Transmission tower bolt-loosening time–frequency analysis and localization method considering time-varying characteristics

Long Zhao, Guanru Wen, Jingyao Wang, Zhicheng Liu, Xinbo Huang
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Abstract

To address the issues of high concealment and difficult positioning of loose bolts in transmission towers, this paper proposes a new method for locating loose bolts in transmission towers. In this method, we divide the vibration response of the transmission tower into low-frequency signals of 2–25 Hz and high-frequency signals of 25–75 Hz. For the low-frequency signals, the single signal component is obtained by adaptive Chirp mode decomposition and uses the general demodulation transformation to deeply denoise the non-modal information. Since frequency characteristics themselves do not contain time information, considering the importance of time information for positioning, we propose a low-frequency time-varying frequency feature that preserves time characteristics based on synchronous wavelet transform and peak search. For the high-frequency signals, we use singular value decomposition to remove signal outliers caused by pulse excitation and eliminate forced vibrations through wavelet packet transform. Without altering its inherent characteristics, this method enables high-frequency time-domain signals to better represent the nonlinear characteristics of transmission towers. Furthermore, based on the powerful capabilities of Timesnet and Transformer in dealing with time series data, we propose a fault diagnosis model, which ultimately achieves the positioning of loose bolts in transmission towers. The bolt node model proves that this approach can better represent the loose bolt characteristics, and the transmission tower model verifies the effectiveness of this approach in locating loose bolts in transmission towers. Finally, bolt-loosening tests were conducted on a 110 kV transmission tower, and the accuracy of the positioning results reached 92.8%, demonstrating the effectiveness and efficiency of this method in practical positioning applications.
考虑时变特性的输电塔螺栓松动时频分析和定位方法
针对输电塔松动螺栓隐蔽性高、定位困难的问题,本文提出了一种新的输电塔松动螺栓定位方法。在该方法中,我们将输电塔的振动响应分为 2-25 Hz 的低频信号和 25-75 Hz 的高频信号。对于低频信号,通过自适应 Chirp 模式分解获得单一信号分量,并使用一般解调变换对非模式信息进行深度去噪。由于频率特性本身不包含时间信息,考虑到时间信息对定位的重要性,我们提出了基于同步小波变换和峰值搜索的低频时变频率特性,保留了时间特性。对于高频信号,我们采用奇异值分解法去除脉冲激励引起的信号异常值,并通过小波包变换消除强迫振动。在不改变其固有特性的前提下,这种方法能使高频时域信号更好地表现输电塔的非线性特性。此外,基于 Timesnet 和 Transformer 处理时间序列数据的强大功能,我们提出了一种故障诊断模型,最终实现了对输电塔松动螺栓的定位。螺栓节点模型证明这种方法能更好地表示松动螺栓的特征,输电塔模型则验证了这种方法在输电塔松动螺栓定位方面的有效性。最后,在 110 千伏输电塔上进行了螺栓松动试验,定位结果的准确率达到 92.8%,证明了该方法在实际定位应用中的有效性和高效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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