scholarly journals Performance of Envelope Demodulation for Bearing Damage Detection on CWRU Accelerometric Data: Kurtogram and Traditional Indicators vs. Targeted a Posteriori Band Indicators

2021 ◽  
Vol 11 (14) ◽  
pp. 6262
Author(s):  
Daga Alessandro Paolo ◽  
Garibaldi Luigi ◽  
Fasana Alessandro ◽  
Marchesiello Stefano
Keyword(s):  
Search Space ◽  
Spectral Lines ◽  
Center Frequency ◽  
Signal Spectrum ◽  
Test Case ◽  
Band Size ◽  
Rolling Element ◽  
Non Gaussian ◽  
Envelope Spectrum ◽  
Bearing Damage

Envelope demodulation of vibration signals is surely one of the most successful methods of analysis for highlighting diagnostic information of rolling element bearings incipient faults. From a mathematical perspective, the selection of a proper demodulation band can be regarded as an optimization problem involving a utility function to assess the demodulation performance in a particular band and a scheme to move within the search space of all the possible frequency bands {f, Δf} (center frequency and band size) towards the optimal one. In most of cases, kurtosis-based indices are used to select the proper demodulation band. Nevertheless, to overcome the lack of robustness to non-Gaussian noise, different utility functions can be found in the literature. One of these is the kurtosis of the unbiased autocorrelation of the squared envelope of the filtered signal found in the autogram. These heuristics are usually sufficient to highlight the defect spectral lines in the demodulated signal spectrum (i.e., usually the squared envelope spectrum (SES)), enabling bearings diagnostics. Nevertheless, it is not always the case. In this work, then, posteriori band indicators based on SES defect spectral lines are proposed to assess the general envelope demodulation performance and the goodness of traditional indicators. The Case Western Reserve University bearing dataset is used as a test case.

Optimal Frequency Band Selection for the Square Envelope Spectrum in the Diagnostics of Rolling Element Bearings

2014 ◽  
Author(s):  
S. Chatterton ◽  
P. Borghesani ◽  
P. Pennacchi ◽  
A. Vania
Keyword(s):  
Frequency Band ◽  
Vibration Signal ◽  
Band Selection ◽  
Rolling Element Bearings ◽  
Optimal Frequency ◽  
Simple Method ◽  
Rolling Element ◽  
Envelope Spectrum ◽  
Bearing Damage ◽  
Selection Of

Diagnostics of rolling element bearings is usually performed by means of a second-order cyclostationary tool applied to the vibration signal, due to the stochastic nature of the contact between the defect and the bearing rolling elements. The most used and simple method is the Envelope Analysis that is based on the identification of bearing damage frequency components in the so-called Square Envelope Spectrum. The main critical point of this technique is the selection of a suitable frequency band for the demodulation of the vibration signal. The most used approach for the frequency band selection is based on the evaluation of the band-Kurtosis index by mean of diagrams as the frequently used Fast Kurtogram or the more recent Protrugram. Both of them may fail in the selection of the optimal frequency band when other vibration sources affect the Kurtosis index. Also critical is the constancy in the time of this optimal band. In the paper, an experimental case of a bearing damage is investigated and an alternative approach for the filter band selection, the so-called “PeaksMap”, will be proposed by the authors and compared with the ones available in the literature.

scholarly journals Multi-objective Informative Frequency Band Selection Based on Negentropy-induced Grey Wolf Optimizer for Fault Diagnosis of Rolling Element Bearings

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1845 ◽  
Author(s):  
Xiaohui Gu ◽  
Shaopu Yang ◽  
Yongqiang Liu ◽  
Rujiang Hao ◽  
Zechao Liu
Keyword(s):  
Frequency Band ◽  
Background Noise ◽  
Grey Wolf Optimizer ◽  
Data Sets ◽  
Rolling Element Bearings ◽  
Grey Wolf ◽  
Objective Functions ◽  
Multi Objective ◽  
Rolling Element ◽  
Envelope Spectrum

Informative frequency band (IFB) selection is a challenging task in envelope analysis for the localized fault detection of rolling element bearings. In previous studies, it was often conducted with a single indicator, such as kurtosis, etc., to guide the automatic selection. However, in some cases, it is difficult for that to fully depict and balance the fault characters from impulsiveness and cyclostationarity of the repetitive transients. To solve this problem, a novel negentropy-induced multi-objective optimized wavelet filter is proposed in this paper. The wavelet parameters are determined by a grey wolf optimizer with two independent objective functions i.e., maximizing the negentropy of squared envelope and squared envelope spectrum to capture impulsiveness and cyclostationarity, respectively. Subsequently, the average negentropy is utilized in identifying the IFB from the obtained Pareto set, which are non-dominated by other solutions to balance the impulsive and cyclostationary features and eliminate the background noise. Two cases of real vibration signals with slight bearing faults are applied in order to evaluate the performance of the proposed methodology, and the results demonstrate its effectiveness over some fast and optimal filtering methods. In addition, its stability in tracking the IFB is also tested by a case of condition monitoring data sets.

Analysis of low damping ratios in multi-exciter stationary non-Gaussian random vibration control

2020 ◽  
Vol 26 (17-18) ◽  
pp. 1463-1470 ◽  
Author(s):  
Ronghui Zheng ◽  
Huaihai Chen ◽  
Min Qin ◽  
Andrea Angeli ◽  
Dirk Vandepitte
Keyword(s):  
Vibration Control ◽  
Random Vibration ◽  
Response Spectra ◽  
Spectral Lines ◽  
Control Algorithms ◽  
Calculation Error ◽  
Spectral Matrix ◽  
At Resonance ◽  
Input Signals ◽  
Non Gaussian

This article investigates the influence of low damping ratios on the performance of the multi-exciter stationary non-Gaussian random vibration control system. The basic theory of the multi-exciter stationary non-Gaussian random vibration method is reviewed first, and then the influences of low damping ratios on multi-output spectra and kurtoses are analyzed. The low damping ratios cause an ill-conditioned problem which will make the drive spectral matrix solution inaccurate; thus, some spectral lines located at resonance peaks in the response spectra cannot be modified within the preset tolerances by the control algorithms. The regularization method is used to alleviate the calculation error. The output kurtoses are dependent not only on the characteristics of the system but also on the input signals. It is found that the kurtosis control will be intractable if the damping ratios are very low. A two-input two-output cantilever beam simulation example is described to illustrate the analysis results.

Rolling Element Defect Diagnosis Based on Local Mean Decomposition

2011 ◽  
Vol 117-119 ◽  
pp. 33-37 ◽  
Author(s):  
Tian He ◽  
Xian Dong Liu ◽  
Ying Chun Shan ◽  
Qiang Pan
Keyword(s):  
Fourier Transform ◽  
Amplitude Modulation ◽  
Simulation Analysis ◽  
Vibration Signals ◽  
Local Mean Decomposition ◽  
Spectrum Method ◽  
Rolling Element ◽  
Modulation Signal ◽  
Local Mean ◽  
Envelope Spectrum

A method to extract rolling element fault characteristics from fault signal, based on local mean decomposition (LMD) and Fourier transform (FT), is introduced in this study. The LMD’s characteristics are obtained by processing multi-component frequency and amplitude modulation signal, which are usually used to describe the bearing fault signals. Base on the simulation analysis, the envelope spectrum method called LMD-FT is presented to deal with the vibration signals of rolling balling bearing with element fault. The results show that the rolling element defect can be diagnosed by LMD-FT effectively

New Feature Extraction Method for the Detection of Defects in Rolling Element Bearings

2012 ◽  
Vol 134 (8) ◽  
Author(s):  
Ling Xiang ◽  
Aijun Hu
Keyword(s):  
Ensemble Empirical Mode Decomposition ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Intrinsic Mode Functions ◽  
Feature Extraction Method ◽  
Outer Race ◽  
Mode Decomposition ◽  
Rolling Element ◽  
Envelope Spectrum ◽  
Detection Of Defects

This paper proposes a new method based on ensemble empirical mode decomposition (EEMD) and kurtosis criterion for the detection of defects in rolling element bearings. Some intrinsic mode functions (IMFs) are presented to obtain symptom wave by EEMD. The different kurtosis of the intrinsic mode function is determined to select the envelope spectrum. The fault feature based on the IMF envelope spectrum whose kurtosis is the maximum is extracted, and fault patterns of roller bearings can be effectively differentiated. Practical examples of diagnosis for a rolling element bearing are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race and inner-race, can be effectively identified by the proposed method.

A PEAK ENERGY CRITERION (P. E.) FOR THE SELECTION OF RESONANCE BANDS IN COMPLEX SHIFTED MORLET WAVELET (CSMW) BASED DEMODULATION OF DEFECTIVE ROLLING ELEMENT BEARINGS VIBRATION RESPONSE

2009 ◽  
Vol 07 (04) ◽  
pp. 387-410 ◽  
Author(s):  
KONSTANTINOS C. GRYLLIAS ◽  
IOANNIS ANTONIADIS
Keyword(s):  
Energy Criterion ◽  
Vibration Response ◽  
Frequency Resolution ◽  
Center Frequency ◽  
Index Number ◽  
Rolling Element Bearings ◽  
Time Frequency ◽  
Peak Energy ◽  
Rolling Element ◽  
Selection Of

Complex Shifted Morlet Wavelets (CSMW) present a number of advantages when used for the demodulation of the vibration response of defective rolling element bearings: (A) They present the optimally located window simultaneously in the time and in the frequency domains; (B) They allow for the maximal time-frequency resolution; (C) The magnitudes of the complex wavelet coefficients in the time domain lead directly to the required envelope; (D) They allow for the optimal selection of both the center frequency and the bandwidth of the requested filter. A Peak Energy criterion (P. E.) is proposed in this paper for the simultaneous automatic selection of both the center frequency and the bandwidth of the relevant wavelet window to be used. As shown in a number of application cases, this criterion presents a more effective behavior than other criteria used (Crest Factor, Kurtosis, Smoothness Index, Number of Peaks), since it combines the advantages of energy based criteria, with criteria characterizing the spikiness of the response.

scholarly journals Demodulation of Vibration Signal Based on Envelope-Kurtogram for Ball Bearing Fault Detection

2020 ◽  
Vol 4 (2) ◽  
pp. 115-123
Author(s):  
Berli Paripurna Kamiel
Keyword(s):  
Ball Bearing ◽  
Vibration Signal ◽  
Rolling Element Bearings ◽  
Central Frequency ◽  
Value Analysis ◽  
Bearing Fault ◽  
Bearing Defect ◽  
Rolling Element ◽  
Signal Demodulation ◽  
Envelope Spectrum

Rolling element bearings often suffer damage due to harsh operating and environmental conditions. The method commonly used in detecting faults in a bearing is envelope analysis. However, this method requires setting the central frequency and the correct bandwidth - which corresponds to the resonance frequency of the bearing - for signal demodulation to be effective. This study proposes a kurtogram to determine the correct central frequency and bandwidth to obtain the frequency band with the highest impulse content or the highest kurtosis value. Analysis envelope is applied to the filtered vibration signal using the central frequency and bandwidth parameters obtained from the kurtogram. The results showed that the envelope-kurtogram method is effective for faulty bearing detection as shown in the envelope spectrum where the peaks coincide with the bearing defect characteristic frequency (BPFO) with high accuracy. Likewise, it can be observed several BPFO harmonics which provide information on the level of bearing fault.

scholarly journals Development of damage detection parameters over the lifetime of a rolling element bearing

2021 ◽  
Vol 38 (3−4) ◽  
Author(s):  
Matti Savolainen ◽  
Arto Lehtovaara
Keyword(s):  
Acoustic Emission ◽  
Damage Detection ◽  
Impact Load ◽  
Load Condition ◽  
Constant Load ◽  
Rolling Element Bearing ◽  
Emission Data ◽  
Rolling Element ◽  
Element Bearing ◽  
Bearing Damage

This paper presents the trends of damage detection parameters over the lifetime of a rolling element bearing. In the experimental part, a series of bearing tests was performed using the twin-disc test device, until the monitored bearing was severely worn. This was followed by the analysis of measured acceleration and acoustic emission data in a constant-load condition, but also as loaded with impact-type loading. The results showed that traditionally used parameters, such as kurtosis and RMS, can indicate whether the bearing is damaged or not in a non-impact load condition. However, especially under impact-loading, the parameters based on acoustic emission data showed good performance and enabled monitoring of progress of the bearing damage.

Envelope pre-processing techniques for rolling element bearing diagnosis in variable speed conditions

2016 ◽  
Vol 6 (2) ◽  
pp. 27-32
Author(s):  
D Abboud ◽  
M Eltabach ◽  
J Antoni ◽  
S Sieg-Zieba
Keyword(s):  
Rolling Element Bearing ◽  
Rotating Machine ◽  
Order Tracking ◽  
Processing Step ◽  
Rolling Element ◽  
Pros And Cons ◽  
Deterministic Components ◽  
Envelope Spectrum ◽  
Processing Techniques ◽  
Random Part

In rotating machine diagnosis, the squared envelope spectrum (SES) is one of the most efficient indicators of the presence of cyclostationarity, which is a typical symptom of damage in rolling element bearings. Similarly to other cyclostationary tools, the SES should be applied on the pure random part of the signal, otherwise spurious peaks may appear and hide the cyclostationary content. Therefore, conventional deterministic/random separation (DRS) techniques are usually used as a pre-processing step to suppress the deterministic (periodic) component. In speed-varying regimes, the SES is combined with computed order tracking to obtain an order-domain representation rather than a Hertzian one. Through being order tracked, the deterministic components undergo speed-dependent variations in their magnitude and phase, thus losing their periodicity. This necessarily invalidates the working assumption of conventional DRS techniques and, consequently, jeopardises the efficiency of the SES. Recently, some sophisticated pre-processing techniques have been proposed to deal with this issue, the most important of which are the improved synchronous average (ISA), the cepstrum pre-whitening (CPW) and the generalised synchronous average (GSA). This paper aims to provide a comparative study of these techniques by highlighting their pros and cons. The comparison is performed on real-world signals.

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