiber monitoring sites, showing an overall shape of the two peaks and two valleys. The characteristic quantities KP1 (first local peak) gradually decreased with the aging process. In this paper, with the aid of Matlab software, the tendency of strain was predicted by using BP neural network and gray model, and priority was given to the TD21538 channel for its larger load. The results show that: take 60% KP1 as failure condition, the equivalent accelerated aging life of composite material tower is 9 500 h. As the consideration of extremely serious test condition, calculated life is far less than the actual service life, since the service life of composite material is much longer than the test time of 5 000 h, it shows high ageing-resistant performance of poly urethane composite material.
李姗姗, 王力农, 方雅琪, 郭真萍, 宋斌. 基于布拉格光纤光栅传感技术的复合材料杆塔老化寿命预测[J]. 电工技术学报, 2018, 33(1): 217-224.
Li Shanshan, Wang Linong, Fang Yaqi, Guo Zhenping, Song Bin. Aging Prediction of Composite Tower Based on FBG Sensing Technology. Transactions of China Electrotechnical Society, 2018, 33(1): 217-224.
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