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Shock and Vibration
Volume 2015 (2015), Article ID 506430, 14 pages
http://dx.doi.org/10.1155/2015/506430
Research Article

Online Structural Health Monitoring and Parameter Estimation for Vibrating Active Cantilever Beams Using Low-Priced Microcontrollers

Institute of Automation, Measurement and Applied Informatics, Faculty of Mechanical Engineering, Slovak University of Technology in Bratislava, Nám Slobody 17, 812 31 Bratislava 1, Slovakia

Received 28 November 2014; Accepted 23 April 2015

Academic Editor: Xinjie Zhang

Copyright © 2015 Gergely Takács et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. C. R. Fuller, “Active control of sound transmission/radiation from elastic plates by vibration inputs: I. Analysis,” Journal of Sound and Vibration, vol. 136, no. 1, pp. 1–15, 1990. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Preumont and K. Seto, Active Control of Structures, John Wiley & Sons, Chichester, UK, 3rd edition, 2008. View at Publisher · View at Google Scholar
  3. C. Edwards, “The 8-bit strikes back,” IET Electronics Systems and Software, vol. 5, no. 2, pp. 36–39, 2007. View at Publisher · View at Google Scholar · View at Scopus
  4. D. C. Hyland and L. D. Davis, “Toward self-reliant control for adaptive structures,” Acta Astronautica, vol. 51, no. 1–9, pp. 89–99, 2002. View at Publisher · View at Google Scholar · View at Scopus
  5. G. Takács, T. Polóni, and B. Rohal'-Ilkiv, “Adaptive model predictive vibration control of a cantilever beam with real-time parameter estimation,” Shock and Vibration, vol. 2014, Article ID 741765, 15 pages, 2014. View at Publisher · View at Google Scholar · View at Scopus
  6. M.-T. Vakil-Baghmisheh, M. Peimani, M. H. Sadeghi, and M. M. Ettefagh, “Crack detection in beam-like structures using genetic algorithms,” Applied Soft Computing Journal, vol. 8, no. 2, pp. 1150–1160, 2008. View at Publisher · View at Google Scholar · View at Scopus
  7. F. S. Buezas, M. B. Rosales, and C. P. Filipich, “Damage detection with genetic algorithms taking into account a crack contact model,” Engineering Fracture Mechanics, vol. 78, no. 4, pp. 695–712, 2011. View at Publisher · View at Google Scholar · View at Scopus
  8. P. M. Pawar and R. Ganguli, “Genetic fuzzy system for online structural health monitoring of composite helicopter rotor blades,” Mechanical Systems and Signal Processing, vol. 21, no. 5, pp. 2212–2236, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. F. Kang, J.-J. Li, and Q. Xu, “Damage detection based on improved particle swarm optimization using vibration data,” Applied Soft Computing Journal, vol. 12, no. 8, pp. 2329–2335, 2012. View at Publisher · View at Google Scholar · View at Scopus
  10. R. O. Curadelli, J. D. Riera, D. Ambrosini, and M. G. Amani, “Damage detection by means of structural damping identification,” Engineering Structures, vol. 30, no. 12, pp. 3497–3504, 2008. View at Publisher · View at Google Scholar · View at Scopus
  11. W. L. Bayissa, N. Haritos, and S. Thelandersson, “Vibration-based structural damage identification using wavelet transform,” Mechanical Systems and Signal Processing, vol. 22, no. 5, pp. 1194–1215, 2008. View at Publisher · View at Google Scholar · View at Scopus
  12. M. B. Rosales, C. P. Filipich, and F. S. Buezas, “Crack detection in beam-like structures,” Engineering Structures, vol. 31, no. 10, pp. 2257–2264, 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. M. T. Vakil Baghmisheh, M. Peimani, M. H. Sadeghi, M. M. Ettefagh, and A. F. Tabrizi, “A hybrid particle swarm-Nelder-Mead optimization method for crack detection in cantilever beams,” Applied Soft Computing Journal, vol. 12, no. 8, pp. 2217–2226, 2012. View at Publisher · View at Google Scholar · View at Scopus
  14. R. Y. Chiang and M. G. Safonov, “Design of H controller for a lightly damped system using a bilinear pole shifting transform,” in Proceedings of the American Control Conference, pp. 1927–1928, June 1991. View at Scopus
  15. R. E. Kalman, “Contributions to the theory of optimal control,” Boletín de la Sociedad Matemática Mexicana, vol. 2, no. 5, pp. 102–119, 1960. View at Google Scholar · View at MathSciNet
  16. R. E. Kalman, “A new approach to linear filtering and prediction problems,” Transactions of the ASME. Series D: Journal of Basic Engineering, vol. 82, pp. 35–45, 1960. View at Google Scholar
  17. R. E. Kalman and R. S. Bucy, “New results in linear filtering and prediction theory,” Journal of Basic Engineering Series D, vol. 83, pp. 95–107, 1961. View at Google Scholar
  18. G. L. Smith, S. F. Schmidt, and L. A. McGee, “Application of statistical filter theory to the optimal estimation of position and velocity on board a circumlunar vehicle,” Tech. Rep. NASA TR R-135, National Aeronautics and Space Administration (NASA), Moffet Field, Calif, USA, 1962, https://archive.org/details/nasa_techdoc_19620006857. View at Google Scholar
  19. B. A. McElhoe, “An assessment of the navigation and course corrections for a manned flyby of mars or venus,” IEEE Transactions on Aerospace and Electronic Systems, vol. 2, no. 4, pp. 613–623, 1966. View at Publisher · View at Google Scholar
  20. Z. A. Jassim, N. N. Ali, F. Mustapha, and N. A. Abdul Jalil, “A review on the vibration analysis for a damage occurrence of a cantilever beam,” Engineering Failure Analysis, vol. 31, pp. 442–461, 2013. View at Publisher · View at Google Scholar · View at Scopus
  21. J. Richelot, J. B. Guibe, and V. P. Budinger, “Active control of a clamped beam equipped with piezoelectric actuator and sensor using generalized predictive control,” in Proceedings of the IEEE International Symposium on Industrial Electronics (ISlE '04), vol. 1, pp. 583–588, May 2004. View at Publisher · View at Google Scholar · View at Scopus
  22. H. Lu and G. Meng, “An experimental and analytical investigation of the dynamic characteristics of a flexible sandwich plate filled with electrorheological fluid,” The International Journal of Advanced Manufacturing Technology, vol. 28, no. 11-12, pp. 1049–1055, 2006. View at Publisher · View at Google Scholar · View at Scopus
  23. B. N. Agrawal and H. Bang, “Adaptive structures for large precision antennas,” Acta Astronautica, vol. 38, no. 3, pp. 175–183, 1996. View at Publisher · View at Google Scholar · View at Scopus
  24. M. Sabatini, P. Gasbarri, R. Monti, and G. B. Palmerini, “Vibration control of a flexible space manipulator during on orbit operations,” Acta Astronautica, vol. 73, pp. 109–121, 2012. View at Publisher · View at Google Scholar · View at Scopus
  25. Q. Hu, “A composite control scheme for attitude maneuvering and elastic mode stabilization of flexible spacecraft with measurable output feedback,” Aerospace Science and Technology, vol. 13, no. 2-3, pp. 81–91, 2009. View at Publisher · View at Google Scholar · View at Scopus
  26. E. Lourens, E. Reynders, G. De Roeck, G. Degrande, and G. Lombaert, “An augmented Kalman filter for force identification in structural dynamics,” Mechanical Systems and Signal Processing, vol. 27, no. 1, pp. 446–460, 2012. View at Publisher · View at Google Scholar · View at Scopus
  27. T. F. Mu, L. Zhou, and J. N. Yang, “Adaptive extended Kalman filter for parameter tracking of base-isolated structure under unknown seismic input,” in Proceedings of the 10th International Bhurban Conference on Applied Sciences and Technology (IBCAST '13), pp. 84–88, IEEE, Islamabad, Pakistan, January 2013. View at Publisher · View at Google Scholar · View at Scopus
  28. A. Turnip, K.-S. Hong, and S. Park, “Modeling of a hydraulic engine mount for active pneumatic engine vibration control using the extended Kalman filter,” Journal of Mechanical Science and Technology, vol. 23, no. 1, pp. 229–236, 2009. View at Publisher · View at Google Scholar · View at Scopus
  29. K. Szabat and T. Orlowska-Kowalska, “Adaptive control of two-mass system using nonlinear extended Kalman Filter,” in Proceedings of the 32nd Annual Conference on IEEE Industrial Electronics (IECON '06), pp. 1539–1544, November 2006. View at Publisher · View at Google Scholar · View at Scopus
  30. K. Szabat and T. Orlowska-Kowalska, “Application of the extended Kalman filter in advanced control structure of a drive system with elastic joint,” in Proceedings of the IEEE International Conference on Industrial Technology (ICIT '08), pp. 1–6, April 2008. View at Publisher · View at Google Scholar · View at Scopus
  31. P. Williams, “Structural damage detection from transient responses using square-root unscented filtering,” Acta Astronautica, vol. 63, no. 11-12, pp. 1259–1272, 2008. View at Publisher · View at Google Scholar · View at Scopus
  32. K. Erazo and E. M. Hernandez, “A model-based observer for state and stress estimation in structural and mechanical systems: experimental validation,” Mechanical Systems and Signal Processing, vol. 43, no. 1-2, pp. 141–152, 2014. View at Publisher · View at Google Scholar · View at Scopus
  33. G. Takács, T. Polóni, and B. Rohal'-Ilkiv, “Adaptive model predictive vibration control with state and parameter estimation using extended kalman filtering,” in Proceedings of the 20th International Congress on Sound and Vibration (ICSV '13), pp. 611/1–611/8, Bangkok, Thailand, July 2013. View at Scopus
  34. G. Takács, T. Polóni, and B. Rohal-Ilkiv, “Adaptive predictive control of transient vibrations in cantilevers with changing weight,” in Proceedings of the 19th World Congress of the International Federation of Automatic Control (IFAC '14), pp. 4739–4747, Cape Town, South Africa, August 2014.
  35. G. Takács and B. Rohal-Ilkiv, Model Predictive Vibration Control: Efficient Constrained MPC Vibration Control for Lightly Damped Mechanical Systems, Springer, London, UK, 2012.
  36. N. P. Jones, T. Shi, J. H. Ellis, and R. H. Scanlan, “System-identification procedure for system and input parameters in ambient vibration surveys,” Journal of Wind Engineering and Industrial Aerodynamics, vol. 54-55, pp. 91–99, 1995, Third Asian-Pacific Symposium on Wind Engineering. View at Google Scholar
  37. V. Namdeo and C. S. Manohar, “Nonlinear structural dynamical system identification using adaptive particle filters,” Journal of Sound and Vibration, vol. 306, no. 3–5, pp. 524–563, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  38. T. Polóni, A. A. Eielsen, T. A. Johansen, and B. Rohal-Ilkiv, “Adaptive model estimation of vibration motion for a nanopositioner with moving horizon optimized extended Kalman filter,” Journal of Dynamic Systems, Measurement and Control, vol. 135, no. 4, Article ID 041019, 2013. View at Publisher · View at Google Scholar · View at Scopus
  39. H. Benaroya and M. L. Nagurka, Mechanical Vibration: Analysis, Uncertainities and Control, CRC Press, Boca Raton, Fla, USA, 3rd edition, 2010.
  40. G. F. Franklin, J. D. Powell, and M. L. Workman, Digital Control of Dynamic Systems, Addison-Wesley, Boston, Mass, USA, 3rd edition, 1997.
  41. D. J. Inman, Vibration with Control, John Wiley & Sons, Chichester, UK, 2006.
  42. P. S. Maybeck, Stochastic Models, Estimation and Control, vol. 141 of Mathematics in Science and Engineering, Academic Press, New York, NY, USA, 1st edition, 1979.
  43. A. Gelb, Applied Optimal Estimation, The MIT Press, Cambridge, Mass, USA, 1974. View at MathSciNet
  44. D. Simon, Optimal State Estimation: Kalman, H1, and Nonlinear Approaches, Wiley-Interscience, Hoboken, NJ, USA, 1st edition, 2006.
  45. Z. Duan, C. Han, and H. Dang, “An adaptive Kalman filter with dynamic resealing of process noise,” in Proceedings of the 6th International Conference of Information Fusion, vol. 2, pp. 1310–1315, IEEE, Cairns, Australia, July 2003. View at Publisher · View at Google Scholar
  46. A. Khitwongwattana and T. Maneewarn, “Extended kalman filter with adaptive measurement noise characteristics for position estimation of an autonomous vehicle,” in Proceedings of the IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications (MESA '08), pp. 505–509, IEEE, Beijing, China, October 2008. View at Publisher · View at Google Scholar · View at Scopus
  47. V. A. Bavdekar, A. P. Deshpande, and S. C. Patwardhan, “Identification of process and measurement noise covariance for state and parameter estimation using extended Kalman filter,” Journal of Process Control, vol. 21, no. 4, pp. 585–601, 2011. View at Publisher · View at Google Scholar · View at Scopus
  48. G. Takács and B. Rohal-Ilkiv, “Real-time diagnostics of mechanical failure for thin active cantilever beams using low-cost hardware,” in Proceedings of the 7th Forum Acusticum, pp. 1–6, European Acoustics Association, Kraków, Poland, September 2014.
  49. Atmel Corporation, “Atmel ATmega640/V-1280/V-1281/V-2560/V-2561/V: 8-bit atmel microcontroller with 16/32/64KB,” in System Programmable Flash, Atmel Corporation, San Jose, Calif, USA, 2549q-avr-02/2014 edition, 2014, Datasheet. View at Google Scholar
  50. Atmel Corporation, ATmega48A/PA/88A/PA/168A/PA/328/P Complete: Atmel 8-Bit Microcontroller with 4/8/16/32KBytes In-System Programmable Flash, 8271g-avr-02/2013 edition, Datasheet, Atmel Corporation, San Jose, Calif, USA, 2013.
  51. Texas Instruments, C2000TM Real-Time Microcontrollers, sprb176s edition, Datasheet, Texas Instruments, Dallas, Tex, USA, 2014.
  52. Digi-Key Corporation, ATMEGA328P-PU Atmel ∣ ATMEGA328P-PU ∣ DigiKey, April 2014, http://www.digikey.com/product-detail/en/ATMEGA328P-PU/ATMEGA328P-PU-ND/1914589.