Identification of time-varying cable tension forces based on adaptive sparse time-frequency analysis of cable vibrations
Identification of time-varying cable tension forces based on adaptive sparse time-frequency analysis of cable vibrations
复制标题
基于索振动自适应稀疏时频分析的时变索拉力识别
DOI：
10.1002/stc.1889
复制
发表时间：
2017-03-01
影响因子：
5.4
通讯作者：
Hou, Thomas Y.
中科院分区：
文献类型：
--
作者：
Bao, Yuequan;Shi, Zuoqiang;Hou, Thomas Y.
对于斜拉桥来说，索力在其施工、评估和长期结构健康监测中起着至关重要的作用。斜拉索的张拉力随着移动车辆荷载和环境效应的变化而实时变化，这种连续变化的张拉力可能会导致拉索的疲劳损伤。传统的基于振动的索力估算方法只能得到时间平均的索力，而不能得到瞬时索力。提出了一种基于自适应稀疏时频分析的桥梁时变索力识别新方法。这是最近开发的一种方法，通过在最大可能的时频字典(即，扩展函数集)中寻找信号的最稀疏的时频表示来估计瞬时频率。在该方法中，首先从拉索的加速度测量中识别出时变的模态频率，然后根据该力与识别出的频率之间的关系得到时变的拉索索力。通过考虑不同模态频率与电缆基频的整数比，进一步改进了该算法，以增强其对测量噪声的鲁棒性。通过电缆实验验证了该方法的有效性。为了便于比较，还采用了希尔伯特-黄变换来识别时变频率，然后利用这些频率来计算时变索力。结果表明，自适应稀疏时频分析方法比希尔伯特-黄变换方法能更准确地估计时变索力。版权所有(C)2016 John Wiley&Sons，Ltd.
For cable bridges, the cable tension force plays a crucial role in their construction, assessment and long-term structural health monitoring. Cable tension forces vary in real time with the change of the moving vehicle loads and environmental effects, and this continual variation in tension force may cause fatigue damage of a cable. Traditional vibration-based cable tension force estimation methods can only obtain the time-averaged cable tension force and not the instantaneous force. This paper proposes a new approach to identify the time-varying cable tension forces of bridges based on an adaptive sparse time-frequency analysis method. This is a recently developed method to estimate the instantaneous frequency by looking for the sparsest time-frequency representation of the signal within the largest possible time-frequency dictionary (i.e. set of expansion functions). In the proposed approach, first, the time-varying modal frequencies are identified from acceleration measurements on the cable, then, the time-varying cable tension is obtained from the relation between this force and the identified frequencies. By considering the integer ratios of the different modal frequencies to the fundamental frequency of the cable, the proposed algorithm is further improved to increase its robustness to measurement noise. A cable experiment is implemented to illustrate the validity of the proposed method. For comparison, the Hilbert-Huang transform is also employed to identify the time-varying frequencies, which are then used to calculate the time-varying cable-tension force. The results show that the adaptive sparse time-frequency analysis method produces more accurate estimates of the time-varying cable tension forces than the Hilbert-Huang transform method. Copyright (C) 2016 John Wiley & Sons, Ltd.