Defect Diagnosis for Rolling Element Bearings Using Acoustic Emission

2009 ◽  
Vol 131 (6) ◽  
Author(s):  
Yongyong He ◽  
Xinming Zhang ◽  
Michael I. Friswell
Keyword(s):  
Acoustic Emission ◽  
Condition Monitoring ◽  
Characteristic Frequency ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Complementary Method ◽  
Actual Characteristic ◽  
Rolling Element ◽  
Ae Signal ◽  
Short Time

Rolling element bearings are very common components in rotating machinery. Hence, condition monitoring and the detection of defects are very important for the normal and safe running of these machines. Vibration based techniques are well established for the condition monitoring of rolling element bearings, although they are not so effective in detecting incipient defects in the bearing. Acoustic emission (AE) is receiving increasing attention as a complementary method for condition monitoring of bearings as AE is very sensitive to incipient defects. This paper presents an experimental study to investigate the AE characteristics of bearing defect and validates the relationship between various AE parameters and the operational condition of rolling element bearings. To analyze the characteristic vibration frequency of the bearing using the AE signal, short-time rms and autocorrelation functions are integrated to extract the actual characteristic frequency. The AE signal is then analyzed using standard parameters of the signals to explore the source characteristics and sensitivity of typical rolling element bearing faults. The results demonstrate that the proposed method is very effective to extract the actual characteristic frequency of the bearing by AE signal. Furthermore the AE parameters are always sensitive to the running and fault conditions, which have a strong influence on the strain and deformation within the bearing material.

Experimental investigation on time-domain features in the diagnosis of rolling element bearings by acoustic emission

2021 ◽  
pp. 107754632110161
Author(s):  
Aref Aasi ◽  
Ramtin Tabatabaei ◽  
Erfan Aasi ◽  
Seyed Mohammad Jafari
Keyword(s):  
Acoustic Emission ◽  
Condition Monitoring ◽  
Time Domain ◽  
Central Moment ◽  
Rolling Element Bearings ◽  
Test Rig ◽  
Acoustic Emission Sensor ◽  
Outer Race ◽  
Common Time ◽  
Rolling Element

Inspired by previous achievements, different time-domain features for diagnosis of rolling element bearings are investigated in this study. An experimental test rig is prepared for condition monitoring of angular contact bearing by using an acoustic emission sensor for this purpose. The acoustic emission signals are acquired from defective bearing, and the sensor takes signals from defects on the inner or outer race of the bearing. By studying the literature works, different domains of features are classified, and the most common time-domain features are selected for condition monitoring. The considered features are calculated for obtained signals with different loadings, speeds, and sizes of defects on the inner and outer race of the bearing. Our results indicate that the clearance, sixth central moment, impulse, kurtosis, and crest factors are appropriate features for diagnosis purposes. Moreover, our results show that the clearance factor for small defects and sixth central moment for large defects are promising for defect diagnosis on rolling element bearings.

scholarly journals Automatic Condition Monitoring of Industrial Rolling-Element Bearings Using Motor’s Vibration and Current Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Zhenyu Yang
Keyword(s):  
Point Defect ◽  
Condition Monitoring ◽  
Single Point ◽  
Operating Conditions ◽  
Multiple Point ◽  
Rolling Element Bearings ◽  
Current Analysis ◽  
Rolling Element ◽  
High Frequency Resonance ◽  
Short Time

An automatic condition monitoring for a class of industrial rolling-element bearings is developed based on the vibration as well as stator current analysis. The considered fault scenarios include a single-point defect, multiple-point defects, and a type of distributed defect. Motivated by the potential commercialization, the developed system is promoted mainly using off-the-shelf techniques, that is, the high-frequency resonance technique with envelope detection and the average of short-time Fourier transform. In order to test the flexibility and robustness, the monitoring performance is extensively studied under diverse operating conditions: different sensor locations, motor speeds, loading conditions, and data samples from different time segments. The experimental results showed the powerful capability of vibration analysis in the bearing point defect fault diagnosis. The current analysis also showed a moderate capability in diagnosis of point defect faults depending on the type of fault, severity of the fault, and the operational condition. The temporal feature indicated a feasibility to detect generalized roughness fault. The practical issues, such as deviations of predicted characteristic frequencies, sideband effects, time-average of spectra, and selection of fault index and thresholds, are also discussed. The experimental work shows a huge potential to use some simple methods for successful diagnosis of industrial bearing systems.

Spalling Size Evaluation of Rolling Element Bearing Using Acoustic Emission

2013 ◽  
Vol 569-570 ◽  
pp. 497-504 ◽  
Author(s):  
An Bo Ming ◽  
Zhao Ye Qin ◽  
Wei Zhang ◽  
Fu Lei Chu
Keyword(s):  
Acoustic Emission ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Outer Race ◽  
Cepstrum Analysis ◽  
Rolling Element ◽  
Rolling Elements ◽  
Element Bearing ◽  
Envelope Spectrum ◽  
Size Evaluation

Spalling of the races or rolling elements is one of the most common faults in rolling element bearings. Exact estimation of the spall size is helpful to the life prediction for rolling element bearings. In this paper, the dual-impulsive phenomenon in the response of a spalled rolling element bearing is investigated experimentally, where the acoustic emission signals are utilized. A new method is proposed to estimate the spall size by extracting the envelope of harmonics of the ball passing frequency on the outer race from the squared envelope spectrum. Compared with the cepstrum analysis, the proposed procedure shows more powerful anti-noise ability in the fault size evaluation.

Approximate Entropy Analysis of the Acoustic Emission From Defects in Rolling Element Bearings

2012 ◽  
Vol 134 (6) ◽  
Author(s):  
Yongyong He ◽  
Xinming Zhang
Keyword(s):  
Acoustic Emission ◽  
Defect Detection ◽  
Approximate Entropy ◽  
Rolling Element Bearings ◽  
Effective Measure ◽  
Rotating Speed ◽  
Rolling Element ◽  
Feature Parameter ◽  
Ae Signal ◽  
Nonlinear Feature

This paper introduces approximate entropy (ApEn) to address a nonlinear feature parameter of acoustic emission (AE) signal for the defect detection of rolling element bearings. With respect to AE signal, parameter selection of ApEn calculation is investigated, and appropriate parameters are suggested. Finally, an experimental study is presented to investigate the influence of various running conditions, i.e., radial load, rotating speed and defect size, on ApEn calculation. The results demonstrate that ApEn provides an effective measure for AE analysis and can be used as an effective feature parameter of AE signal for the defect detection of rolling element bearings.

Monitoring the Lubrication Condition of Rolling Element Bearings Using the Acoustic Emission Technique

2006 ◽  
Author(s):  
Yibo Edward Fan ◽  
Zhanqun Shi ◽  
Georgina Harris ◽  
Fengshou Gu ◽  
Andrew Ball
Keyword(s):  
Acoustic Emission ◽  
Frequency Domain ◽  
Frequency Domain Analysis ◽  
Processing Technique ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Signal Processing Technique ◽  
Operational Life ◽  
Rolling Element ◽  
Lubrication Condition

Lubrication condition strongly influences the behaviour and operational life of a rolling element bearing. This paper presented an experimental investigation of rolling element bearings with no lubricant and with grease-lubricant containing contaminants using the acoustic emission (AE) technique. High frequency sampling and data streaming technology were applied in the measurement of AE, instead of traditionally measured AE parameters such as the counts, events, and peak amplitude of the signal etc. By processing the AE signals with frequency domain analysis technology, the no lubricant and containing contaminants conditions can be clearly discriminated. This result proved that the frequency domain AE signal processing technique is a suitable method for monitoring the lubrication condition in rolling element bearings.

An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission

2021 ◽  
Vol 113 (1-2) ◽  
pp. 585-603
Author(s):  
Wenderson N. Lopes ◽  
Pedro O. C. Junior ◽  
Paulo R. Aguiar ◽  
Felipe A. Alexandre ◽  
Fábio R. L. Dotto ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Fourier Transform ◽  
Condition Monitoring ◽  
Grinding Wheel ◽  
Short Time Fourier Transform ◽  
Short Time

Simultaneous Monitoring of Rolling-Element and Journal Bearings Using Analysis of Structure-Born Ultrasound Acoustic Emissions

2010 ◽  
Author(s):  
A. Albers ◽  
M. Dickerhof
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emissions ◽  
Piezoelectric Sensor ◽  
Journal Bearings ◽  
Rolling Element Bearings ◽  
Acoustic Emission Sensor ◽  
Outer Race ◽  
Rolling Element ◽  
Characteristic Values ◽  
Acoustic Emission Technology

The application of Acoustic Emission technology for monitoring rolling element or hydrodynamic plain bearings has been addressed by several authors in former times. Most of these investigations took place under idealized conditions, to allow the concentration on one single source of emission, typically recorded by means of a piezoelectric sensor. This can be achieved by either eliminating other sources in advance or taking measures to shield them out (e. g. by placing the acoustic emission sensor very close to the source of interest), so that in consequence only one source of structure-born sound is present in the signal. With a practical orientation this is often not possible. In point of fact, a multitude of potential sources of emission can be worth considering, unfortunately superimposing one another. The investigations reported in this paper are therefore focused on the simultaneous monitoring of both bearing types mentioned above. Only one piezoelectric acoustic emission sensor is utilized, which is placed rather far away from the monitored bearings. By derivation of characteristic values from the sensor signal, different simulated defects can be detected reliably: seeded defects in the inner and outer race of rolling element bearings as well as the occurrence of mixed friction in the sliding surface bearing due to interrupted lubricant inflow.

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