Keynote Speakers

Jérôme Lacaille  

"Prognostic and Health Monitoring for Turbofans by Snecma, Engine Manufacturer"

Snecma is an engine manufacturer and produces turbofans for most of the short and  medium range civil aircrafts as well as French military engines and rocket engines. New maintenance services proposals for our airline customers are now possible because of the ability to produce robust prognostic about component health. During the last ten years Snecma develops some capabilities in PHM (prognostic and health monitoring), including research tools to help engineers designing specific applications to monitor any engine subsystem using advanced mathematic tools. Among them, we develop health prognostic for the start process of the engine, its oil and fuel subsystems and mechanical elements such as bearings, gears and some structural parts. This presentation is a review of the last works on PHM by Snecma with a vision of the health prognostic and high volume of data management from the manufacturer side.

Biography

Jérôme Lacaille is a Safran emeritus expert which mission for Snecma is to help in the development of mathematic algorithms used for the engine health monitoring. Jérôme has a PhD in Mathematics on “Neural Computation” and a HDR (habilitation à diriger des recherches) for “Algorithms Industrialization” from the Ecole Normale Supérieure (France). Jérôme has held several positions including scientific consultant and professor. He has also co-founded the Miriad Technologies Company, entered the semiconductor business taking in charge the direction of the Innovation Department for Si Automation (Montpellier - France) and PDF Solutions (San Jose - CA). He developed specific mathematic algorithms that where integrated in industrial process. Over the course of his work, Jérôme has published several papers on integrating data analysis into industry infrastructure, including neural methodologies and stochastic modeling.

Michael Feldman

Hilbert Transform: from fundamentals to some applications

Basic and fundamental aspects of the Hilbert Transform are briefly presented. This is followed by comparisons to other Time-Frequency representation, summarizing both advantages and limitations. The by now classic application to modulated signals is briefly shown.

Some important and powerful application to the analysis signal and systems encountered in vibration engineering are shown. These include decompositions of fast varying function, and also non-stationary multicomponent vibrations. Applications to non-linear vibrating systems are next presented: Non-parametric extraction of the modal parameters including initial nonlinear, non-symmetric and time-varying elastic and damping force characteristics.

Biography

Dr. Michael Feldman completed his PhD in Moscow State Technological University in 1977; worked until 1991 as a senior researcher in the Institute of Machine Studies, Moscow - Russian Academy of Sciences.

In 1991 he got a position in the Faculty of Mechanical Engineering, Technion - Israel Institute of Technology, Haifa where nowadays he is a head of Electronics and Computerized Experiment Laboratory and an Adjunct Associate Professor.

His research areas include nonlinear vibration system identification, theory and applications of the Hilbert transform to vibration engineering.

Dr. Feldman has served as an Editorial Board Member of Elsevier’s Journal Mechanical Systems and Signal Processing since 2008. Author of over 50 scientific publications in the areas of both vibration analysis and signal processing, among them the recent book entitled “Hilbert Transform Applications in Mechanical Vibration”, Wiley, 2011.

Patrick Flandrin

Data-driven time-frequency analyses

Multicomponent AM-FM signals are ubiquitous in Nature as well as in man-made systems, and the need for their analysis and processing has been instrumental in the development of the many time-frequency techniques that have been proposed during the last 30 years. Whereas the now well-established "classical" theories (short-time Fourier, wavelets, Wigner, etc.) are based on fixed transforms, new perspectives are nowadays offered by more recent advances which operate in a data-driven way (Hilbert-Huang transform, synchrosqueezing, etc.). Such new approaches will be surveyed, with a discussion of their pros and cons based on theoretical considerations and illustrative examples.

Biography

Patrick Flandrin graduated from ICPI Lyon (Engineer Degree in 1978) and INPG Grenoble (PhD in 1982). He is currently a CNRS "Research Director" at ENS de Lyon. His research interests are mostly in nonstationary signal processing (time-frequency/time-scale methods), self-similar stochastic processes and complex systems. He published over 200 journal or conference papers, contributed several chapters to collective books and authored one monograph. Former Director of CNRS-GdR ISIS (2002-2005), he is President of GRETSI, the French Association for Signal and Image Processing, since 2009. Dr Flandrin has been awarded the Philip Morris Scientific Prize in Mathematics (1991), the SPIE Wavelet Pioneer Award (2001) and the Prix Michel Monpetit from the French Academy of Sciences (2001). Fellow of IEEE (2002) and EURASIP (2009), he has been elected member of the French Academy of sciences in 2010.

More at http://perso.ens-lyon.fr/patrick.flandrin

Luigi Garibaldi

Identification of Time Varying Systems

The lecture is manly based on the reach contributions collected for the recent issue of MSSP (Volume 47, 2014) on time varying systems.  This issue has been devoted to share and spread the knowledge on the main techniques recently developed for the identification of those systems where the parameter invariability assumption leads to important errors and misleading interpretations. Independently on the model adopted, these methods can be generically classified as time-frequency methods because they can follow the parameter evolution along the time; they are usually classed as non-parametric when directly adopting time-frequency methods, while are classed as parametric, such as a type of TARMA (Time dependent ARMA) or TVSSI (Time Variant Stochastic Subspace) when using structured equations. Quite often they are adopted for output only measurements, which is the case by far more frequent in real structures analysis such as for bridges, robots, deploying systems, rockets and aircraft wings.

Apart the cited time-frequency methods and TARMA, TVSSI techniques, some other techniques adopting Hilbert or windowed Hilbert-Huang transform, as well as some Least Square methods, have been approached by authors in the recent past to better fit the models in case of time variant behaviour.

The speech is trying to underline the basic differences and assumptions among these techniques, highlighting the advantages, the drawbacks and the limits of applicability.

Biography

Full Professor of Applied Mechanics and Vibrations at Politecnico di Torino, since 2002, he is leading the Dynamics & Identification Research Group (DIRG) whose research fields are: mechanical vibrations, system identification and diagnostics. He is the Coordinator of the PhD in Mechanics at Politecnico di Torino since 2011, and responsible of Dynamics and Identification Research Group for industry consultancies and international program participations; he has been national coordinator of five Universities net for a Ministry funded research program in 2007-2010. He has been invited professor for a few months at the Université de Technologie de Compiègne (2003 and 2004) and at ENPC (Ecole des Ponts et Chaussées) in 2008; he has conceived the Double Diplome accord within UTC and Polito. He is member of Mechanical Systems and Signal Processing Editorial Board since 2004 and Mechanics & Industry since 2014; reviewer for the most relevant Journals on vibrations, identification and monitoring. He has organized a few congresses, such as DAMAS (2009 in Beijing and 2007 in Torino) and Surveillance5 in Compiègne - (2004 France) and he is present in a number of congress scientific committees. He has been External examiner / tutor / jury member for many PhD Thesis and HDR in Italy, France and Belgium. His group has signed many contracts with private companies such as Fiat Auto, D.R. Renault, Alenia, Pininfarina, Maserati, Fiat Engineering, Ferrari, AVL, Graziano, FIBET, AVIO, Sicme Motori, Eni, SNAM rete gas, Prima Industrie, PMT Italia, Carraro, AP Brakes, SKF Avio, SKF, Arvin Meritor and others. He has published about 150 papers in International reviews and congresses.