Francois Baccelli INRIA ENS Information Theoretic Capacity and Error Exponents of Stationary Point Processes under Random Additive Displacements Authors Venkat Anantharam Francois Baccelli

BOOK OF ABSTRACTS

th6 International Conference
Acoustical and Vibratory
Surveillance Methods and Diagnostic Techniques
UTC Compiègne

Tuesday 25 october 2011
9h20
Plenary Session

Invited paper 1 - THE SURVEILLANCE OF BRIDGES IN FRANCE
Christian Cremona
Technical Centre for Bridges and Structures (CTOA),Technical Department for Transport, Roads
and Bridges (SETRA),Ministry of Ecology, sustainable Development, Transport and Housing
(MEDDTL), Bagneux, France.
The management of structures is a very important economic issue. France has been aware of this
for many years. In 2006, after the parliament vote of decentralization law, the State considered as
critical to rationalize the maintenance and the management of the remaining national asset. Since
the past 5 years, a lot of procedures and guidelines for bridge maintenance have been revised for
the national bridge stock. In addition opportunity was given to introduce new concepts such
focalized inspection, risk-based assessment. These changes or upgrades are made to take better
account in the decision-making process of socio-economic aspects (disruption for road users in
particular) and the effect of decisional choices and to introduce more elaborate structural condition
assessment methods which will give a more reliable estimate of the current and predicted
condition of the bridges asset. This paper presents the current procedures used for managing the
national bridge stock and the proposed enhancements or dominant future works.



Invited paper 2 -AN OVERVIEW OF PARAMETRIC METHODS FOR NON-STATIONARY RANDOM
VIBRATION MODELING AND IDENTIFICATION
Stilios Fassois Stochastic Mechanical Systems and Automation (SMSA) University of Patras,
Greece,
Non–stationary random vibration signals exhibit time–dependent characteristics, thus requiring
time-dependent models and corresponding identification methods. In this talk parametric models
are distinguished into three main classes: unstructured, stochastic, and deterministic parameter
evolution. The main identification methods pertinent to each class are presented, along with recent
advances on “automated” and “complete” methods aiming at the concurrent handling of the model
structure and parameter estimation subproblems. Comparisons of the various methods via a
benchmark study, employing a laboratory bridge–like structure with a moving mass, are made.
Snapshots from the application of the methods to the modeling and identification of mechanism,
robot arm, and wind turbine vibrations, as well as earthquake ground motion are presented. An
outlook on upcoming and future developments is finally provided.




Schematic diagram of wind turbine indicating measurement locations and estimated frozen-type
time-dependent Power Spectral Density function (SP-TARMA method).







th6 International Conference
Acoustical and Vibratory
Surveillance Methods and Diagnostic Techniques
UTC Compiègne

Tuesday 25 october 2011
Morning session 1A
11h00
Signal processing : Cyclostationarity


3 - USING THE MOVING SYNCHRONOUS AVERAGE TO ANALYSE FUZZY
CYCLOSTATIONARY SIGNALS
Q. Leclere,N. Hamzaoui
INSA Lyon, LaboratoireVibrations Acoustique,
Cyclostationarity is a property of vibration and acoustic signals recorded on rotating machines operating at
constant speed. It states that the statistic properties of signals are periodic: the random process defined by
the signal observed at a given position in the cycle is stationary, the cycle being defined as the angle
interval between two identical configurations of the mechanical system. The cyclostationary theory allows
for example the division of the signal into the deterministic part (expected value of a cycle realization, also
called periodic part) and a random part (the centered signal). In some cases, the cyclostationarity property
is not fully satisfied. Mechanical events in the cycle can exhibit different periodicities, for example because
of transmission ratios or rolling elements. If those periodicities are incommensurable, it means that the
mechanical system never recovers periodically strictly identical configurations. Cyclostationarity is also not
fully satisfied if the signals are acquired in the time domain on rotating machines with a fluctuating rotation
speed. Indeed, if the instantaneous rotation speed is not purely periodic, it means that time samples taken
at a constant time interval (equal to the average cycle duration) do not correspond exactly to an angle in
the cycle. In this particular case, a synchronous averaging of cycle realizations can still be processed to
estimate a periodic part using a predefined trigger angle to align cycle realizations before the averaging
process. The time window of each realization is thus defined as two time portions before and after this
synchronization angle (practically, by a number of points of the time-sampled signal before and after the
trigger). In these conditions,the synchronousaverage dependsonthe chosen synchronization angle: each
point of the synchronous average is an estimate of the expected value of the signal at a given time
preceding or following the synchronization angle. The synchronous average can be computed in function of
the synchronization angle, varying over an entire cycle. The result is a moving synchronous average that
can be post-processed for diagnosis purposes. For example, a time frequencyrepresentation of the moving
synchronous average can be computed, and the synchronization angle maximizing each point of the time
frequencymap can be easily extracted. Under certain conditions of instantaneous speed fluctuations, this
analysis allows the precise localization of different mechanical events in the cycle, as well as their
contributions in the analyzed vibration or acoustic signal.

63 - IMPACT OF ANGULAR SAMPLING ON IMPULSE RESPONSE
M. El Badaoui, F. Bonnardot 1Université de Lyon,; Université de Saint Etienne, LASPI, France
Rotating machines produces cyclic signals. When the machine parameters (load, speed, …) are almost
onstant or slowly vary,this cycles will introduce periodicity into acceleration (ie the acceleration signal
exhibits cyclostationarity). Since the cycle is linked to the angular part, it seems natural to use the angle as
a sampling variable instead of the time. Therefore, signal becomes synchronised to machine cycle. The
use of angular (or synchronous) sampling have shown very interesting results.Unfortunately, the
synchronisation with mechanical events obtained by angular sampling is not suitable to study the impulse
response associated to these events (or some structural damage). Therefore, it exists a dilemma in the
choice between angular sampling and classical temporal sampling.In the past, degradation of
cyclostationarity property introduced by the influence of temporal ing was studied. The purpose of
this paper was to study the influence of angular sampling on impulse response and time domain relative
signals.An experimental bench described in figure 1 was constructed. This bench uses a synchronous
data acquisition board. The time domain signal comes from an arbitrary generator (sine wave). The
synchronous sampler is driven by an external clock. Our external clock generator creates a square wave
with a tunable jitter δi (see Figure 2). Each sample are taken during the rising edge. The sampled signal is
digitized and analysed by Labview and MatLab.In order to check our random clock generator, a counter is
used to characterized precisely the sampling signal by measuring each period (T1, T2, …). The data
acquisition board is also capable of making both synchronous and temporal acquisition for comparison.

Experimentations are performed by using various period fluctuations (from 0,1 % to 20 %) and are
corroborated by theoretical studies.The first experimentation was to compare the spectrum of the signal
with period fluctuation vs without period fluctuation (temporal sampling). A comparison of the two spectra
is available in figure 3. Surprisingly, the fluctuation does not alter the peak in the spectrum even with high
fluctuation (the attenuation of the magnitude is very small). Nevertheless, the noise level significantly
increased when the fluctuation percentage increased. This result,confirmed by our theoretical study,
shows that the synchronous sampling hazard is not to distort the signal but to mask the information. A low
pass filter effect exists, but it is marginal.

Figure 3 : Effect of speed
fluctuation on spectra (Speed
fluctuation of 10%)
59 - COMBINING BLIND SEPARATION AND CYCLOSTATIONARY TECHNIQUES FOR
MONITORING DISTRIBUTED WEAR IN GEARBOX ROLLING BEARINGS
G. D' Eliaa, S. Delvecchioa, M. Cocconcellib, G. Dalpiaza University of Ferrara Italy
This work seeks to study the potential effectiveness of the Blind Signal Extraction as a pre-
processing tool for the detection of distributed faults in rolling bearings. In literature, most of the
authors focus their attention on the detection if incipient localized defects. In that case classical
techniques (i.e. envelope analysis) are robust in re