@inproceedings{52fadf1debc242669e68932d18755f85,
title = "An exponential smoothing extension method for restraining the end effect of local mean decomposition",
abstract = "Characterized by the self-adaptive time-frequency, Local Mean Decomposition (LMD) is suitable for analyzing non-linear and non-stationary signals. With LMD method, vibration signals of roller bearings can be decomposed into a number of product functions and a residual trend. However, end effects are produced when performing the LMD method, which make the results distortion. After researching the restraining methods of end effects for Empirical Mode Decomposition (EMD) and LMD, a new exponential smoothing extension method was proposed. The basic idea of this method is that the time of extended point is symmetrical about the datum mark and the value is decided by the exponential smoothing model. By using this method, the extension waveform confirms to the trend of the original signal. The results of the simulated signals indicate that the new method can solve the end effects efficiently.",
author = "Jiali Pan and Minghong Han",
note = "Publisher Copyright: {\textcopyright} 2015 Taylor \& Francis Group, London.; 25th European Safety and Reliability Conference, ESREL 2015 ; Conference date: 07-09-2015 Through 10-09-2015",
year = "2015",
doi = "10.1201/b19094-318",
language = "英语",
isbn = "9781138028791",
series = "Safety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015",
publisher = "CRC Press/Balkema",
pages = "2433--2439",
editor = "Luca Podofillini and Bruno Sudret and Bo{\v z}idar Stojadinovi{\'c} and Enrico Zio and Wolfgang Kr{\"o}ger",
booktitle = "Safety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015",
}