Wireless Device Based on MEMS Sensors and Bluetooth Low Energy (LE/Smart) Technology for Diagnostics of Mechatronic Systems

Article Preview

Abstract:

This paper deals with usability of MEMS sensors for diagnostics of mechatronics system state wirelessly. We can acquire basic kinematics and dynamics mechanism parameters (spatial position, speed, acceleration, vibration, angular rate, orientation, etc.) and some environment condition (local/remote temperature, humidity, pressure, electromagnetic noise) by MEMS sensors. Acquired data are sent to remote application in desktop computer. This system can replace expensive and separate diagnostic tools by small integrated solution with one wireless communication interface (with limitation of MEMS sensors precision). This solution can be battery powered with long operation time, because there is used new wireless technology based on Bluetooth 4 protocol (Low Energy/Smart Bluetooth). Some of integrated MEMS sensors measures same variable on different measuring principle. For example angle can be acquired from three different sensors: magnetometer, accelerometer or gyroscope. Combination of these sensor data can significantly improve value accuracy. The designed diagnostic tool can serve as an inertia measuring unit IMU or Wireless IMU (WIMU).

You might also be interested in these eBooks

Info:

Periodical:

Pages:

13-21

Citation:

Online since:

November 2013

Export:

Price:

[1] S. M. Ma, C. Chen, T. Wang, H. Zhang, H. X. Zhou, Study on Parameters of MEMS Accelerometer, 2012, Key Engineering Materials, pp.531-532.

DOI: 10.4028/www.scientific.net/kem.531-532.496

Google Scholar

[2] J. Lenz, A. S. Edelstein, Magnetic Sensors and Their Applications, 2006, IEEE Sensors Journal, Vol. 6, No. 3, pp.631-649.

DOI: 10.1109/jsen.2006.874493

Google Scholar

[3] K. Kawano, S. Kobashi, M. Yagi, K. Kondo, Analyzing 3D Knee Kinematics Using Accelerometers, Gyroscopes and Magnetometers, System of Systems Engineering, 2007, SoSE 7. IEEE International Conference on 16-18 April 2007, p.1 – 6.

DOI: 10.1109/sysose.2007.4304332

Google Scholar

[4] Information on TMP006 http://www.ti.com/lit/ug/sbou107/sbou107.pdf

Google Scholar

[5] Information on http://processors.wiki.ti.com/images/7/71/TMP006_Lens_Materials.pdf

Google Scholar

[6] Information on http://processors.wiki.ti.com/index.php/SensorTag_User_Guide

Google Scholar

[7] D. Roetenberg, H. J. Luinge, C. T. M. Baten, P. H. Veltink, Compensation of magnetic disturbances improves inertial and magnetic sensing of human body segment orientation.

DOI: 10.1109/tnsre.2005.847353

Google Scholar

[8] Y. Li, A. Dempster, B. Li, J. Wang, C. Rizos, A low-cost attitude heading reference system by combination of GPS and magnetometers and MEMS inertial sensors for mobile applications, 2006, Journal of Global Positioning Systems, Vol. 5, No. 1-2, pp.88-95.

DOI: 10.5081/jgps.5.1.88

Google Scholar

[9] J. Boržíková, J. Piteľ, M. Tóthová, B. Šulc, Dynamic simulation model of PAM based antagonistic actuator, 2011, proceedings of the 12th International Carpatian Control Conference, Velké Karlovice, Czech Republic, IEEE, 2011 pp.32-35.

DOI: 10.1109/carpathiancc.2011.5945809

Google Scholar

[10] M. Balara, M. Tóthová, Static and dynamic properties of the pneumatic actuator with artificial muscles, SISY 2012: IEEE 10th Jubilee International Symposium on Intelligent Systems and Informatics, proceedings: Subotica, Serbia: IEEE, pp.577-581.

DOI: 10.1109/sisy.2012.6339483

Google Scholar

[11] M. Balara, The upgrade methods of the pneumatic actuator operation ability, Applied Mechanics and Materials, 2013, Vol. 308, pp.63-68.

DOI: 10.4028/www.scientific.net/amm.308.63

Google Scholar

[12] M., Tóthová, J., Piteľ, J., Boržíková, Operating modes of pneumatic artificial muscle actuator, Applied Mechanics and Materials, 2013, Vol. 308, pp.39-44.

DOI: 10.4028/www.scientific.net/amm.308.39

Google Scholar

[13] A. Hošovský, J. N. Marcinčin, J. Piteľ, J. Boržíková and K. Židek, Model-based evolution of a fast hybrid fuzzy adaptive controller for a pneumatic muscle actuator, 2012, International Journal of Advanced Robotic Systems, Vol. 9, pp.1-11.

DOI: 10.5772/50347

Google Scholar

[14] S. Hrehová, A. Vagaská, Application of fuzzy principles in evaluating quality of manufacturing Process, 2012, WSEAS Transaction on Power Systems. Vol.7, No. 2, pp.50-59.

Google Scholar

[15] A. Macurová, S. Hrehová, Some properties of the pneumatic artificial muscle expressed by the nonlinear differential equation, 2013, Advanced Materials Research. Vol. 658, pp.376-379.

DOI: 10.4028/www.scientific.net/amr.658.376

Google Scholar

[16] L. Jurišica, F. Duchoň, D. Kaštan, A. Babinec, High Precision GNSS Guidance for Field Mobile Robots, 2012, International Journal of Advanced Robotic Systems, Vol. 9, pp.169-178.

DOI: 10.5772/52554

Google Scholar

[17] J. Rodina, P. Hubinský, Stability control design of segway like differential drive by using MEMS sensors, 2010, Metallurgy, Croatia, Vol. 49, No. 2, pp.483-487.

Google Scholar

[18] J. Semjon, J. Svetlík, R. Jánoš, Analysis of the basic design by positioning modules for cooperation of the robot, 2012. International Scientific Herald, Vol. 3, No. 2, pp.150-155.

Google Scholar