Real-Time Vibration Control of Rotor-Bearing System Based on Artificial Neural Networks and Active Support Stiffness
A real-time dynamic response of the rotor-bearing system is controlled through an active support stiffness designed and constructed for this purpose. It consists mainly of a variable, flexible beam length. A stepper motor with a screw is implemented to manipulate the beam length to the required optimum position. Hence, it works as active spring stiffness, which minimizes the vibration response for the system. Stiff support is fixed at a specified position on the beam, and it is provided with a small ball bearing at the point of contact with the rotor at the other end. An artificial neural network has been used to control the dynamic system response. Response simulation with real-time LabVIEW is conducted to play a role as an interface to deal with the required sensors' records and the rotation of the stepper motor. The results show that the controlled system is efficient in obtaining the optimum support stiffness for different rotational speeds of the driven motor, which gives, in turn, the optimum system dynamic response.
Blanco – Ortega,A., Silva - Navarro,G., and Gomez – Mancill ,j.c., Active Vibration Control on a Rotor Bearing System Using Hybrid Journal Bearings, Twelfth international congress on sound and vibration, Lisbon, 11(1), July 2005.
Ricardo C. Simoes, Valder Steffen, Jr.,Johan Der Hagopain,and Jarir Mahfoud, Model Active Vibration Control of a Rotor Using Piezoelectric Stack Actuators, Journal of Vibration and Control,13(1), pp.45-6, January 2007.
Andre’s Blanco – Ortega, Francisco Beltran Carbajal, Gerardo Silva Navaro, and Marco Antonio Oliver Salazar, Active Vibration Control on a Rotor Bearing System Based on Dynamic Stiffness, Rev, Fac, Ing. Univ, Antioquia, 55 pp. 125-133, Sep.2010.
Peter Ferefcki, Roman Sikora, and Zdenek Poruba, Numerical Simulation of Feedback Controlled Fluid – Induced Instabilities in Rotor System Supported by Hydro – Dynamic Bearings, Archives of Control Sciences, 20 (LVI) (3), pp. 287-301,2010.
Cabrera – Amado,A., and Silva – Navaro, G., Semi Active Vibration Absorption in a Rotor – Bearing System Using a PPF Control Sheme, proceeding of ISMA 2012 – USD, pp. 205-222, January 2012.
Jader M. Borges, Antonio Silva, A., Carlos J. de Aroujo, Eisenhawer de M. Fernandes, Roberto Leal Pimental,and Alberdan A. Santigo, Rotor – Bearing Vibration Control System Based on Fuzzy Controller and Smart actuators, int. Jnl of Multi Physics, 7(3), pp. 197-206, September 2013.
Salazar, J.G., and Santos, Feedback Controlled Lubrication for Reducing the Lateral Vibration of Flexible Rotors Supported by Tilting – Pad Journal Bearings, Proceeding of the Institution of Mechanical Engineering Part J, Journal of Engineering Technology, 208 – 210(10), pp. 1994-1998, April 2015.
Abdur Rosyid, Mohannad Alata, and Mohammed Elmadany, Adaptive Neuro – Fuzzy Inference System Controller for Vibration Control of Reduced – Order Finite Elements Model of Rotor – Bearing – Support System, International Letters Chemistry, Physics and Anstromy, ISSN 2299-3843, 55(1), PP. 1-11., July 2015.
Rajasethara Reddy Mutra, and srinivas, J., Semi-Active Vibration Control of High-Speed Rotor System with Electro - Rheological Bearing, MATEL web conferences, 211, 14008, October 2018.
Shaolin Ran, Yefa Hu, Hauchun Wu, and Xin Cheng, Resonance Vibration Control for AMB Flexible Rotor System Based on µ - Synthesis controller, Mathematical Problems in Engineering’s, 2018, Article ID 4362101, 16 pages, Dec. 2018.
Behnam Monjezi and and Hamidreza Heidari, Active Vibration Control of Rotor – Bearing System by Virtual Dynamic Absorber, Eur. Phys. J. Appl. Phys.,86(3), pp. 10, June 2019.
Mohammed Alhussein, Hamid Moeeufard, and Jalil Razaee Pazhand, Vibration Attenution of Rotor – Bearing Systems Using Smart Electro- Rheological Elastomer Supports, Journal of the Barazilian Socity of Mechanical Sciences and Engineering,41(6), June 2019.
Yangho Zheng, Nimo. Yan Zhou, and Zhengang Shi, Unbalance Compensation and Automatic Balance of Active Magnetic Bearing Rotor System by Using Iterative Learning Control, IEEE Access, 7, pp. 122613 – 122625, August 2019.
Shaolin Ran, Yefa Hu,Huachun Wu, and Xin Cheng, Active Vibration Control of Flexible High Speed Rotor with Magnetic Bearings Via Phase Compensation to pass Critical Speed, Journal of Low Frequency Noise, Vibration and Active Control, 9(17), Dec. 2019.
Antony Kirk, and Jonothan Griffiths, On the Importance of Sleeve Flexibility in Pasive Control of Critical Speeds of a Rotatng Shaft Using Eccentric Sleeves, Journal Machines, 7(3), Sep. 2019.
Timoshenko, S., Elements of Strength of Materials, Divan Nostrand company, INC, England, 1968. (Book).
Hegan, M. T., and Menhaj, M.B, 1994, Training Feed Forward Networks with the Marquardt Algorithm, IEEE Transaction on Neural Networks, 5(6), November. 1994.
- There are currently no refbacks.
Published by INSIGHT - Indonesian Society for Knowledge and Human Development