TITLE

An Improved EMD Method for Time-Frequency Feature Extraction of Telemetry Vibration Signal Based on Multi-Scale Median Filtering

AUTHOR(S)
Li, Mei; Liu, Xueyong; Wu, Xiong
PUB. DATE
March 2015
SOURCE
Circuits, Systems & Signal Processing;Mar2015, Vol. 34 Issue 3, p815
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
We hereby propose an Empirical Mode Decomposition (EMD) method improved with a multi-scale median filtering for extraction of the time-frequency feature of telemetry vibration signals under interference from impulse noise. The signal is decomposed into a series of intrinsic mode functions (IMF) by EMD roughly. Median filtering is then performed on each IMF with filter window length varying with the IMF's frequency, respectively. This maneuver will allow effective impulse noise suppression with minimal loss of signal integrity. A new signal can then be reconstructed by adding up each component after the median filtering and treated with a repeat EMD to obtain new IMFs as a final result. This method overcomes the filtering window length selection problem in the median filtering, which can obtain better time-frequency feature extraction performance under the impulse noise interference condition. Data processing results from both a simulation signal and a telemetry vibration signal of a test showed the effectiveness of this method.
ACCESSION #
101148484

 

Related Articles

  • Non-stationary Signal Analysis Based on Hilbert-Huang Transform and Median Filter. Xiaoli Wang; Dianhong Wang // Advanced Materials Research;2014, Vol. 1049-1050, p1694 

    The Hilbert-Huang Transform (HHT) is a new time-frequency analysis with adaptability and orthogonality, but it is rather weak in terms of noise resistance, even low noise can disturb the HHT result greatly. The paper launches an investigation on how noises affect the HHT result and proposes the...

  • Research and Comparison of Time-frequency Techniques for Nonstationary Signals. Qiang Zhu; Yansong Wang; Gongqi Shen // Journal of Computers;Apr2012, Vol. 7 Issue 4, p954 

    Most of signals in engineering are nonstationary and time-varying. The Fourier transform as a traditional approach can only provide the feature information in frequency domain. The time-frequency techniques may give a comprehensive description of signals in time-frequency planes. Based on some...

  • Time-Frequency Fault Feature Extraction for Rolling Bearing Based on the Tensor Manifold Method. Fengtao Wang; Shouhai Chen; Jian Sun; Dawen Yan; Lei Wang; Lihua Zhang // Mathematical Problems in Engineering;2014, p1 

    Rolling-bearing faults can be effectively reflected using time-frequency characteristics. However, there are inevitable interference and redundancy components in the conventional time-frequency characteristics. Therefore, it is critical to extract the sensitive parameters that reflect the...

  • Application of EMD-AR and MTS for hydraulic pump fault diagnosis. Lu Chen; Hu Jiameng; Liu Hongmei // Journal of Vibroengineering;Jun2013, Vol. 15 Issue 2, p761 

    A real-time diagnosis of hydraulic pumps is very crucial for the reliable operation of hydraulic systems. The main purpose of this study is to propose a fault diagnosis approach for hydraulic systems based on the empirical mode decomposition (EMD), autoregressive (AR) model, singular value...

  • Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection. Wei Liu; Kai He; Qun Gao; Cheng-yin Liu // Journal of Applied Mathematics;2014, p1 

    Coal-gangue interface detection during top-coal caving mining is a challenging problem. This paper proposes a new vibration signal analysis approach to detecting the coal-gangue interface based on singular value decomposition (SVD) techniques and support vector machines (SVMs). Due to the...

  • Rolling Bearing Fault Diagnosis under Variable Conditions Using Hilbert-Huang Transform and Singular Value Decomposition. Hongmei Liu; Xuan Wang; Chen Lu // Mathematical Problems in Engineering;2014, p1 

    Fault diagnosis precision for rolling bearings under variable conditions has always been unsatisfactory. To solve this problem, a fault diagnosis method combining Hilbert-Huang transform(HHT), singular value decomposition (SVD), and Elman neural network is proposed in this paper. The method...

  • Nonlinear Vibration of Continuous Systems. Pellicano, Francesco; Strozzi, Matteo; Avramov, Konstantin V. // Shock & Vibration;6/20/2019, p1 

    Highlights from the article: Continuous systems, such as beams, membranes, plates, shells, and other structural/mechanical components, represent fundamental elements of mechanical systems in any field of engineering: Aerospace, Aeronautics, Automation, Automotive, Civil, Nuclear, Petroleum, and...

  • An approach to health assessment for tools in milling machine. Bei Jikun; Lu Chen; Wang Zhipeng; Wang Zili // Journal of Vibroengineering;Jun2013, Vol. 15 Issue 2, p773 

    Tool health is identified as the most significant index of the machining process, which directly influences the surface quality of work-piece. An online health monitoring for tools has become more crucial in manufacturing industries. In this study, a health assessment approach for tools in...

  • Improved Empirical Wavelet Transform for Compound Weak Bearing Fault Diagnosis with Acoustic Signals. Chaoren Qin; Dongdong Wang; Zhi Xu; Gang Tang // Applied Sciences (2076-3417);1/15/2020, Vol. 10 Issue 2, p1 

    Most of the current research on the diagnosis of rolling bearing faults is based on vibration signals. However, the location and number of sensors are often limited in some special cases. Thus, a small number of non-contact microphone sensors are a suboptimal choice, but it will result in some...

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics