文章基本信息

标题：Vibration Based Gear Fault Diagnosis under Empirical Mode Decomposition and Power Spectrum Density Analysis
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作者：Muhammad Ammar Akram ; Shahab Khushnood ; Syeda Laraib Tariq 等
期刊名称：Advances in Science and Technology Research Journal
印刷版ISSN：2080-4075
电子版ISSN：2299-8624
出版年度：2019
卷号：13
期号：3
页码：192-200
DOI：10.12913/22998624/111663
语种：English
出版社：Society of Polish Mechanical Engineers and Technicians
摘要：Rotating machinery plays a signifcant role in industrial applications and covers a wide range of mechanical equipment. A vibration analysis using signal processing techniques is generally conducted for condition monitoring ofrotary machinery and engineering structures in order to prevent failure, reduce maintenance cost and to enhancethe reliability of the system. Empirical mode decomposition (EMD) is amongst the most substantial non-linear andnon-stationary signal processing techniques and it has been widely utilized for fault detection in rotary machinery.This paper presents the EMD, time waveform and power spectrum density (PSD) analysis for localized spur gearfault detection. Initially, the test model was developed for the vibration analysis of single tooth breakage of spurgear at diﬀerent RPMs and then specifc fault was introduced in driven gear under diﬀerent damage conditions.The data, recorded by means of a wireless tri-axial accelerometer, was then analyzed using EMD and PSD techniques and the results were plotted. The results depicted that EMD algorithms are found to be more functional thanthe ordinarily used PSD and time waveform techniques.
关键词：spur gears; tooth breakage; vibration amplitude; empirical mode decomposition; power spectrum density; time waveform