Diagnostic of Rolling Element Bearings with Envelope Analysis in Non-Stationary Conditions

2013 ◽  
pp. 127-135 ◽  
Author(s):  
Pietro Borghesani ◽  
Roberto Ricci ◽  
Steven Chatterton ◽  
Paolo Pennacchi
Keyword(s):  
Rolling Element Bearings ◽  
Envelope Analysis ◽  
Rolling Element ◽  
Stationary Conditions

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.

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.

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.

scholarly journals A Novel Method of Frequency Band Selection for Squared Envelope Analysis for Fault Diagnosing of Rolling Element Bearings in a Locomotive Powertrain

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4344 ◽  
Author(s):  
Lang Xu ◽  
Steven Chatterton ◽  
Paolo Pennacchi
Keyword(s):  
Frequency Band ◽  
Modulation Frequency ◽  
New Method ◽  
Statistical Characteristics ◽  
Rolling Element Bearings ◽  
Optimal Frequency ◽  
Envelope Analysis ◽  
Vibration Data ◽  
Rolling Element ◽  
Envelope Spectrum

The development of diagnostics for rolling element bearings (REBs) in recent years makes it possible to detect faults in bearings in real-time. Squared envelope analysis (SEA), in which the statistical characteristics of the squared envelope (SE) or the squared envelope spectrum (SES) are analysed, is widely recognized as both an effective and the simplest method. The most critical step of SEA is to find an optimal frequency band that contains the maximum defect information. The most commonly used approaches for selecting the optimal frequency band are derived from measuring the kurtosis of the SE or the SES. However, most methods fail to cope with the interference of a single or a few impulses in the corresponding domain. A new method is proposed in this paper called “PMFSgram”, which just calculates the kurtosis of the SES in the range centred at the first two harmonics with a span of three times the modulation frequency rather than the entire SES of the band filtered signals. It is possible to avoid most of the interference from a small number of undesired impulses in the SES. PMFSgram uses several bandwidths from 1.5 times to 4.5 times the fault frequency and for each bandwidth has the same number of central frequencies. The frequency setting method is able to select an optimal frequency band containing most of the useful information with less noise. The performance of the new method is verified using synthesized signals and actual vibration data.

Incipient Faults Identification in Gearbox by Combining Kurtogram and Independent Component Analysis

2015 ◽  
Vol 764-765 ◽  
pp. 309-313 ◽  
Author(s):  
Yu Guo ◽  
Xing Wu ◽  
Jing Na ◽  
Rong Fong Fung
Keyword(s):  
Independent Component Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
Rolling Element Bearings ◽  
Detection Scheme ◽  
Characteristic Frequencies ◽  
Envelope Analysis ◽  
Analysis Scheme ◽  
Rolling Element ◽  
Incipient Faults

Envelope analysis is a popular incipient fault identification tool for rolling element bearings (REBs) and gears. However, in some harsh conditions where more than one fault of REBs and gears exists simultaneously in a gearbox. In general, only the characteristic frequencies of the stronger vibration can be exposed clearly, and the others may be missed by conventional envelope analysis. To address this issue, an incipient faults detection scheme combining the kurtogram and independent component analysis (ICA) for gearbox faults diagnosis is proposed in this paper. In the proposed scheme, multi-channel vibrations are acquired from the gearbox synchronously at first. Subsequently, the vibration envelopes from each channel are extracted by the novel fast kurtogram algorithm. Then, the independent component analysis algorithm is utilized to separate the envelopes. As a result, the independent envelope components corresponding to different sources are obtained. Finally, the characteristic frequencies of the incipient faults of rolling element bearings and/or gears in a gearbox can be clearly exposed in envelope spectral plots. An experiment on a gearbox test rig which has both a REB fault and a gear fault is conducted to compare the conventional envelope analysis scheme and the proposed scheme. Test results show that the proposed scheme is more effective to identify the incipient faults of REBs and gears simultaneously existing in a gearbox.

Sign in / Sign up

Export Citation Format

Share Document