Scientific Research Publishing

Read  full  paper  at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=53726#.VNB3aCzQrzE Author(s)   Yu Zhang , Shen Wang , Songling Huang * , Wei Zhao Affiliation(s) State Key Lab of Power System, Department of Electrical Engineering, Tsinghua University, Beijing, China . ABSTRACT The dispersion and multiple modes characteristics which exist in the propagation of Lamb waves (LW) in metal plates make it extremely hard to analyze and recognize the detection echo signals of defects. As a newly developed time-frequency analysis method in recent years, Hilbert-Huang transform (HHT) is one of the powerful tools to analyze non-stationary signals. The experimental LW detecting system for single aluminum plate is setup in this work, and the LW detecting signals are analyzed by HHT. The overlapped LW detecting signals of different modes are recognized by the means of extracting flight time of intrinsic mode functions (IMFs) after Hil...

Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=50741#.VEm91VfHRK0 Author(s)    Liming Li , Xiaodong Chai , Shubin Zheng , Wenfa Zhu Affiliation(s) College of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China . ABSTRACT Based on the statistical characteristics analysis of random noise power and autocorrelation function, this paper proposes a de-noising method for track state detection signal by using Empirical Mode Decomposition (EMD). This method is used to noise reduction refactoring for the first Intrinsic Mode Function (IMF) component in accordance with the “random sort-accumulation-average-refactoring" order. Signal autocorrela...

Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=50365#.VDsy2lfHRK0 Author(s)   Liming Li , Xiaodong Chai , Shubin Zheng , Wenfa Zhu Affiliation(s) College of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China . ABSTRACT In the track irregularity detection, the acceleration signals of the inertial measurement unit (IMU) output which with low frequency components and noise, this paper studied a de-noising algorithm. Based on the criterion of consecutive mean square error, a de-noising method for IMU acceleration signals based on empirical mode decomposition (EMD) was proposed. This method can divide the intrinsic mode functions (IMFs) derived from EMD into signal dominant m...