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个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:中国地震局工程力学研究所
学位:博士
所在单位:土木工程系
学科:结构工程. 防灾减灾工程及防护工程
Noise Smoothing for Structural Vibration Test Signals Using an Improved Wavelet Thresholding Technique
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论文类型:期刊论文
发表时间:2012-08-01
发表刊物:SENSORS
收录刊物:SCIE、PubMed、Scopus
卷号:12
期号:8
页面范围:11205-11220
ISSN号:1424-8220
关键字:vibration testing; wavelet transform (WT); denoise; wavelet thresholding; sigmoid function
摘要:In structural vibration tests, one of the main factors which disturb the reliability and accuracy of the results are the noise signals encountered. To overcome this deficiency, this paper presents a discrete wavelet transform (DWT) approach to denoise the measured signals. The denoising performance of DWT is discussed by several processing parameters, including the type of wavelet, decomposition level, thresholding method, and threshold selection rules. To overcome the disadvantages of the traditional hard- and soft-thresholding methods, an improved thresholding technique called the sigmoid function-based thresholding scheme is presented. The procedure is validated by using four benchmarks signals with three degrees of degradation as well as a real measured signal obtained from a three-story reinforced concrete scale model shaking table experiment. The performance of the proposed method is evaluated by computing the signal-to-noise ratio (SNR) and the root-mean-square error (RMSE) after denoising. Results reveal that the proposed method offers superior performance than the traditional methods no matter whether the signals have heavy or light noises embedded.