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.
Li Shanshan,Wang Linong,Fang Yaqi等. Aging Prediction of Composite Tower Based on FBG Sensing Technology[J]. Transactions of China Electrotechnical Society, 2018, 33(1): 217-224.
[1] 胡毅, 刘庭, 刘凯, 等. 110 kV输电线路复合材料杆塔特性试验研究[J]. 高电压技术, 2011, 37(4): 801-808. Hu Yi, Liu Ting, Liu Kai, et al. Experimental research on performance of composite materials pole of 110 kV transmission line[J]. High Voltage Engineering, 2011, 37(4): 801-808. [2] EN 61109-2008 架空线路用绝缘子.标称电压大于1 000 V的交流设备用复合绝缘子和耐张绝缘子.定义、试验方法和验收准则[S]. 2008. [3] Uno M, Tanaka K. Accelerated charge-discharge cycling test and cycle life prediction model for supercapacitors in alternative battery applications[J]. IEEE Transactions on Industrial Electronics, 2012, 59(12): 4704-4712. [4] Yin Pengcheng, Wang Chengdong. Life-prediction of accelerated life testing based on support vector machine[C]//2011 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), IEEE, Xi’an, 2011: 284-286. [5] Zhuang Q, Morshuis P H F, Chen X C, et al. Life prediction for epoxy resin insulated transformer windings through accelerated aging tests[C]//2010 10th IEEE International Conference on Solid Dielectrics (ICSD), IEEE, Potsdam, Germany, 2010: 1-4. [6] Yang Y H, Su Y F, Chiang K N. Acceleration factor analysis of aging test on gallium nitride (GaN)-based high power light-emitting diode (LED)[C]//2014 IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems, Orlando, Florida, 2014: 178-181. [7] Jahromi A N, El-Hag A H, Jayaram S H, et al. A neural network based method for leakage current prediction of polymeric insulators[J]. IEEE Transactions on Power Delivery, 2006, 21(1): 506-507. [8] 杜剑波, 魏玉宾, 刘统玉. 光纤传感技术在变压器状态检测中的应用研究[J]. 电力系统保护与控制, 2008, 36(23): 36-40. Du Jianbo, Wei Yubin, Liu Tongyu. Study of optical fiber sensor technology applying in state detecting of transformer[J]. Power System Protection and Control, 2008, 36(23): 36-40. [9] 陈强, 李庆民, 丛浩熹, 等. 基于多点分布式光纤光栅的GIS隔离开关触头温度在线监测技术[J]. 电工技术学报, 2015, 30(12): 298-306. Chen Qiang, Li Qingmin, Cong Haoxi, et al. On-line temperature monitoring for GIS disconnecting switch contacts based on multipoint-distributed fiber bragg grating[J]. Transactions of China Electrotechnical Society, 2015, 30(12): 298-306. [10] 罗云月, 孙志峰, 张文权. 电力电缆光纤传感监测系统多波长光源设计[J]. 电力系统保护与控制, 2011, 39(17):130-133, 138. Luo Yunyue, Sun Zhifeng, Zhang Wenquan. A design of multiwavelength light source used in fiber sensing monitoring system for power cable[J]. Power System Protection and Control, 2011, 39(17): 130-133, 138. [11] 吕安强, 李永倩, 李静, 等. 利用光纤应变判断光电复合海缆锚害程度的有限元分析法[J]. 电工技术学报, 2014, 29(11): 261-268. Lü Anqiang, Li Yongqian, Li Jing, et al. Finite element analysis for judging anchor damage degree of photoelectric composite submarine cable by optical fiber strain [J]. Transactions of China Electrotechnical Society, 2014, 29(11): 261-268. [12] 蒋建, 李成榕, 马国明, 等. 架空输电线路覆冰监测用FBG拉力传感器的研制[J]. 高电压技术, 2010, 36(12): 3028-3034. Jiang Jian, Li Chengrong, Ma Guoming, et al. Development of FBG tension sensor applied to ice monitoring of overhead transmission lines[J]. High Voltage Technology, 2010, 36(12): 3028-3034. [13] 何宁, 王平, 丁勇, 等. 分布式光纤传感技术应变测量试验研究[J]. 中国测试, 2011, 37(2): 92-96. He Ning, Wang Ping, Ding Yong, et al. Experimental study of distributed fiber optic sensing techniques for the measurement of strain[J]. China Measurement & Test, 2011, 37(2): 92-96. [14] 李成榕, 马国明. 光纤布喇格光栅传感器应用于电气设备监测的研究进展[J]. 中国电机工程学报, 2013, 33(12): 114-122. Li Chengrong, Ma Guoming. Research and development of fiber bragg grating monitoring in electrical engineering[J]. Proceedings of CSEE, 2013, 33(12): 114-122. [15] 李鹏, 郭裕强, 余峰, 等. 光纤传感器在智能复合材料中的应用[J]. 玻璃钢/复合材料, 2005(3): 49-52. Li Peng, Guo Yuqiang, Yu Feng, et al. Fiber-optic sensors in smart composite materials[J]. FRP/ Composites, 2005(3): 49-52. [16] 颜熹琳, 周筱雨, 温茂萍, 等. 多因素加速老化对硬质聚氨酯泡沫塑料压缩力学性能的影响研究[J]. 化工新型材料, 2012, 40(9): 56-58. Yan Xilin, Zhou Xiaoyu, Wen Maoping, et al. Study on the effect of multi-stress accelerated aging on compressive mechanical properties of rigid polyurethane foam[J]. New Chemical Materials, 2012, 40(9): 56-58. [17] 尤毅, 刘东, 于文鹏, 等. 考虑加速老化的变压器剩余寿命计算方法研究[J]. 华东电力, 2011, 39(2): 217-220. You Yi, Liu Dong, Yu Wenpeng, et al. Algorithm research on remnant life of power transformer considering accelerated aging[J]. East China Power, 2011, 39(2): 217-220. [18] 蔡苗, 杨道国, 钟礼君, 等. 基于BP神经网络的模塑封材料疲劳寿命预测[J]. 电子元件与材料, 2008, 27(3): 64-67. Cai Miao, Yang Daoguo, Zhong Lijun, et al. Prediction of fatigue life of packaging EMC material based on BP neural networks [J]. Electronic Components and Materials, 2008, 27(3): 64-67. [19] 刘冰. 基于BP神经网络的高压潜水电机绝缘寿命预测[D]. 合肥：合肥工业大学, 2012. [20] 闫楚良, 郝云霄, 刘克格. 基于遗传算法优化的BP神经网络的材料疲劳寿命预测[J]. 吉林大学学报(工学版), 2014, 44(6): 1710-1715. Yan Chuliang, Hao Yunxiao, Liu Kege. Fatigue life prediction of materials based on BP neural networks optimized by genetic algorithm[J]. Journal of Jilin University (Engineering Science), 2014, 44(6): 1710-1715. [21] 史丽萍, 汤家升, 王攀攀, 等. 采用最优小波树和改进BP神经网络的感应电动机定子故障诊断[J]. 电工技术学报, 2015, 30(24): 38-45. Shi Liping, Tang Jiasheng, Wang Panpan, et al. Stator fault diagnosis of induction motors using the optimal wavelet tree and improved BP neural network[J]. Transactions of China Electrotechnical Society, 2015, 30(24): 38-45. [22] 项可璐. 人工神经网络在橡胶材料耐磨性能和疲劳寿命预测中的应用[D]. 北京: 北京化工大学, 2013. [23] 周天春, 杨丽君, 廖瑞金, 等. 基于局部放电因子向量和BP神经网络的油纸绝缘老化状况诊断[J]. 电工技术学报, 2010, 25(10): 18-23. Zhou Tianchun, Yang Lijun, Liao Ruijin, et al. Diagnosis of aging condition in oil-paper insulation based on factor vectors of partial discharge and BP neural network[J]. Transactions of China Electrotechnical Society, 2010, 25(10): 18-23. [24] 王同旭, 马鸿雁, 聂沐晗. 电梯用永磁同步电机BP神经网络PID调速控制方法的研究[J]. 电工技术学报, 2015, 30(增刊1): 43-47. Wang Tongxu, Ma Hongyan, Nie Muhan. The research of PMSM BP neural network PID control in elevator [J]. Transactions of China Electrotechnical Society, 2015, 30(S1): 43-47. [25] 孙仲民, 何正友, 戴铭. 基于灰色预测的电力电缆老化过程预警仿真研究[J]. 电力系统保护与控制, 2012, 40(13): 55-60. Sun Zhongmin, He Zhengyou, Dai Ming. Simulation study on pre-alarm of power cable aging process based on grey prediction[J]. Power System Protection and Control, 2012, 40(13): 55-60.
2018, Vol. 33 
