A new model for rolling element bearing defect size estimation

Measurement ◽  
2018 ◽  
Vol 114 ◽  
pp. 144-149 ◽  
Author(s):  
Aoyu Chen ◽  
Thomas R. Kurfess
Keyword(s):  
Defect Size ◽  
Rolling Element Bearing ◽  
Size Estimation ◽  
New Model ◽  
Bearing Defect ◽  
Rolling Element ◽  
Element Bearing

scholarly journals Estimation of the Defect Width on the Outer Race of a Rolling Element Bearing under Time-Varying Speed Conditions

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Guang-Quan Hou ◽  
Chang-Myung Lee
Keyword(s):  
Research Work ◽  
Defect Size ◽  
Remaining Useful Life ◽  
Rolling Element Bearing ◽  
Time Varying ◽  
Entry And Exit ◽  
Outer Race ◽  
Time Frequency ◽  
Rolling Element ◽  
Element Bearing

Fault diagnosis and failure prognostics for rolling element bearing are helpful for preventing equipment failure and predicting the remaining useful life (RUL) to avoid catastrophic failure. Spall size is an important fault feature for RUL prediction, and most research work has focused on estimating the fault size under constant speed conditions. However, estimation of the defect width under time-varying speed conditions is still a challenge. In this paper, a method is proposed to solve this problem. To enhance the entry and exit events, the edited cepstrum is used to remove the determined components. The preprocessed signal is resampled from the time domain to the angular domain to eliminate the effect of speed variation and measure the defect size of a rolling element bearing on outer race. Next, the transient impulse components are extracted by local mean decomposition. The entry and exit points when the roller passes over the defect width on the outer race were identified by further processing the extracted signal with time-frequency analysis based on the continuous wavelet transform. The defect size can be calculated with the angle duration, which is measured from the identified entry and exit points. The proposed method was validated experimentally.

Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor

2013 ◽  
Vol 588 ◽  
pp. 333-342 ◽  
Author(s):  
Leon Swędrowski ◽  
Kazimierz Duzinkiewicz ◽  
Michał Grochowski ◽  
Tomasz Rutkowski
Keyword(s):  
Neural Networks ◽  
Induction Motor ◽  
Measurement Data ◽  
Failure Detection ◽  
Rolling Element Bearing ◽  
Bearing Defect ◽  
Instantaneous Current ◽  
Rolling Element ◽  
Current Change ◽  
Element Bearing

Bearing defect is statistically the most frequent cause of an induction motor fault. The research described in the paper utilized the phenomenon of the current change in the induction motor with bearing defect. Methods based on the analysis of the supplying current are particularly useful when it is impossible to install diagnostic devices directly on the motor. The presented method of rolling-element bearing diagnostics used indirect transformation, namely Clark transformation. It determines the vector of the spatial stator current based on instantaneous current measurements of the induction motor supply phases current. The analysis of the processed measurement data used multilayered, one-directional neural networks, which are particularly attractive due to their nonlinear structure and ability to learn. During the research 40 bearings: undamaged, with damages of three types and various degrees of fault extent, were used. The conducted research proves the efficiency of neural networks for detection and recognition of faults in induction motor bearings. In case of tests of the unknown state bearings, an efficiency approach to failure detection equaled 77%.

A fast and adaptive varying-scale morphological analysis method for rolling element bearing fault diagnosis

2012 ◽  
Vol 227 (6) ◽  
pp. 1362-1370 ◽  
Author(s):  
Changqing Shen ◽  
Qingbo He ◽  
Fanrang Kong ◽  
Peter W Tse
Keyword(s):  
Fault Diagnosis ◽  
Morphological Analysis ◽  
Rolling Element Bearing ◽  
Outer Race ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Bearing Defect ◽  
Rolling Element ◽  
Element Bearing ◽  
Fault Characteristic

The research in fault diagnosis for rolling element bearings has been attracting great interest in recent years. This is because bearings are frequently failed and the consequence could cause unexpected breakdown of machines. When a fault is occurring in a bearing, periodic impulses can be revealed in its generated vibration frequency spectrum. Different types of bearing faults will lead to impulses appearing at different periodic intervals. In order to extract the periodic impulses effectively, numerous techniques have been developed to reveal bearing fault characteristic frequencies. In this study, an adaptive varying-scale morphological analysis in time domain is proposed. This analysis can be applied to one-dimensional signal by defining different lengths of the structure elements based on the local peaks of the impulses. The analysis has been first validated by simulated impulses, and then by real bearing vibration signals embedded with faulty impulses caused by an inner race defect and an outer race defect. The results indicate that by using the proposed adaptive varying-scale morphological analysis, the cause of bearing defect could be accurately identified even the faulty impulses were partially covered by noise. Moreover, compared to other existing methods, the analysis can be functioned as an efficient faulty features extractor and performed in a very fast manner.

Rolling Element Bearing Defect Detection and Diagnostics Using Displacement Transducers

2001 ◽  
Author(s):  
John J. Yu ◽  
Donald E. Bently ◽  
Paul Goldman ◽  
Kenwood P. Dayton ◽  
Brandon G. Van Slyke
Keyword(s):  
Defect Detection ◽  
Amplitude Ratio ◽  
Spectral Characteristics ◽  
Rolling Element Bearing ◽  
Time Base ◽  
Outer Race ◽  
Bearing Defect ◽  
Rolling Element ◽  
Element Bearing ◽  
Displacement Transducers

This paper introduces the methodology of rolling element bearing defect detection using high-gain displacement transducers. The nature of defect influence on the outer race deflection in the vicinity of the transducer tip in time base has been established. Inner race, outer race, and rolling element (ball/roller) defects, which often occur sequentially, can be clearly identified according to spike signals on the time-varying outer race deflection curve along with known bearing frequencies. The developed techniques are fully corroborated by experimental data. Spike-to-deflection amplitude ratio, which is almost independent of changes in speed and load for a given defect, is used to judge the defect severity. Spectral characteristics due to these defects have also been found. It is shown that this direct measurement by using displacement transducers without casing influence, which would be inevitable by using accelerometers mounted on the casing, is a reliable approach to detect bearing defects as well as their severity and locations.

Rolling Element Bearing Defect Detection and Diagnostics Using Displacement Transducers

2002 ◽  
Vol 124 (3) ◽  
pp. 517-527 ◽  
Author(s):  
J. J. Yu ◽  
D. E. Bently ◽  
P. Goldman ◽  
K. P. Dayton ◽  
B. G. Van Slyke
Keyword(s):  
Defect Detection ◽  
Amplitude Ratio ◽  
Spectral Characteristics ◽  
Rolling Element Bearing ◽  
Time Base ◽  
Outer Race ◽  
Bearing Defect ◽  
Rolling Element ◽  
Element Bearing ◽  
Displacement Transducers

This paper introduces the methodology of rolling element bearing defect detection using high-gain displacement transducers. The nature of defect influence on the outer race deflection in the vicinity of the transducer tip in time base has been established. Inner race, outer race, and rolling element (ball/roller) defects, which often occur sequentially, can be clearly identified according to spike signals on the time-varying outer race deflection curve along with known bearing frequencies. The developed techniques are fully corroborated by experimental data. Spike-to-deflection amplitude ratio, which is almost independent of changes in speed and load for a given defect, is used to judge the defect severity. Spectral characteristics due to these defects have also been found. It is shown that this direct measurement by using displacement transducers without casing influence, which would be inevitable by using accelerometers mounted on the casing, is a reliable approach to detect bearing defects as well as their severity and locations.

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