Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/5008
Title: Analysis And Simulation Of Bearing Fault Detection Using Fft Analyzer For Spherical Roller Bearing 22207Ek
Authors: Bhat, Sandeep
Keywords: Mechanical 2012
Project Report
Project Report 2012
Mechanical Project Report
12MMED
12MMED13
Design
Design 2012
Issue Date: 1-Jun-2014
Publisher: Institute of Technology
Series/Report no.: 12MMED13;
Abstract: Rolling elements bearing are most commonly yet very important component used in various machineries that support rotating elements . The reliable operations of the machinery depends on the healthy conditions of the bearing .The fault induction in the bearing will eventually cause the failure of the total system .The shafts used in the mechanical system like in textile machinery are overhung and have considerable unsupported spans. This configuration causes sagging of the shafts due to its own weight and its required to permit angular misalignment for proper functionality of the system. Spherical roller bearings are widely used for the cause like these . In the preset study of Spherical roller bearing ( Specification No.22207EK) has been taken for analysing its operational behaviour under various bearing faults in outer race.The bearing fault detection has been carried out from the vibration spectrum of the faulty bearing obtained by FFT analyzer with uniaxial accelerometer .To carry out the studies ,the experimental setup has been designed and fabricated .Defects on the defect free bearing has been generated intentionally using wirecut EDM process on Outer race to simulate the faulty conditions experimentally. The various frequency plots were obtained for lubricated as well as non lubricated bearings to understand the effect of lubrications on the vibration behaviour due to defects .The performance of the faulty bearing has been evaluated for various parameters like bearing load and rotational speed . The result obtained has been used to derive co-relations with various types of defect and the spectrum obtained for the same using Artificial neural network (ANN) technique.The simulation of the same has been carried out to predict the behaviour of any bearing under operations for its healthy conditions and unknown defects . The same results can be used as the benchmarks for predicting the unknown defects in the bearing used in various machines.
URI: http://hdl.handle.net/123456789/5008
Appears in Collections:Dissertation, ME (Design)

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