A Brief Review on Fault Diagnosis of Rotating Machineries

2014 ◽  
Vol 541-542 ◽  
pp. 635-640 ◽  
Author(s):  
S.P. Mogal ◽  
D.I. Lalwani

Vibration in any rotating machines is due to faults like misalignment, unbalance, crack, mechanical looseness etc. Identification of these faults in rotor systems, model and vibration signal based methods are used. Signal processing techniques such as Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), Wigner-Ville Distribution (WVD) and Wavelet Transform (WT) are applied to vibration data for faults identification. The intent of the paper is to present a review and summarize the recent research and developments performed in condition monitoring of rotor system with the purpose of rotor faults detection. In present paper discuss the different signal processing techniques applied for fault diagnosis. Vibration response measurement has given information concerning any fault within a rotating machine and many of the methods utilizing this technique are reviewed. A detail review of the subject of fault diagnosis in rotating machinery is presented.

2014 ◽  
Vol 592-594 ◽  
pp. 2091-2096
Author(s):  
H.N. Sharma ◽  
Santosh Verma

This work employs the wavelet transform for reading the fault diagnosis in a rotor-bearing system. Initiating with literature review with some relevant studies of bearing fault and the signal processing techniques used followed by the theory of wavelet transform. A bearing test rig is shown which is used for implementing wavelet transform. A faulty bearing vibration signal is measured from the test rig; thereafter the fast Fourier transform is plotted to show the critical frequencies, bearing characteristics frequency and its harmonics. A scalogram showing the energy levels of signal is plotted as result. Faulty signal is analyzed using wavelet transform.


2012 ◽  
Vol 1 (1) ◽  
pp. 35-46 ◽  
Author(s):  
Igor Vujović ◽  
Joško Šoda ◽  
Ivica Kuzmanić

Signal processing plays a pivotal role in information gathering and decision making. This paper presents and compares different signal processing techniques used in marine and navy applications, primarily based on using wavelets as kernel. The article covers Fourier transform, time frequency wavelet based techniques such as bandelets, contourlets, curvelets, edgelets, wedgelets, shapelets, and ridgelets. In the example section of the paper, several transform techniques are presented and commented on the harbour surveillance video stream example.


2009 ◽  
Vol 413-414 ◽  
pp. 175-180 ◽  
Author(s):  
Salem Al-Arbi ◽  
Feng Shou Gu ◽  
Lu Yang Guan ◽  
Andrew Ball ◽  
Abdelhamid Naid

In many cases, it is impractical to measure the vibrations directly at or close to their source. It is a common practice to measure the vibration at a location far from the source for condition monitoring purposes. The vibration measured in this way inevitably has high distortions from the vibrations due to the effect of the attenuation of signal paths and the interference from other sources. The suppression of the distortions is a key issue for the remote measurements based condition monitoring. In this paper, the influences of transducer locations are investigated on a typical gearbox transmission system for the detection of the faults induced to the gearbox. Several signal processing techniques’ analysis results show that the attenuation and interference cause high influences on the gear transmission signals. However, time synchronous average (TSA) is very effective to detect the local faults induced to the gear system.


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