PROGNOSTIC SYSTEM BASED ON THE MONTE CARLO METHOD FOR DETECTING VIBRATIONS
Keywords:
Monte Carlo, prognosis, vibration, time remaining after failure, industrial system.Abstract
The objective of this work is to choose the Monte Carlo method to predict the future behavior of a vibration system to make estimate the remaining time before the failure. The positive results obtained with the Monte Carlo method. We have seen the effectiveness of this method and the need to adopt it in the prognosis system in the industrial system.
References
Journals
Boulanouar Saadat, Abdellah Kouzou, Mouloud Guemana and Ahmed Hafaifa, Availability phase estimation in gas turbine based on prognostic system modeling. DIAGNOSTYKA the Journal of Polish Society of Technical Diagnostics (PSTD), 2017, vol. 18, no.02, pp. 3-11.
Boulanouar Saadat, Ahmed Hafaifa and Mouloud Guemana, Vibration analysis and measurement based on defect signal evaluation: Gas turbine investigation. Journal of Advanced Research in Science and Technology, 2016, vol. 3, no 1, pp.271-280.
Boulanouar Saadat, Ahmed Hafaifa, Ali Bennani, Nadji Hadroug, Abdellah Kouzou,Mohamed Haddar, Remaining Useful Lifetime Prediction of Gas Turbine Bearings Based on Experiment Vibration Signals Data. Journal of Vibration Testing and System Dynamics. Journal homepage.
D. DROUIN, P. Covington, R. Gauvin, "CASINO: A New Monte Carlo Code In C Language For Electron Beam Interaction - Part II: Tabulated Values Of The Mott Cross Section", Scanning, Vol.19, (1997) 20-28.
D. DROUIN, A. Couture R., D. Joly, X. Tastet, V. Like, "CASINO V2.42- A Fast and Easy to Use Modeling Tool for Scanning Electron Microscopy and Microanalysis Users," Scanning, Vol. 29, (2007) 92-101.
Books
Celine BARANGER and Julien MATHIAUD, Monte-Carlo Method, 2012/2013.
LAURE ELIE BERNARD LAPEYRE, Introduction to Monte Carlo Methods, September 2001.
Emmanuel Grenier, What is the "good" standard deviation formula? Reims Management School.
Bernard. YCART, Monte Carlo Methods, UFR Mathematics and Computer Science René Descartes University, Paris.
Eric GILLON, Approximation of Pi by the Monte Carlo Method, 2008-2009.
Boulanouar Saadat, Ahmed Hafaifa, Abdallah Kouzou and Mouloud Guemana, Elaboration of prognostic system based on time series for decision-making in gas turbine monitoring. Third International Conference on Electrical Engineering and Control Applications. ICEECA'17. November, 21-23, 2017, Constantine, Alegria.
Dissertation
Boulanouar SAADAT, Development of a prognostic system for modeling the vibrations of a gas turbine by reducing maintenance costs, doctoral thesis, 2017 université Djelfa – Algeria.
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