人民黄河2025，Vol.47Issue(3)：130-134,5.DOI:10.3969/j.issn.1000-1379.2025.03.020
基于自适应小波包降噪的厂房动力特性识别方法
Method for Identifying Dynamic Characteristics of Powerhouses Based on Adaptive Wavelet Packet Denoising
摘要
Abstract
A dynamic characteristic identification method based on the Adaptive Wavelet Packet Denoising(AWPD)algorithm was proposed to address the vibration issue in hydraulic powerhouse structures.The AWPD algorithm was applied at the wavelet packet terminal node layer to estimate noise variance and assess the associated risk of the noise variance,enabling flexible selection of wavelet coefficient thresholds.The Hilbert transform was used to calculate the instantaneous frequency and instantaneous damping ratio,facilitating the identification of nat-ural frequencies from the de-noised response.The Confidence Index(CI)was employed to determine the validity of the identified natural fre-quencies.The effectiveness of the proposed method was validated using the case study of the Hekoucun Reservoir Hydraulic Powerhouse in Henan Province,and its identification accuracy was compared with that of the RDT-DWT-HT-CI and WPD-RDT-DWT-HT-CI methods,et al.The results show that the AWPD algorithm effectively analyzes and determines the noise characteristics of the time history signal,achieving reasonable de-noising of the vibration response in the hydraulic powerhouse.Compared to other methods,the dynamic characteristic identifi-cation method integrating the AWPD algorithm with CI exhibits the smallest absolute difference error and the highest identification accuracy.关键词
自适应小波包降噪/厂房振动/阈值/动力特性识别/河口村水库Key words
Adaptive Wavelet Packet Denoising/factory vibration/threshold/identification of dynamic characteristics/Hekoucun Reservoir分类
建筑与水利引用本文复制引用
赵玉宏,李乐晨,杨志超..基于自适应小波包降噪的厂房动力特性识别方法[J].人民黄河,2025,47(3):130-134,5.基金项目
中央高校基本科研业务费专项(B240201069) （B240201069）
河南省财政资金资助项目(824013516) （824013516）
