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.

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.

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.

Detection of Incipient Damage in Large Rolling Element Bearings

2006 ◽  
Vol 13-14 ◽  
pp. 37-44 ◽  
Author(s):  
Leonard M. Rogers
Keyword(s):  
Acoustic Emission ◽  
The Body ◽  
Metal Loss ◽  
Rolling Element Bearings ◽  
Variable Speed ◽  
Fluid Turbulence ◽  
Rolling Element ◽  
Acoustic Emission Source ◽  
Reliable Detection ◽  
True Condition

The paper describes a methodology for the reliable detection of incipient damage due to fatigue, fretting and false brinelling in large, heavily loaded rolling element bearings such as found in pedestal slewing cranes and ship azi-pod propulsors. It has been found that combining acoustic emission source location and spectrum analysis of the associated time-domain signatures has produced a powerful diagnostic tool for the detection of micro-damage to the various working faces of the bearing under variable speed and loading conditions, before any metal loss is evident in the bearing lubricant. Other sources of acoustic emission such as fretting at contact faces elsewhere in the body of the bearing and fluid turbulence can be resolved and quantified so as not to interfere with the diagnosis of bearing condition. Results are presented for new and damaged bearings, where the true condition has been verified when the bearings were subsequently replaced.

Quality inspection of rolling element bearings using acoustic emission techniques

1994 ◽  
Vol 27 (4) ◽  
pp. 219
Author(s):  
V. Bansal ◽  
A. Prakash ◽  
V.A. Eshwar ◽  
B.C. Gupta
Keyword(s):  
Acoustic Emission ◽  
Quality Inspection ◽  
Rolling Element Bearings ◽  
Rolling Element

Fault Diagnosis Based on Acoustic Emission Signal for Low Speed Rolling Element Bearing

2011 ◽  
Vol 199-200 ◽  
pp. 1020-1023 ◽  
Author(s):  
Hua Qing Wang ◽  
Yong Wei Guo ◽  
Jian Feng Yang ◽  
Liu Yang Song ◽  
Jia Pan ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Fault Diagnosis ◽  
Acoustic Emission Signal ◽  
Rotating Machinery ◽  
Rolling Element Bearing ◽  
Low Speed ◽  
Rotating Speed ◽  
Emission Signal ◽  
Rolling Element ◽  
Element Bearing

The fault of a bearing may cause the breakdown of a rotating machine, leading to serious consequences. A rolling element bearing is an important part of, and is widely used in rotating machinery. Therefore, fault diagnosis of rolling bearings is important for guaranteeing production efficiency and plant safety. Although many studies have been carried out with the goal of achieving fault diagnosis of a bearing, most of these works were studied for rotating machinery with a high rotating speed rather than with a low rotating speed. Fault diagnosis for bearings under a low rotating speed, is more difficult than under a high rotating speed. Because bearing faults signal is very weak under a low rotating speed. This work acquires vibration and acoustic emission signals from the rolling bearing under low speed respectively, and analyzes the both kinds of signals in time domain and frequency domain for diagnosing the typical bearing faults contrastively. This paper also discussed the advantages using the acoustic emission signal for fault diagnosis of rolling speed bearing. From the results of analysis and experiment we can find the effectiveness of acoustic emission signal is better than vibration signal for fault diagnosis of a bearing under the low speed.

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