A De-Noising Method for Track State Detection Signal Based on the Statistical Characteristic of Noise

• 作者: Liming Li Shubin Zheng Wenfa Zhu Xiaodong Chai
• 来源期刊: 交通科技期刊(英文)
• 学科: 医学
• 关键词: TRACK Inspection LONG Wave IRREGULARITY Empirical Mode DECOMPOSITION DE-NOISING
• 年，卷（期）: 2014,（4）
• 页码范围: 327-336
• 页数: 10页
• 分类号: R73

摘要

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 autocorrelation function characteristics are used to determine the cut-off point of the dominant mode. This method was applied to test signals and the actual inertial unit signals;the experimental results show that the method can effectively remove the noise and better meet the precision requirement.