Bearing Multiple Defects Detection Based on Envelope Detector Time Constant

2012 ◽  
Vol 135 (1) ◽  
Author(s):  
A. Mohammadi ◽  
M. S. Safizadeh
Keyword(s):  
Time Constant ◽  
Rolling Element Bearing ◽  
Multiple Faults ◽  
Outer Race ◽  
Multiple Defects ◽  
Envelope Detector ◽  
Bearing Defect ◽  
Defect Frequency ◽  
High Frequency Resonance ◽  
Bearing Damage

Rolling element bearing damage detection is one of the foremost concerns in rotating machinery. The difficulties in bearing defect diagnosis when the bearing has multiple defects increase, since unexpected changes occur in the amplitude of the bearing defect frequencies. In addition, the tendency toward condition-based maintenance (CBM) requires a better understanding of the fault progression due to the fact that multiple defects is one kind of fault development. In this paper, in order to detect multiple defects on one component of the bearing, a new method based on the high frequency resonance technique (HFRT) is introduced. The time constant in the envelope detector is used to find the pattern of the amplitude of defect frequency harmonics (ADFH) in the frequency domain. This method is based on a comparison of the ADFH with a curve, which is obtained from vibration modeling of the bearing. Two criteria are given for the diagnosis of multiple defects. The method is investigated with a simulation and a real experiment. Single and multiple defects are created on the outer race of the ball bearing at different angles. Additionally, the ADFH in the multiple faults experiments are calculated with the proposed mathematical modeling in order to check the accuracy of the model. The experimental results confirm the ability of the proposed method to diagnose multiple defects.

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.

Discrimination of Multiple Faults in Bearings Using Density-Based Orthogonal Functions of the Time Response

2017 ◽  
Author(s):  
T. Haj Mohamad ◽  
C. A. Kitio Kwuimy ◽  
C. Nataraj
Keyword(s):  
High Performance ◽  
Detection Efficiency ◽  
Time Response ◽  
Rolling Element Bearing ◽  
Orthogonal Functions ◽  
Multiple Faults ◽  
Outer Race ◽  
Vibration Data ◽  
Rolling Element ◽  
Inner Race

This study investigates the use of the mapped density of time response using orthogonal functions to detect single and multiple faults in rolling element bearings. The method is based on constructing the density of a single time response of the system by using orthogonal functions. The coefficients of the orthogonal functions create the feature vector in order to discriminate between different rolling element bearing faults. The method does not require preprocessing of the data, noise reduction, or feature selection. This method has been applied to vibration data of different bearing conditions at rotational speeds ranging from 300 rpm to 3000 rpm. These conditions include a healthy bearing, and bearings with defects in inner race, outer race, combination of inner race and outer race and rolling element. The results have shown remarkable detection efficiency in the case of a single and two bearing fault configurations. In general, for all bearing configurations, the approach has high performance in detecting defective conditions. These results indicate that using the mapped density to characterize the system under different conditions has considerable potential in bearing diagnostics.

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.

An approach to investigating rolling element bearing damage under impact loading

2021 ◽  
pp. 135065012110594
Author(s):  
Matti Savolainen ◽  
Arto Lehtovaara
Keyword(s):  
Impact Loading ◽  
Rolling Element Bearing ◽  
Acceleration Response ◽  
Test Device ◽  
Outer Race ◽  
Response Data ◽  
Rolling Element ◽  
Element Bearing ◽  
Bearing Damage ◽  
The Impact

This paper presents an approach to studying rolling element bearing damage under the interference of impact loading. In the experimental part, a series of bearing tests was performed by using the twin-disc test device with artificially damaged bearings. This was followed by analysis of the measured acceleration response data in impact-free condition as well as under the influence of the impact loading. The results showed successful detection of the bearing outer race damage by using typical bearing damage detection approaches regardless whether the impact loading was applied to the system or not. In turn, recognition of the bearing rolling element damage required specific signal processing.

A nonlinear dynamic vibration model of a defective bearing: the importance of modelling the angle of the leading and trailing edges of a defect

2020 ◽  
pp. 147592172096395
Author(s):  
Francesco Larizza ◽  
Carl Q Howard ◽  
Steven Grainger ◽  
Wenyi Wang
Keyword(s):  
Numerical Model ◽  
Surface Defects ◽  
Vibration Response ◽  
Rolling Element Bearing ◽  
Analytical Models ◽  
Bearing Defect ◽  
Defect Profile ◽  
Vibration Model ◽  
Trailing Edges ◽  
Rolling Element

Rolling element bearings eventually become worn and fail by developing surface defects, such as spalls, dents and pits. Previous researchers have tested bearings with defects that have sharp [Formula: see text] rectangular edges that were used to develop analytical models of a defective bearing. These models have limitations that require smooth surfaces and constant curvature of the bearing components; as well as assuming the defect profile. A method has been created to capture the surface topography of a bearing defect. A numerical model has been developed for a rolling element bearing that uses the measured defect profile and removes the limitations of models by previous researchers that use analytical expressions for contact area and force. The predicted vibration response of a bearing with a defect that has sloped leading and trailing edges on the outer and inner raceway was compared with experimental results. It was found that the new numerical model was able to predict the vibration response of a defective bearing. The defect topographies and the developed model have been made publicly available.

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.

Effect of Waviness on Vibration and Acoustic Features of Rolling Element Bearing

2012 ◽  
Author(s):  
Yimin Shao ◽  
Pei Wang ◽  
Zaigang Chen
Keyword(s):  
Dynamic Model ◽  
Computational Cost ◽  
Element Model ◽  
Mapping Method ◽  
Rolling Element Bearing ◽  
Acoustic Features ◽  
Rigid Displacement ◽  
Outer Race ◽  
Deep Groove ◽  
Rolling Element

Waviness of rolling element bearings, as one of the most concerned factors, would greatly influence the dynamic and acoustic performances of machines. In this paper, a new algorithm of vibro-acoustic coupling, which is based on the displacement mapping method by applying the displacement history obtained from a 6-DOF bearing dynamic model to be as the boundary condition of the finite element model of the bearing housing, is developed to predict the effect of waviness on the vibration and acoustic features of the bearing. The displacement excitation of the circumferential surface of bearing housing can be obtained by vector synthesis of bearing rigid displacement from the 6-DOF bearing dynamic model. This new method enables not only the reduction in computational cost, but also simulation of the bearing waviness under different sizes. A 6308 deep groove ball bearing model with outer race waviness is taken as an example case to examine the effectiveness of the new algorithm. The simulation results show that the new algorithm is able to predict the vibration and acoustic features of the bearing with waviness.

scholarly journals An Improved Method Based on CEEMD for Fault Diagnosis of Rolling Bearing

2014 ◽  
Vol 6 ◽  
pp. 676205 ◽  
Author(s):  
Meijiao Li ◽  
Huaqing Wang ◽  
Gang Tang ◽  
Hongfang Yuan ◽  
Yang Yang
Keyword(s):  
Fault Diagnosis ◽  
Empirical Mode Decomposition ◽  
Early Stage ◽  
Rolling Bearing ◽  
Ensemble Empirical Mode Decomposition ◽  
Rolling Element Bearing ◽  
Bearing Faults ◽  
Outer Race ◽  
Mode Decomposition ◽  
Acceleration Sensors

In order to improve the effectiveness for identifying rolling bearing faults at an early stage, the present paper proposed a method that combined the so-called complementary ensemble empirical mode decomposition (CEEMD) method with a correlation theory for fault diagnosis of rolling element bearing. The cross-correlation coefficient between the original signal and each intrinsic mode function (IMF) was calculated in order to reduce noise and select an effective IMF. Using the present method, a rolling bearing fault experiment with vibration signals measured by acceleration sensors was carried out, and bearing inner race and outer race defect at a varying rotating speed with different degrees of defect were analyzed. And the proposed method was compared with several algorithms of empirical mode decomposition (EMD) to verify its effectiveness. Experimental results showed that the proposed method was available for detecting the bearing faults and able to detect the fault at an early stage. It has higher computational efficiency and is capable of overcoming modal mixing and aliasing. Therefore, the proposed method is more suitable for rolling bearing diagnosis.

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