ARTICLE
Consideration of uncertainties in the preliminary design case of an electromagnetic spindle
 
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1
Mechanics, Modelling and Production Research Laboratory, National School of Engineers of Sfax, University of Sfax, Sfax
2
QUARTZ EA7393, Supméca-Paris, Saint-Ouen
Online publish date: 2019-10-15
Publish date: 2019-10-15
Submission date: 2019-01-29
Acceptance date: 2019-04-02
 
Journal of Theoretical and Applied Mechanics 2019;57(4):821–832
KEYWORDS
ABSTRACT
Modeling and evaluation of uncertainties constitute indeed one of the key points when making any decision. For this, designers have to compare the measured or calculated value with a range of permissible values in order to obtain a guaranteed design process. Thus, in this work, simulation of the dynamic behavior of an electromagnetic spindle was done based on the interval computation technique. Indeed, the use of this technique makes it possible to obtain a set of values for different design parameters of the spindle and, consequently, to avoid making several simulations which could make the system useless, expensive or ineffective. The proposed model is based on the combination of Matlab with ModelCenter. Matlab was used to model and simulate the system and ModelCenter to perform parametric studies to verify the influences of uncertainty on the dynamic behavior of the electromagnetic spindle and to determine the optimal design parameters.
 
REFERENCES (20)
1.
Affi Z., Badreddine E., Romdhane L., 2007, Advanced mechatronic design using a multi--objective genetic algorithm optimization of a motor-driven four-bar system, Mechatronics, 17, 489-500.
 
2.
Alefeld G., Mayer G., 2000, Interval analysis: theory and applications, Journal of Computational and Applied Mathematics, 121, 421-464.
 
3.
Amendola G., Dimino I., Concilio A., Amoroso F., Pecora R., 2017, Preliminary design of an adaptive aileron for the next generation regional aircraft, Journal of Theoretical and Applied Mechanics, 55, 1, 307-316, DOI: 10.15632/jtam-pl.55.1.307.
 
4.
Bouaziz A., 2016, Contribution á l’etude du comportement dynamique d’une machine-outil en presence des suspensions magnetiques, ENIS.
 
5.
Bouaziz A., Barkallah M., Bouaziz S., Choley J.Y., Haddar M., 2016, Cutting parameters and vibrations analysis of magnetic bearing spindle in milling process, Journal of Theoretical and Applied Mechanics, 54, 3, 691-703, DOI: 10.15632/jtam-pl.54.3.691.
 
6.
Colton J.S., Ouellette M.P., 1994, A form verification system for the conceptual design of complex mechanical systems, Engineering with Computers, 10, 33-44.
 
7.
Deb K., Pratap A., Agarwal S., Meyarivan T., 2002, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, 6, 182-197.
 
8.
Faroughi S., Lee J., 2015, Analysis of tensegrity structures subject to dynamic loading using a Newmark approach, Journal of Building Engineering, 2, 1-8.
 
9.
Gościniak I., Gdawiec K., 2019; Control of dynamics of the modified Newton-Raphson algorithm, Communications in Nonlinear Science and Numerical Simulation, 67, 76-99.
 
10.
Gourc E., Seguy S., Arnaud L., 2011, Chatter milling modeling of active magnetic bearing spindle in high-speed domain, International Journal of Machine Tools and Manufacture, 51,928-936.
 
11.
Guizani A., Hammadi M., Choley J.Y., Soriano T., Abbes M.S., Haddar M., 2017, Multi-agent approach based on a design process for the optimization of mechatronic systems, Mechanics and Industry, 18, 507.
 
12.
Hansen E., Walster G.W., 2003, Global Optimization Using Interval Analysis: Revised and Expanded, CRC Press.
 
13.
He Y., McPhee J., 2005, Multidisciplinary design optimization of mechatronic vehicles with active suspensions, Journal of Sound and Vibration, 283, 217-241.
 
14.
Hentati T., Bouaziz A., Bouaziz S., Choley J.Y., Haddar M., 2013, Dynamic behaviour of active magnetic bearings spindle in high-speed domain, International Journal of Mechatronics and Manufacturing Systems, 6, 474-492.
 
15.
Kimman M., Langen H., Schmidt R.M., 2010, A miniature milling spindle with active magnetic bearings, Mechatronics, 20, 224-235.
 
16.
Knospe C.R., 2007, Active magnetic bearings for machining applications, Control Engineering Practice, 15, 307-313.
 
17.
Makowski M., Zalewski R., 2015, Vibration analysis for vehicle with vacuum packed particles suspension, Journal of Theoretical and Applied Mechanics, 53, 109-117.
 
18.
Teorey T. J., Yang D., Fry J.P., 1986, A logical design methodology for relational databases using the extended entity-relationship model, ACM Computing Surveys (CSUR), 18, 197-222.
 
19.
Trabelsi H., Yvars P.A., Louati J., Haddar M., 2015, Evaluation of the effectiveness of the interval computation method to simulate the dynamic behavior of subdefinite system: application on an active suspension system, International Journal on Interactive Design and Manufacturing (IJIDeM), 9, 83-96.
 
20.
Vu N.A., Lee J.W., Le T.P.N., Nguyen S.T.T., 2016, A fully automated framework for helicopter rotor blades design and analysis including aerodynamics, structure, and manufacturing, Chinese Journal of Aeronautics, 29, 1602-1617.
 
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