Stochastic definition of state-space equation for particle filtering algorithms

Chemical Engineering Transactions

Volumn 33, Issue , 2013, Pages 1075-1080

  Corbetta, Matteo ^a   Sbarufatti, Claudio ^a   Manes, Andrea ^a   Giglio, Marco ^a  

^a POLITECNICO DI MILANO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CRACKS; EQUATIONS OF STATE; ESTIMATION; MONTE CARLO METHODS; RANDOM PROCESSES; SIGNAL FILTERING AND PREDICTION; STATE SPACE METHODS; STOCHASTIC SYSTEMS;

DETERMINISTIC EQUATIONS; DETERMINISTIC MODELING; MONTE CARLO SAMPLING; MONTE CARLO SAMPLING TECHNIQUE; NONLINEAR AND NON-GAUSSIAN; PARTICLE FILTERING ALGORITHMS; STATE - SPACE MODELS; STOCHASTIC DEGRADATION;

STOCHASTIC MODELS;

EID: 84883705627     PISSN: 22839216     EISSN: 22839216     Source Type: Journal    
DOI: 10.3303/CET1333180     Document Type: Conference Paper

References (16)

1. Arulampalam, M. S., Maskell, S., Gordon, N. Clapp, T., 2002, A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking, IEEE Transactions on signal processing, 50, No. 2.
2. Beretta, S., Villa, A., 2008, A RV approach for the analysis of Fatigue Crack Growth with NASGRO equation, ASRANET Maritime Conferences, Athens, Greece.
3. Broek, D., 1988, The practical Use of Fracture Mechanics, Kluwer Academic Publishers, Dordrecht, Netherlands.
4. Cadini, F., Zio, E., Avram, D., 2009, Monte Carlo-based filtering for fatigue crack growth estimation, Probabilistic Engineering Mechanics, 24, 367-373.
5. Colombo D., Giglio M., Manes A., 2007, 3D fatigue crack propagation analysis of a helicopter component, International Journal of Materials & Product Technology, 30(1/2/3), 107-123.
6. Giglio M., Manes A., Fossati M., Mariani U., Giani C., 2010, Comparison of fatigue crack propagation behaviour of Al 2024 and Al-Li 8090 Helicopter fuselage panels, Journal of Testing and evaluation, 38, No 1, 73-82.
7. Giglio M., Manes A., 2006, Crack propagation on aluminum nomex panels: experimental and numerical approach, The Arabian Journal for Science and Engineering, 31 2C, 1-16.
8. Giglio M., Manes A., 2008, Crack propagation on helicopter panel: Experimental test and analysis, Engineering Fracture Mechanics, 75, 866-879.
9. Giglio M., Manes A., 2011, Terminal ballistic effect on the crack growth assessment of a helicopter rotor drive, Engineering Fracture Mechanics, 78(8), 1542-1554.
10. Haug, A.J., 2005, A Tutorial on Bayesian Estimation and Tracking Techniques Applicable to Nonlinear and Non-Gaussian Processes, MITRE Technical Report, MTR 05W0000004, MITRE Corporate Headquarters McLean, Virginia, USA.
11. Holper, B., Mayer, H., Vasudevan, A. K., Stanzl-Tschegg, S. E., 2003, Near threshold fatigue crack growth in aluminum alloys at low and ultrasonic frequency: Influences of specimen thickness, strain rate, slip behaviour and air humidity, International Journal of Fatigue, 25, 397-411.
12. NASA J. S. Center and Southwest Research Insitute, 2002, NASGRO Reference Manual, Version 4.02. SwRI®, San Antonio, Texas, USA.
13. Sbarufatti, C., Corbetta, M., Manes, A., Giglio, M., 2012, Finite Element based Bayesian Particle Filtering for the estimation of crack damage evolution on metallic panels, European Conference of Prognostic and Health Management, Dresden, Germany.
14. Viganò F., Manes A., Giglio M., 2012, Numerical simulation of the slant fracture of a helicopter's rotor hub with a ductile damage failure criteria, Fatigue and Fracture of Engineering Materials and Structures, 35, Issue 4, 317-327.
15. Virkler, D.A., Hillberry, B. M., Goel, P. K., 1978, The statistical nature of fatigue crack propagation, Technical Report Air Force Flight Dynamics Laboratory, TR-78-43.
16. Zio, E., Peloni, G., 2011, Particle Filtering prognostic estimation of the remaining useful life of nonlinear components, Reliability Engineering and System Safety 96, 403-409.