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SUMMARY:COMO3#6 -
DTSTART;VALUE=DATE-TIME:20230712T134000Z
DTEND;VALUE=DATE-TIME:20230712T140000Z
DTSTAMP;VALUE=DATE-TIME:20260308T095522Z
UID:indico-contribution-194-789@events.isae-supaero.fr
DESCRIPTION:https://events.isae.fr/event/22/contributions/789/
LOCATION:
URL:https://events.isae.fr/event/22/contributions/789/
END:VEVENT
BEGIN:VEVENT
SUMMARY:"COMO3#3 - Identification of non-informative noise component in ti
 me-frequency representations. Application to vibration-based local damage 
 detection"
DTSTART;VALUE=DATE-TIME:20230712T124000Z
DTEND;VALUE=DATE-TIME:20230712T130000Z
DTSTAMP;VALUE=DATE-TIME:20260308T095522Z
UID:indico-contribution-194-652@events.isae-supaero.fr
DESCRIPTION:Speakers: Wylomanska Agnieszka ()\nIn this presentation we hig
 hlight the importance of the background noise properties in the context of
  the vibration-based local damage detection. We assume the model is a mixt
 ure of signal of interest (SOI) and the noise. In the case\, when the back
 ground noise has Gaussian characteristics\, the classical methods for loca
 l damage detection can be applied. In this case\, the most common approach
 es are based on the measuring of impulsiveness of the vibration signal or 
 cyclostationary analysis. In both cases\, the used methods often are appli
 ed to the signal in time-frequency representation. However\, for many case
 s in real environment the assumption of Gaussian distribution of the noise
  is not satisfied and one may expect the large impulses that influence the
  noise characteristics. It should be noted\, the non-Gaussian distribution
  of the signal may occur for many machines. In that case the impulsiveness
  criteria fail and the cyclostationary analysis seems to be more useful ap
 proach. Since\, most of the methods used in the cyclostationary analysis a
 re based on the autocovariance function\, we indicate here the important r
 ole of the finite variance of the signal. In theory\, if the variance is i
 nfinite\, then the autocovariance is also not defined. We highlight\, the 
 problem considered here is much more general than the problem of testing t
 he noise distribution. We present a new approach for the assessment of the
  noise probabilistic properties. The methodology is applied for the time-f
 requency representation of the signal. The problem is illustrated for the 
 simulated signals from non-Gaussian distributions and real signals from va
 rious machines.\n\nhttps://events.isae.fr/event/22/contributions/652/
LOCATION:Toulouse
URL:https://events.isae.fr/event/22/contributions/652/
END:VEVENT
BEGIN:VEVENT
SUMMARY:"COMO3#5 - Algorithm for the detection of faults in rolling elemen
 t bearings running under tacholess and variable rotating speed conditions"
DTSTART;VALUE=DATE-TIME:20230712T132000Z
DTEND;VALUE=DATE-TIME:20230712T134000Z
DTSTAMP;VALUE=DATE-TIME:20260308T095522Z
UID:indico-contribution-194-654@events.isae-supaero.fr
DESCRIPTION:Speakers: Hernandez Fidel ()\nThe goal of this research was to
  implement a new algorithm for the automatic detection of faults in rollin
 g element bearings\, in such a way that it does not depend on the estimati
 on of the shaft rotational speed. The idea was that the algorithm could be
  applied under variable and unknown rotational speed conditions. The propo
 sed algorithm was based on the detection of phase-relationships between sp
 ectral components that emerge when an amplitude modulation appears in the 
 gathered vibration. To do that\, a mode decomposition procedure\, as well 
 as the Hilbert transform\, was applied in order to estimate a detection co
 efficient\, which served as indicator of the presence of the modulation pr
 oduced by the faults. Lock-in amplifiers were used in order to calculate s
 uch an indicator. The effectiveness of the method was validated through ex
 periments preformed by using simulation and real signals. It was proven th
 at the application of the proposed method can lead to an effective detecti
 on of the modulation featuring the existence of rolling element bearing fa
 ults.\n\nhttps://events.isae.fr/event/22/contributions/654/
LOCATION:Toulouse
URL:https://events.isae.fr/event/22/contributions/654/
END:VEVENT
BEGIN:VEVENT
SUMMARY:"COMO3#2 - Wavelet-based high order spectrum for local damage diag
 nosis of gears under different operating conditions"
DTSTART;VALUE=DATE-TIME:20230712T122000Z
DTEND;VALUE=DATE-TIME:20230712T124000Z
DTSTAMP;VALUE=DATE-TIME:20260308T095522Z
UID:indico-contribution-194-651@events.isae-supaero.fr
DESCRIPTION:Speakers: Zhu Rui ()\nGears play an important role in transmis
 sion systems\, allowing for high performance in terms of load capacity and
  efficiency. Common gear faults such as cracked teeth and pitted teeth\, c
 an occur as a result of contact fatigue\, excessive load\, or sudden impac
 t. Starting from an initial stage\, their steady growth can lead to irrepa
 rable damage and unexpected breakdowns that result in economic losses. The
 refore\, local tooth damage diagnosis of gears using advanced monitoring t
 echniques is extremely important for the normal operation of drivelines an
 d transmissions. The presence of local tooth damage on gear tooth produces
  transient impact in the vibration signals\, which exhibit non-stationary 
 and non-linear characteristics. Taking into account its ability to charact
 erize the phase coupling between signal components caused by non-linearity
 \, wavelet-based high order spectrum (e.g. wavelet bispectrum/bicoherence)
  is considered to be effective to attain reliable fault-related features. 
 Among others\, wavelet bicoherence technology has been successfully applie
 d to detect the artificially created gear faults under steady speed and lo
 ad. However\, in case the operating condition changes\, the effectiveness 
 of this method in detecting gear faults is still unclear. Additionally\, t
 here is no mature idea of selecting informative bifrequency bands and extr
 acting instantaneous diagnostic features after applying wavelet bicoherenc
 e. This may constraint the widespread application of wavelet-based high or
 der spectrum in gear fault diagnosis. This paper presents a novel strategy
  for selecting informative bifrequency bands and extracting instantaneous 
 diagnostic features in the time-bifrequency domain. The performance of the
  proposed methodology is evaluated and extended to cases involving healthy
  and faulty gears operating under different speeds and loads. To validate 
 the effectiveness of the methodology\, a publicly available dataset is uti
 lized\, which includes gears with various crack severity as well as differ
 ent speed and load operating conditions.\n\nhttps://events.isae.fr/event/2
 2/contributions/651/
LOCATION:Toulouse
URL:https://events.isae.fr/event/22/contributions/651/
END:VEVENT
BEGIN:VEVENT
SUMMARY:"COMO3#4 - Robust estimators of autocorrelation function in applic
 ation to local damage detection for non-Gaussian signals"
DTSTART;VALUE=DATE-TIME:20230712T130000Z
DTEND;VALUE=DATE-TIME:20230712T132000Z
DTSTAMP;VALUE=DATE-TIME:20260308T095522Z
UID:indico-contribution-194-653@events.isae-supaero.fr
DESCRIPTION:Speakers: Zulawinski Wojciech ()\nOne of the most common appro
 aches for local damage detection is the cyclostationary analysis. The indi
 cators of cyclostationarity are based on the classical estimation of autoc
 orrelation function (ACF)\, called sample ACF. It can be applied for the u
 nderlying signal in time\, time-frequency or frequency-frequency domains. 
 The indicators based on sample ACF are very efficient in case when the inf
 ormative signal is disturbed by Gaussian- (or close to Gaussian)-distribut
 ed noise. However\, in case when the background noise has strong non-Gauss
 ian behavior\, the sample ACF may fail as it is sensitive to large impulse
 s related to the non-Gaussian characteristics of the noise. Thus\, in this
  presentation we discuss the new approach based on the robust versions of 
 sample ACF. By robust sample ACF we mean the algorithms less sensitive to 
 large observations that estimate theoretical ACF. By relatively simple rep
 lacement of the classical statistic by its robust versions\, one may decre
 ase the influence the non-Gaussian distribution and identify the cyclostat
 ionary behavior also in this case. In the literature there are considered 
 various statistics used as robust versions of sample ACF but they were nev
 er used in condition monitoring. In this presentation we demonstrate the g
 eneral methodology of new cyclostationary indicators that\, similar as the
  classical approach\, can give the information in different domains. The r
 esults are demonstrated for three selected robust estimators of ACF and tw
 o different non-Gaussian distributions of the background noise. The simula
 tion studies are supported by applications of the introduced methodology t
 o real vibration signal.\n\nhttps://events.isae.fr/event/22/contributions/
 653/
LOCATION:Toulouse
URL:https://events.isae.fr/event/22/contributions/653/
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BEGIN:VEVENT
SUMMARY:"COMO3#1 - Experimental study on condition indicators for severity
  estimation of growing spall in bearings."
DTSTART;VALUE=DATE-TIME:20230712T120000Z
DTEND;VALUE=DATE-TIME:20230712T122000Z
DTSTAMP;VALUE=DATE-TIME:20260308T095522Z
UID:indico-contribution-194-650@events.isae-supaero.fr
DESCRIPTION:Speakers: Bublil Tal ()\nRolling element bearings are essentia
 l components for the proper functioning of many types of rotating equipmen
 t. Diagnosing faults in bearings has traditionally been done using signal 
 processing techniques inspired by physics\, where acceleration signals are
  analyzed using time-frequency analysis methods. One of the key challenges
  in classifying the spall severity in practical applications is that chang
 es in acceleration signatures\, which are related to the size of the spall
 \, are hard to detect due to low signal-to-noise ratios (SNRs).  The obje
 ctive of this research is to study and characterize the effect of spall pr
 opagation on acceleration signatures to classify and identify the spall se
 verity. To overcome the challenge of low SNRs\, we focus on changes in sig
 nal trends rather than events in single measurements. Experiments were con
 ducted to gather data from endurance tests with growing faults on the oute
 r ring of cylindrical roller bearings. The data collected includes measure
 ments of acceleration and load at various rotational speeds.  One benefit
  of conducting endurance tests is that they allow for the natural propagat
 ion of spall\, however\, the extent of spall severity during the test rema
 ins uncertain. To overcome this\, a spall size estimate is used derived fr
 om the load-cell signals\, which is validated by means of visual inspectio
 ns. Although a load-cell is not available in practical applications it is 
 used in our research as the €œground truth€ to validate the acceler
 ation-based algorithms.  A new condition indicator (CI) for classifying s
 pall severity is proposed. This CI was derived through analysis of CIs tre
 nds\, extracted from order domain signatures. The new CIs enable the ident
 ification of several stages of spall propagation prior to reaching the cri
 tical size\, where beyond asset operation is no longer acceptable. The eff
 ectiveness of this new CI was demonstrated using four different endurance 
 tests.\n\nhttps://events.isae.fr/event/22/contributions/650/
LOCATION:Toulouse
URL:https://events.isae.fr/event/22/contributions/650/
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