Abstract
The environment of the three-trans towers is complicated, with the influence of strong noise and non-deterministic interference, the features of the vibration response signal of bolts are very weak, which is difficult to identify the bolts’ state. In order to avoid man-made damage to the tower and realize the identification of bolt state under natural vibration conditions, a state identification method based on quadratic wavelet transform and KNN was proposed. First, the wavelet denoising method based on new threshold function was used to filter out the noise in original signal. Then, the dB10 wavelet function commonly used in fault diagnosis was selected to decompose and reconstruct the denoised signal, the dimensionless time domain characteristics of the low-frequency signal component and the information entropy of the high-frequency detail component were calculated respectively. Finally, the bolts state feature dataset was established. By comparing common classifiers, KNN with the best performance was selected. The experimental case analysis verified the effectiveness of the proposed method for bolts state identification. The overall research has certain practical and engineering value.
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