Fault Symptoms of Rolling Element Bearings Under Variable Operating Conditions: A Multi Domain Analysis

2012 ◽  
Author(s):  
P. Borghesani ◽  
R. Ricci ◽  
S. Chatterton ◽  
P. Pennacchi
Keyword(s):  
Digital Signal ◽  
Experimental Tests ◽  
Diagnostic Techniques ◽  
Operating Conditions ◽  
Small Scale ◽  
Rolling Element Bearings ◽  
Envelope Analysis ◽  
Spectral Kurtosis ◽  
Rolling Element ◽  
Variable Operating Conditions

Diagnostics of rolling element bearings have been traditionally developed for constant operating conditions, and sophisticated techniques, like Spectral Kurtosis or Envelope Analysis, have proven their effectiveness by means of experimental tests, mainly conducted in small-scale laboratory test-rigs. Algorithms have been developed for the digital signal processing of data collected at constant speed and bearing load, with a few exceptions, allowing only small fluctuations of these quantities. Owing to the spreading of condition based maintenance in many industrial fields, in the last years a need for more flexible algorithms emerged, asking for compatibility with highly variable operating conditions, such as acceleration/deceleration transients. This paper analyzes the problems related with significant speed and load variability, discussing in detail the effect that they have on bearing damage symptoms, and propose solutions to adapt existing algorithms to cope with this new challenge. In particular, the paper will i) discuss the implication of variable speed on the applicability of diagnostic techniques, ii) address quantitatively the effects of load on the characteristic frequencies of damaged bearings and iii) finally present a new approach for bearing diagnostics in variable conditions, based on envelope analysis. The research is based on experimental data obtained by using artificially damaged bearings installed on a full scale test-rig, equipped with actual train traction system and reproducing the operation on a real track, including all the environmental noise, owing to track irregularity and electrical disturbances of such a harsh application.

A NEW GEARBOX FAULT DIAGNOSIS METHOD BASED ON LUCY–RICHARDSON DECONVOLUTION

2015 ◽  
Vol 39 (3) ◽  
pp. 593-603
Author(s):  
Xinghui Zhang ◽  
Jianshe Kang ◽  
Hongzhi Teng ◽  
Jianmin Zhao
Keyword(s):  
Fault Diagnosis ◽  
Experimental Studies ◽  
Experimental Tests ◽  
Rolling Element Bearings ◽  
Envelope Analysis ◽  
Rolling Element ◽  
Negative Effect ◽  
Diagnosis Method ◽  
Good Identification ◽  
Incipient Fault Diagnosis

Gear and bearing faults are the main causes of gearbox failure. Till now, incipient fault diagnosis of these two components has been a problem and needs further research. In this context, it is found that Lucy–Richardson deconvolution (LRD) proved to be an excellent tool to enhance fault diagnosis in rolling element bearings and gears. LRD’s good identification capabilities of fault frequencies are presented which outperform envelope analysis. This is very critical for early fault diagnosis. The case studies were carried out to evaluate the effectiveness of the proposed method. The results of simulated and experimental studies show that LRD is efficient in alleviating the negative effect of noise and transmission path. The results of simulation and experimental tests demonstrated outperformance of LRD compared to classical envelope analysis for fault diagnosis in rolling element bearings and gears, especially when it is applied to the processing of signals with strong background noise.

scholarly journals New State Identification Method for Rotating Machinery under Variable Load Conditions Based on Hybrid Entropy Features and Joint Distribution Adaptation

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Xiaoming Xue ◽  
Nan Zhang ◽  
Suqun Cao ◽  
Wei Jiang ◽  
Jianzhong Zhou ◽  
...  
Keyword(s):  
Joint Distribution ◽  
Operating Conditions ◽  
Variable Load ◽  
Rolling Element Bearings ◽  
Time Frequency ◽  
Identification Method ◽  
State Identification ◽  
Rolling Element ◽  
Load Conditions ◽  
Testing Set

Fault identification under variable operating conditions is a task of great importance and challenge for equipment health management. However, when dealing with this kind of issue, traditional fault diagnosis methods based on the assumption of the distribution coherence of the training and testing set are no longer applicable. In this paper, a novel state identification method integrated by time-frequency decomposition, multi-information entropies, and joint distribution adaptation is proposed for rolling element bearings. At first, fast ensemble empirical mode decomposition was employed to decompose the vibration signals into a collection of intrinsic mode functions, aiming at obtaining the multiscale description of the original signals. Then, hybrid entropy features that can characterize the dynamic and complexity of time series in the local space, global space, and frequency domain were extracted from each intrinsic mode function. As for the training and testing set under different load conditions, all data was mapped into a reproducing space by joint distribution adaptation to reduce the distribution discrepancies between datasets, where the pseudolabels of the testing set and the final diagnostic results were obtained by the k-nearest neighbor algorithm. Finally, five cases with the training and testing set under variable load conditions were used to demonstrate the performance of the proposed method, and comparisons with some other diagnosis models combined with the same features and other dimensionality reduction methods were also discussed. The analysis results show that the proposed method can effectively recognize the multifaults of rolling element bearings under variable load conditions with higher accuracies and has sound practicability.

scholarly journals Diagnostics 101: A Tutorial for Fault Diagnostics of Rolling Element Bearing Using Envelope Analysis in MATLAB

2020 ◽  
Vol 10 (20) ◽  
pp. 7302
Author(s):  
Seokgoo Kim ◽  
Dawn An ◽  
Joo-Ho Choi
Keyword(s):  
Process Simulation ◽  
Rolling Element Bearing ◽  
Fault Identification ◽  
New Developments ◽  
Envelope Analysis ◽  
Practical Applications ◽  
Spectral Kurtosis ◽  
Rolling Element ◽  
Element Bearing ◽  
Simulation Signal

This paper presents a MATLAB-based tutorial to conduct fault diagnosis of a rolling element bearing. While there have been so many new developments in this field, no studies have addressed the tutorial aspects in this field to help the engineers learn the concept and implement by their own effort. The three most common techniques—the autoregressive model, spectral kurtosis, and envelope analysis—are selected to demonstrate the bearing diagnosis process. Simulation signal is introduced to help understand the characteristics of fault signal and carry out the process toward the fault identification. The techniques are then applied to the two real datasets to demonstrate the practical applications, one made by the authors and the other by the Case Western Reserve University, which is known as a standard reference in testing the diagnostic algorithms.

scholarly journals Rolling Element Bearing Fault Diagnosis Based on Multiscale General Fractal Features

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Weigang Wen ◽  
Zhaoyan Fan ◽  
Donald Karg ◽  
Weidong Cheng
Keyword(s):  
Fault Diagnosis ◽  
Fractal Dimensions ◽  
Feature Space ◽  
Operating Conditions ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Vibration Signals ◽  
Bearing Fault Diagnosis ◽  
Rolling Element ◽  
Element Bearing

Nonlinear characteristics are ubiquitous in the vibration signals produced by rolling element bearings. Fractal dimensions are effective tools to illustrate nonlinearity. This paper proposes a new approach based on Multiscale General Fractal Dimensions (MGFDs) to realize fault diagnosis of rolling element bearings, which are robust to the effects of variation in operating conditions. The vibration signals of bearing are analyzed to extract the general fractal dimensions in multiscales, which are in turn utilized to construct a feature space to identify fault pattern. Finally, bearing faults are revealed by pattern recognition. Case studies are carried out to evaluate the validity and accuracy of the approach. It is verified that this approach is effective for fault diagnosis of rolling element bearings under various operating conditions via experiment and data analysis.

A Stochastic Model for Simulation and Diagnostics of Rolling Element Bearings With Localized Faults

2003 ◽  
Vol 125 (3) ◽  
pp. 282-289 ◽  
Author(s):  
J. Antoni ◽  
R. B. Randall
Keyword(s):  
Spectral Characteristics ◽  
Vibration Signal ◽  
Spectral Signature ◽  
Rolling Element Bearings ◽  
Envelope Analysis ◽  
Analysis Technique ◽  
Proposed Model ◽  
Rolling Element ◽  
Excitation Force ◽  
Localized Faults

This paper addresses the stochastic modeling of the vibration signal produced by localized faults in rolling element bearings and its use for diagnostic purposes. The aim is essentially to provide a better understanding of the recognized “envelope analysis” technique as classically used in the diagnostics of rolling element bearings, and incidentally give theoretical proofs for the specific features of envelope spectra as obtained from experimental data. The proposed model may also prove useful for simulation purposes. First, the excitation force generated by a defect is modeled as a random point process and its spectral signature is derived analytically. Then its transmission through the bearing is investigated in detail in order to find the spectral characteristics of the resulting vibration signal. The analysis finally gives sound justification for “squared” envelope analysis and the type of spectral indicators that should be used with it.

A Finite Element Investigation of a Bearing/Cartridge Interface for a Fretting Corrosion Study

1985 ◽  
Vol 107 (2) ◽  
pp. 157-163 ◽  
Author(s):  
R. J. Stover ◽  
H. H. Mabie ◽  
M. J. Furey
Keyword(s):  
Finite Element ◽  
Boundary Conditions ◽  
Analytical Study ◽  
Experimental Tests ◽  
Tangential Direction ◽  
Rolling Element Bearings ◽  
Interface Conditions ◽  
Finite Element Technology ◽  
Rolling Element ◽  
Contact Pressures

The bearing/cartridge interfaces of a Ship Service Motor Generator Set (SSMG) were modeled by using finite element technology. The purpose of this analytical study was to verify the results of earlier experimental tests made on an actual SSMG unit. This research is part of a larger research project to examine the important parameters influencing the fretting of rolling element bearings. Models for the bearings at both ends of the unit were developed, and loads simulating the ball pass loads were applied to these models; the contact pressures, radial deformations, and relative displacements at the interface were calculated. The resulting data showed the interface conditions to be extremely complex with the contact pressures varying from zero to a maximum of 55.4 MPa (8030 psi) as the balls passed by. The maximum relative displacements occurred in the tangential direction (2.44 μm) and were independent of the axial boundary conditions.

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