A novel method for feature extraction using crossover characteristics of nonlinear data and its application to fault diagnosis of rotary machinery-Reference-Cited by-同舟云学术

A novel method for feature extraction using crossover characteristics of nonlinear data and its application to fault diagnosis of rotary machinery

Published:2014-10 Issue:1-2 Volume:48 Page:174-187
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Lin Jinshan,Chen Qian

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference51 articles.

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2. A review on empirical mode decomposition in fault diagnosis of rotating machinery;Lei;Mech. Syst. Signal Process.,2012

3. Prognostics and health management design for rotary machinery systems—reviews, methodology and applications;Lee;Mech. Syst. Signal Process.,2014

4. A new feature for monitoring the condition of gearboxes in non-stationary operating conditions;Bartelmus;Mech. Syst. Signal Process.,2009

5. Diagnostics of bearings in presence of strong operating conditions non-stationarity—A procedure of load-dependent features processing with application to wind turbine bearings;Zimroz;Mech. Syst. Signal Process.,2013

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