摘要
针对现有导线振动监测以秒平均振幅和秒平均频率衡量导线微风振动程度带来的误差,提出了一种考虑振动特征瞬变的导线微风振动在线监测及预警技术。根据压电材料的正压电效应设计一种振动监测传感器,测量距悬垂线夹89 mm处的加速度时程曲线。以获得瞬时幅值和瞬时频率为目标,采用经验模态分解(empirical mode decomposition,EMD)结合相关性判断得到符合原始信号振动机制的特征模态函数(intrinsic mode function,IMF),经希尔伯特变换(hilbert transform,HT)提取瞬时参数,并利用瞬时幅值和瞬时频率计算导线对应动弯应力下各单元损伤参数,通过数值方法证明其有效性。经振动台试验对比分析,导线在有效损伤频段0~60 Hz内,该方法得出的各项疲劳损伤参数与计算值的吻合度均在86.77%以上,且主要疲劳损伤参数最大试验误差为8.02%,平均试验误差为0.92%,说明该方法可以作为振动导线疲劳寿命预警的有效依据。
In view of the errors caused by existing conductor vibration monitoring,which measures the conductor aeolian vibration with the average amplitude and frequency per second,this paper proposes an online monitoring and early warning technology for conductor aeolian vibration considering the transient characteristics of vibration.According to the positive piezoelectric effect of piezoelectric materials,a vibration monitoring sensor is designed to measure the acceleration time history curve of the point 89 mm away from the suspension clamp.In order to obtain the instantaneous amplitude and frequency,the intrinsic mode function(IMF)that conforms to the vibration mechanism of the original signals,is obtained using the empirical mode decomposition(EMD)combined with correlation judgment.The instantaneous parameters are extracted using Hilbert transform(HT),and the damage parameters of each element under dynamic bending stress are calculated using instantaneous amplitude and instantaneous frequency.The effectiveness of the proposed method is validated through numerical analysis.A comparative analysis is conducted with vibrating table test,and the results indicate that within the conductor’s effective damage frequency range of 0~60 Hz,the coincidence degree between the fatigue damage parameters obtained by test and the calculated values is more than 86.77%,and the maximum testing error of the main fatigue damage parameters ni is 8.02%and the average testing error is 0.92%.The comparative analysis shows that the proposed method could provide an effective warning basis for the fatigue life of vibrating conductors.
作者
赵隆
郭玉龙
郑天堂
曹雯
ZHAO Long;GUO Yulong;ZHENG Tiantang;CAO Wen(School of Electronic Information,Xi'an University of Technology,Xi'an 710048,China)
出处
《中国电力》
CSCD
北大核心
2021年第9期34-44,共11页
Electric Power
基金
国家自然科学基金资助项目(51707141)
陕西省重点研发计划一般资助项目(2021GY-068)
陕西省重点研发计划重点资助项目(2018ZDXM-GY-040)
陕西省自然科学基础研究计划资助项目(2019JQ-843)。