The application of spectral kurtosis on Acoustic Emission and vibrations from a defective bearing

Eftekharnejad, Babak; Carrasco, M.R.; Charnley, B.; Mba, David

doi:10.1016/j.ymssp.2010.06.010

Cited by 152 publications

(75 citation statements)

References 20 publications

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“…A value greater than 3 indicates peaks which are related to AE activities caused by defects in the signal. 13 However, false detections can occur when processing signals collected from wheel-bearings from in-service trains. These errors can be caused by impulses arising from random sources reducing the overall ability of TSK to detect bearing faults.…”

Section: Tskmentioning

confidence: 99%

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Wayside detection of faults in railway axle bearings using time spectral kurtosis analysis on high-frequency acoustic emission signals

Amini

Entezami

Huang

et al. 2016

Advances in Mechanical Engineering

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Typical railway wheelsets consist of wheels, axle and axle bearings. Faults can develop on any of the aforementioned components, but the most common are related to wheel and axle bearing defects. The continuous increase in train operating speeds means that failure of an axle bearing can lead to serious derailments, causing loss of life and severe disruption in the operation of the network, damage to the track and loss of confidence in rail transport by the general public. The rail industry has focused on the improvement of maintenance and remote condition monitoring of rolling stock to reduce the probability of failure as much as realistically possible. Current wayside systems such as hot axle box detectors and acoustic arrays may fail to detect defective bearings. This article discusses the results of wayside high-frequency acoustic emission measurements performed on freight rolling stock with artificially induced damage in axle bearings in Long Marston, UK. Time spectral kurtosis is applied for the analysis of the acoustic emission data. From the results obtained, it is evident that time spectral kurtosis is capable of distinguishing the axle bearing defects from the random noises produced by different sources such as the wheel-rail interaction, braking and changes in train speed.

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Section: Tskmentioning

confidence: 99%

“…15 To determine the SK, the signal is passed through a set of band-pass filters and then the kurtosis values of the filtered signals are calculated. 13 …”

Section: Tskmentioning

confidence: 99%

Wayside detection of faults in railway axle bearings using time spectral kurtosis analysis on high-frequency acoustic emission signals

Amini

Entezami

Huang

et al. 2016

Advances in Mechanical Engineering

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“…They demonstrated that the subsurface crack initiation and propagation can be detected by a time and frequency domain acoustic emission analysis. Eftekharnejad et al [11] compared the applicability of the acoustic emission and vibration methods in monitoring a naturally degraded roller bearing. They described that the acoustic emission method was more sensitive in diagnosing incipient faults than the vibration method.…”

Section: Introductionmentioning

confidence: 99%

An investigation of a detection method for a subsurface crack in the outer race of a cylindrical roller bearing

Liu¹,

Shi²,

Shao³

2017

EiN

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An investigAtion of A detection method for A subsurfAce crAck in the outer rAce of A cylindricAl roller beAring bAdAniA metody wykrywAniA pęknięć podpowierzchniowych w zewnętrznej bieżni łożyskA wAlcowego tic emission and vibration methods to detect the propagation initiation and propagation time of rolling contact fatigue cracks. They denoted that the subsurface cracks can be detected by the acoustic emission method. Mano et al. [25] investigated the relationship between the growth of rolling contact fatigue cracks and load distribution on the inner race of a radial rolling bearing using a new acoustic emission source location method. They represented that the fatigue crack at the early stage would occur in a narrow area. Choudhury and Tandon [7] studied changes in the acoustic emission signal for defects with different sizes on the inner race and a roller of a cylindrical roller bearing. They denoted that the ringdown counts of the acoustic emission signal can be used to detect the defect in bearing raceways. Price et al. [27] and Schwach and Guo [31] also used the acoustic emission method to detect a subsurface crack caused by rolling contact fatigue. They also indicated that the acoustic emission method can be used to detect the subsurface crack in the bearing. Elforjani and Mba [12] used a range of time and frequency domain analysis techniques to detect a IntroductionRoller bearings are one of key components in various rotating machines. As one of major failure modes of the roller bearings due to periodic contact forces and external impulse loads, subsurface cracks in the bearings can significantly affect their dynamic performances [18,29], and produce catastrophic failures in these machines. Detecting the subsurface cracks in the races of the bearings at an early stage enables timely maintenance works to extend the lifetime of the machine system. One of current detection methods is vibration-based damage detection based on changes in dynamic characteristics [6,13]. Therefore, it is helpful to investigate the subsurface crack detection method for early failure detection and diagnosis for maintenance purposes.Many crack detection methods for rolling element bearings have been numerically and experimentally studied [21,22,29]. For instance, Yoshioka and Fujiwara [32] and Yoshioka [33] used the acousLiu J, Shi Z, ShAo Y. An investigation of a detection method for a subsurface crack in the outer race of a cylindrical roller bearing. Eksploatacja i Niezawodnosc -Maintenance and Reliability 2017; 19 (2): 211-219, http://dx

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“…Babak Eftekharnejad et.at, studied the relation between acoustic emission and vibration methods for defect identification of naturally damaged bearing. In this Acoustic emission is more sensitive in detecting incipient damage in bearing [11]. Faris Elasha et al researched that the fault detection ability of the AE is based upon the elimination of noise and also in the identification of the higher impact energy frequency region [12].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Solid Contamination in Ball Bearing Through Acoustic Emission Signals

Sheriff¹,

Hariharan²,

Kannan³

2017

Archives of Metallurgy and Materials

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Acoustic emission is one of the effective techniques used for the condition monitoring of rolling element bearings. Contamination is one of the major reasons for bearing early failure due to presence of solid particle in lubricant grease. In most cases, outer race is stationary and the inner race is attached to the rotating assembly. The lubrication is very essential for the bearing to perform under various demanding conditions. The main aim of this project is to analyze the effect of contamination of lubricant by solid particles on the dynamic behavior of rolling bearing. Green sand at three concentration levels 5%, 15%, 25% and different particle sizes 75 μm, 106 μm and 150μm is used to contaminate the lubricant. Experimental tests have been performed for different load and speed condition in good and contaminated ball bearings lubricated with grease. The trends in the amount of AE waves affected by the contamination of the grease were determined. Acoustic emission signals were analyzed in terms of RMS, kurtosis, and peak-peak.

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The application of spectral kurtosis on Acoustic Emission and vibrations from a defective bearing

Cited by 152 publications

References 20 publications

Wayside detection of faults in railway axle bearings using time spectral kurtosis analysis on high-frequency acoustic emission signals

Wayside detection of faults in railway axle bearings using time spectral kurtosis analysis on high-frequency acoustic emission signals

An investigation of a detection method for a subsurface crack in the outer race of a cylindrical roller bearing

Analysis of Solid Contamination in Ball Bearing Through Acoustic Emission Signals

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