condition monitoring of rolling contact bearing

Detection Of Roller Bearing DefectsBy Vibration Analysis

Presenting By:NASEEL IBNU AZEEZ M.PRoll No:12M-Tech MDAJCE-KANJIRAPALLY

Guided By:Mr.TOMS PHILIPAst. Professor Mechanical EngineeringAJCE-KANJIRAPALLY

BEARINGS

A bearing is a machine element that constrains relative motion between moving parts to only in the desired

motionThe term "bearing" is derived from the verb "to bear; a bearing being a

machine element that allows one part to bear (i.e., to support)

another.

Bearing

Sliding Contact Rolling Contact

Tapper Bearing Ball Bearing Cylindrical Bearing

Rolling Contact bearing carries a load by placing round elements between two bearing rings.The relative motion of the pieces causes the round elements to roll with very little rolling resistance and with little sliding.

Rolling Contact Bearings

Ball Bearing

Ball

Shaft

Outer Ring

Inner Ring

Bearing DefectsCauses Of Rolling Bearings Defects

Inappropriate use of bearingsFaulty installation or improper processingImproper lubricant, lubrication method or

sealing deviceInappropriate speed and operating

temperatureContamination by foreign matter during

installationAbnormally heavy load

Roller Bearing Defect Detection

Magnetic particle testing

Artificial visual detection

Eddy current testing

Optical detectionAcoustics & Vibration analysis

Vibration AnalysisCracks change the original vibration modal parameters of roller structure, so whether there are cracks defects in the roller can be distinguished by impulse response features.If there are cracks in the structure, theirs damping coefficient and stiffness will be changed, which will reflect on damping ratio and natural frequency. Damping ratio of the structure is increasing with the extension of the cracks, while natural frequency is reducing.

Condition Monitoring

Sensor(s) Cables Signal Conditioning

Data Acquisition & Storage Communications

Remote Analysis and Diagnostics

What to measure in vibration? Peak values of:1. Displacement2. Velocity3. AccelerationBeing related to each other, measurement of one leads to determination of the other two.

𝐷𝑖𝑠𝑝𝑙𝑎𝑐𝑒𝑚𝑒𝑛𝑡 (𝐴𝑚𝑝𝑙𝑖𝑡𝑢𝑑𝑒 )=𝐴𝑐𝑐𝑒𝑙𝑒𝑟𝑎𝑡𝑖𝑜𝑛(2𝜋 𝑓 )2

𝑉𝑒𝑙𝑜𝑐𝑖𝑡𝑦 (𝐴𝑚𝑝𝑙𝑖𝑡𝑢𝑑𝑒 )= 𝐴𝑐𝑐𝑒𝑙𝑒𝑟𝑎𝑡𝑖𝑜𝑛(2𝜋 𝑓 )

�̇�=∫ �̈� 𝑑𝑡𝑥=∬ �̈�=𝑑𝑡𝑑𝑡

Signal Processing

Input SamplingAnti-

aliasing Filter

A/D Convertor

Windows&

Input Buffer

FFT AveragingDisplay

&Storage

Signal processing is an area of systems engineering, electrical engineering and applied mathematics that deals with operations on or analysis of signals, or measurements of time-varying or spatially varying physical quantities. 

Digital Signal Processing(DSP)

SamplingIn signal processing, sampling is the reduction of a continuous signal to a discrete signal. A sample refers to a value or set of values at a point in time and/or space.A sampler is a subsystem or operation that extracts samples from a continuous signal.A theoretical ideal sampler produces samples equivalent to the instantaneous value of the continuous signal at the desired points.

s

𝑆𝑎𝑚𝑝𝑖𝑛𝑔 𝐹𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦 , 𝑓 𝑠=1𝑇 𝑠

𝑆𝑎𝑚𝑝𝑙𝑒𝑑 𝑓𝑢𝑛𝑐𝑡𝑖𝑜𝑛=𝑆 (𝑛𝑇 𝑠 ) ,𝐹𝑜𝑟 𝑖𝑛𝑡𝑒𝑔𝑒𝑟 valu n

Anti-aliasing Filter

Most sampled signals are not simply stored and reconstructed. But the fidelity of a theoretical reconstruction is a customary measure of the effectiveness of sampling. That fidelity is reduced when s(t) contains frequency components higher than is known as aliasing of signal.

Any signal bandlimited to maximum frequency can be perfectly reconstructed from its sample if the sample rate,(Nyquist rate)

Analog-to-digital converterAn analog-to-digital converter(ADC, A/D or A to D) is a device that converts a continuous physical quantity to a digital number that represents the quantity's amplitude. The result is a sequence of digital values that have converted a continuous-time and continuous-amplitude analog signal to a discrete-time and discrete amplitude digital signal.

Anti-aliasingfilter ADCx(t)

x [n]DSP

Signal Windowing Most digital signals are infinite, or sufficiently large that the dataset cannot be manipulated as a whole. Sufficiently large signals are also difficult to analyze statistically, because statistical calculations require all points to be available for analysis. In order to avoid these problems, engineers typically analyze small subsets of the total data, through a process called windowing

Fast Fourier Transform(FFT)This is a method of taking a real world,time-varying signal and splitting it into components, each with an amplitude, a phase, and a frequency. By associating the frequencies with machine characteristics, and looking at the amplitudes, it is possible to pinpoint troubles very accurately.

𝑥=𝐴1𝑒−ξ𝜔 𝑛𝑡 cos (√1−ξ2𝜔𝑛𝑡+𝜑1 )+ 𝑋 𝑠sin (𝜔𝑡−𝜑 )

√¿¿ ¿¿

AveragingSignal averaging is a signal processing technique applied in the time domain, intended to increase the strength of a signal relative to noise that is obscuring it.

Consider v(k) is the contaminated signal Mathematically, v(k) = vs(k) + vnoise(k),vs(k) being the desired periodic signalvnoise(k) the unwanted noiseSignal averaging is performed by accumulating and partitioning v(k), and adding the partitions with the hope that the noise adds destructively while the desired signal builds up.

Experimental Setup

Accelerometer Sensor

Sample Defect Is Shown as Red Spot

Outer Race

Inner Race

Bearing PitchDiameter (D)

Cage

Bearing Used in Test Motor (SKF 6306)

No. of Balls = n = 8Rotational Speed, N = 1480 rpmBall diameter, d = 12.3 mmBearing pitch dia, D = 50.8 mmBall contact angle =

Vibration Analysis

Time Domain Frequency Domain

Ampl

itude

Time

Ampl

itude

Frequency

FFT

Time Domain Analysis

Time Domain Zooming

Time Domain Splitting

𝟐𝐧𝐝𝐝𝐞𝐫𝐢𝐯𝐚𝐭𝐢𝐯𝐞

Frequency Domain Analysis

Characteristic Frequencies of Bearings

𝐹𝐵𝑃𝐹𝑂=𝑛𝑏2𝑁60 [1− 𝑑𝐷 cos 𝛽 ] 𝐹𝐵𝑆𝐹=

𝐷𝑑𝑁60⌈ 1−( 𝑑𝐷 )

2

cos𝛽 ⌉

𝐹𝐵𝑃𝐹𝐼=𝑛𝑏2⌈ 1+ 𝑑𝐷 cos 𝛽 ⌉ 𝐹𝐹𝑇𝐹=

12𝑁60 ⌈ 1− 𝐷𝑑 cos𝛽⌉

𝐹𝐵𝑃𝐹𝑂=Ball   passing   frequency   outer   race

𝐹𝐵𝑃𝐹𝐼=B all   passing   frequency   inner   race

𝐹𝐵𝑆𝐹=Ball   spin  frequency

𝐹𝐹𝑇𝐹=F undamental   train   frequency

n = no. of ballsN = rotational speed in rpmd=ball diameterD=bearing pitch diameter=ball contact angle with the races

Characteristic Frequencies For SKF-6306

=74.77 Hz=122.55 Hz=47.95 Hz=9.3 Hz

No. of Balls,n=8Rotational Speed,N = 1480rpmBall diameter,d =12.3 mmBearing pitch dia,D=50.8 mmBall contact angle=

Positioning Of Bearing Defect

Conclusions Trend of overall frequencies and vibration spectrum provide useful

information to analyze defects in roller bearings.

This technique can provide early information about progressing malfunctions.As a result, the necessary control action can be taken on the machine in advance.

The distinct and different behavior of vibration signals from bearings with inner race defect and outer race defect helps in identifying the defects in roller bearings.

Reference Prediction of Defects in Roller Bearings Using Vibration Signal Analysis H.MohamadiMonavar,H.AhmadiandS.S.MohtasebiWorld Applied Sciences Journal 4 (1): 150-154, 2008 ISSN18184952,IDOSI Publications,2008 Vibration Analysis using Time Domain Methods for the Detection of small Roller

Bearing Defects TahsinDoguer,JensStrackeljan SIRM 2009 - 8th International Conference on Vibrations in Rotating Machines,Vienna, Austria, 23 - 25 February 2009 Prediction of Defects in Antifriction Bearings using Vibration Signal AnalysisMAmarnath,RShrinidhi,ARamachandra,SBKandagal IE(I) Journal-MC Monitoring and Analysis of Vibration Signal Based On Virtual Instrumentation SunitaMohanta1,UmeshChandraPatiInternational Journal of Advanced Computer Research ISSN:2249-7277 ISSN:2277-7970) Volume-3 Number-1 Issue-8 March-2013

Reference Cont. Experimental Study on Condition Monitoring of Low Speed Bearings : Time Domain

Analysis EricY.Kim,AndyC.C.Tan,Bo-SukYangandVladisKosse5th Australasian Congress on Applied Mechanics, ACAM 2007 10-12 December 2007, Brisbane, Australia Text Books Mechanical Vibrations:Theory and Practice Author:Shrikant Bhave Publisher:Pearson Mechanical Vibrations Author:V P Singh Advanced Engineering Mathematics Author:Erwin Caryzig Publisher:Willey Digital Signal Processing Author:AAnandKumar Publisher:PHI Learning 

THANK YOU