FRICTIONAL MODELING AND OPTIMIZATION FOR A VIBRATION MODAL ANALYSIS SIMULATOR DEVICE USING GENETIC ALGORITHM

Authors

1 mm

2 kk

Abstract

The aim of this study is friction modeling and optimization of a “vibration modal analysis simulator”. This device has been used for observation and measurement of natural frequencies and mode shapes ofvibrating components and parts under the free or forced vibration conditions. In this paper to obtain linear vibrating motion with less measurement errors and optimum friction factor, the new prototype has been designed using the genetic algorithm. Mass linear motion is modeled by viscous friction agent so that optimized friction factor C with six sub-designation factors is calculated. Obtained results with respect to precursor’s availability, fabrication ability and from the economical point of view are more amenable and applicable than the preliminary devices and show a 70% reduction in friction factor.

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[1] Hostens, I., Anthonis, J., Ramon, H. (2005). “New design for a 6 dof vibration simulator with improved reliability and performance”. Mechanical Systems and Signal Processing, Vol. 19, pp. 105–122.
[2] Hostens, I., Anthonis, J., Kennes, P., Ramon, H. (2000). “Six degrees of freedom test rig design for simulation of mobile agricultural machinery vibrations”. Journal of agricultural Engineering Research, Vol. 77(2), pp. 155–169.
[3] Stewart, D. (1965). “A platform with six degrees of freedom”. Proceedings of the institute of Mechanical Engineering, Vol. 180(1), pp. 371–386.
[4] Clijmans, L., Ramon, H., (1997). “The experimental modal analysis technique to study the dynamic behaviour of sprayers”. Optimising pesticide applications, Vol. 48, pp. 9-16.
[5] Liu, K., Fitzgerald J., Lewis, FL. (1993). “Kinematic analysis of a Stewart platform manipulator”. Industrial Electronics, IEEE Transactions , Vol. 40(2), pp. 282-293.
[6] Lebret, G., Liu, K., Lewis, FL. (2007). “Dynamic analysis and control of a Stewart platform manipulator”.  Journal of Robotic Systems, Vol. 10(5), pp. 629-655.
[7] Dasgupta, B., Mruthyunjaya, TS. (1998). “Closed-form dynamic equations of the general Stewart platform through the Newton–Euler approach”. Mechanism and Machine Theory, Vol. 33(7), pp. 993–1012.
[8] Zhang, C., Song, S. (1993), “An efficient method for inverse dynamics of manipulators based on the virtual work. principle”. Journal of Robotic Systems, Vol. 10(5), pp. 27-605.
]9[ تیموری جروکانی، ح.، رادمرد، س.، بزرگ، م.، (1385). ”دستگاه شبیه­ساز ارتعاشی آنالیز مودال تحت نوسان‏های آزاد و اجباری“. پایان­نامه کارشناسی، دانشگاه یزد، ص. 35 - 74.
]10[ اورنگی، م. (1389). ”استفاده از الگوریتم ژنتیک برای بهینه‌سازی سرعت تزریق آب در یکی از مخازن شکاف دار جنوب غربی ایران“. مجله اکتشاف و تولید، نشریه فنی- تخصصی شرکت نفت ایران، شماره 74، ص. 48-44.
[11] Holland, J. (1992). “Adaption in natural and artificial systems”, 2nd edition, MIT Press Cambridge.
[12] Goldberg, DE. (1989). “Genetic Algorithms in Search, Optimization and Machine Learning”. 1st edition, Wesley Longman Publishing.
]13[ مشین‌چی اصل، م.، رئیسی، پ. (1387). ”بررسی کاربرد الگوریتم ژنتیک در مسایل معکوس مقاومت ویژه الکتریکی“، سیزدهمین کنفرانس ژئوفیزیک ایران، 17 تا 19 اردیبهشت.
]14[ قاری پور، ا.، یوسفیان، ع.، پیراسته، ف.، (1387). ”بهبود مدل‌های شبکه عصبی با استفاده از الگوریتم ژنتیک موازی سازگارپذیر“. دومین کنگره مشترک سیستم‌های فازی و هوشمند ایران، 7 تا 9 آبان.
[15] Robert, WF., Mcdonald, A. (1985). “Introduction to Fluid Mechanics”. 1st edition, John Wiley & Sons Inc.
[16] Peter, J. (2001). “The significance and use of the friction coefficient”. Tribology International, Vol. 34, pp. 585–591.
[17] Singiresu, S. (2010), “Mechanical Vibrations”. 5st edition, Pearson Education Centre.