نویسندگان
دانشکدة مهندسی مکانیک، دانشگاه صنعتی امیرکبیر، تهران، ایران
چکیده
در این مقاله، یک روش سریع و کم‌هزینه که با استفاده از اندازه‌گیری جابه‌جایی حسگر قادر به کالیبراسیون است، ارائه می‌شود. همچنین به‌منظور راستی آزمایی روش ارائه شده از یک میز دو درجه آزادی که یک وسیلة متداول ولی گران برای کالیبراسیون به‌شمار می‌رود، به همراه یک شبکة عصبی چندلایه به‌منظور برقراری رابطة غیرخطی بین ورودی‌ها و خروجی‌های سیستم استفاده شده است. نتایج به‌دست آمده نشان دهندة کارایی مناسب و دقت زیاد شبکه در کالیبراسیون است. به‌منظور طراحی شبکة عصبی از امکانات و توابع موجود در محیط برنامه‌نویسی متلب بهره گرفته شده است.
کلیدواژه‌ها
عنوان مقاله [English]
Verification of a Low Cost Method for Accelerometers Calibration with a Two-Axis Table
نویسندگان [English]
- Mohsen Bahrami
- Behzad Parsi
Faculty of Mechanical Engineering, Amirkabir University of Technology, Tehran, Iran
چکیده [English]
In this paper a low cost calibration method which can calibrate with measuring the sensor displacement is suggested. To verify this calibration method a two-axis table, which is expensive, with artificial neural network (ANN) for mapping non-linear relationships between the inputs and outputs is used. The result illustrates the efficiency of this calibration method. In order to design the artificial neural network the MATLAB software is used.
کلیدواژه‌ها [English]
- Calibration
- Artificial Neural Network
- Two
- axis table
- Microelectro mechanical accelerometers
- Yazdi, , Ayazi, F. and Najafi, K., “Microm Chined Inertial Sensors,” Proceeding of the IEEE, Vol. 86, No. 8, 1998, pp. 1640–1659.
- Titterton, D. H. and Weston, J. L., “Strapdown Inertial Navigation Technology,” Proceeding of the IEEE, United Kingdom, 2004.
- Liu, K., Zhang, W., Chen, W., Li, K., Dai, F., Cui, F. and Q. Xiao, “The Development of Micro-Gyroscope Technology,” Journal Micromech. Microeng, Vol. 19, No. 11, 2009, pp. 113001 -113001.
- Sukkarieh, S., Gibbens, P., Grocholsky, B., Willis, K. and Durrant-Whyte, H.F., “A Low-Cost Redundant Inertial Measurement Unit for Unmanned Air Vehicles,” International Journal Robotics Research, Vol. 19, No. 11, 2000, pp.1089–1103.
- Barshan, B. and Durrant-Whyte, H. F., “An Inertial Navigation System for a Mobile Robot,” Proceeding IEEE/ RSJ International Conference Intell. Robots and System Yokohama, Japan, 1993, pp.2243–2248.
- Chatfield, A. B., Fundamentals of High Accuracy Inertial Navigation, Progress in Astronautics and Aeronautics, P. Zarchan, Ed. Reston, VA: AIAA 174, 1997.
- Grewal, M. S., Henderson, V. D. and Miyasako, R. S., “Application of Kaman Filtering to the Calibration and Alignment of Inertial Navigation Systems,” Automatic Control, IEEE Transactions, 36, Issue 1, 1991, pp. 3-13.
- Skog, I. and Handel, P., “Calibration of a Mems Inertial Measurement Unit,” XVIIIIMEKO World Congress, Metrology for a Sustainable Development, Riode Janeiro, Brazil, 2006, pp.17–22.
- Kim, A. and Golnaraghi,M. F., “Initial Calibration of an Inertial Measurement Unit using an Optical Position Tracking System,” IEEE Aerospace Electronic System Soceity Position Location and Navigation Symposium, CA, 2004, pp. 96–101.
- R. and Zhou, Z., “Calibration of three-Dimensional Integrated Sensors for Improved System Accuracy,” Sensors and Actuators A: Physical, Vol. 127, No. 2, 2006, pp. 340–344.
- Rogers, R.M., Applied Mathematics in Integrated Navigation Systems, AIAA, 2000.
- Grewal, M.S., Weill, L.R. and Andrews A.P, Global Positioning System, Inertial Navigation and Integration, John Wiley& Sons, New York, 2001.
- Wolberg, J., Data Analysis Using the Method of Least Squares: Extracting the Most Information from Experiments, Springer, Berlin, 2005.
- Proakis, J.G. and Manolakis, D.K., Digital Signal Processing, Macmillan Publishing Company, New York, 1989.
- Jin-Wei, W., Jia-Li, Z. and Si-Wei, L., “The Improvements of BP Neural Network Learning Algorithm,” Proceeding of the IEEE, 2000.
- Zweiri, Y.H., Whidborne, J.F., Althoefer, K. and SeneviratneL. D., A New Three-Term Back Propagation Algorithm with Convergence Analysis , Proceeding of the IEEE, 2002.
- Sadrzadeh, M., Mohammadi, T., Ivakpour, J. and Kasiri, N., “Separation of Lead Ions from Waste water Using Electrodialysis: Comparing Mathematical and Neural Network Modeling,” Chemical Engineering Journal-CHEM ENG Journal, 144, No. 3, 2008, pp. 431–441.
- Demuth, H. and Beale, M., Neural Network Tool box: For Use with MATLAB (Version 4.0), The Math Works, Inc., 2004.
)