Wireless Sensor Network Microcantilever Data Processing using Principal Component and Correlation Analysis

Viktor Zaharov, Angel Lambertt, Ali Passian

2016

Abstract

One of the main purpose of the wireless sensor network is an identification of unknown physical, chemical and biological agents in monitoring area. It requires the measurement of the microcantilever sensor resonance frequencies with high precision. However, resolving the weak spectral variations in dynamic response of materials that are either dominated or excited by stochastic processes remains a challenge. In this paper we present the analysis and experimental results of the resonant excitation of a microcantilever sensor system (MSS) by the ambient random fluctuations. In our analysis, the dynamic process is decomposed into the bases of orthogonal functions with random coefficients using principal component analysis (PCA) and Karhunen- Lo`eve theorem to obtain pertinent frequency shifts and spectral peaks. We show that using the truncated Karhunen-Lo`eve Transform helps significantly increase the resolution of resonance frequency peaks compared to those obtained with conventional Fourier Transform processing.

References

  1. Ahmed, N. and Rao, K. (1975). Orthogonal transforms for digital signal processing. Springer-Verlag.
  2. Albrecht, T. R., Grtitter, P., Horne, D., and Rugar, D. (1991). Frequency modulation detection using highdkantilevers for enhanced force microscope sensitivity. J. Appl. Phys., 69(2).
  3. Bengtsson, M., Gr önlund, R., Lundqvist, M., Larsson, A., Kr öll, S., and Svanberg, S. (2006). Remote laserinduced breakdown spectroscopy for the detection and removal of salt on metal and polymeric surfaces. Applied Spectroscopy, 60:1188-1191.
  4. Buchapudi, K. R., Huang, X., Yang, X., Ji, H. F., and Thundat, T. (2011). Microcantilever biosensors for chemicals and bioorganisms. Analyst, (136(8)):1539-1556.
  5. Dada, O. O. and Bialkowski, S. E. (2011). A compact, pulsed infrared laser-excited photothermal deflection spectrometer. Applied Spectroscopy, 65(2):201-205.
  6. Farahi, R. H., Passian, A., Jones, Y. K., Tetard, L., Lereu, A. L., and Thundat, T. G. (2012). Pumpprobe photothermal spectroscopy using quantum cascade lasers. Journal of Physics D, 45:125101.
  7. Karhunen, K. (1947). Über lineare methoden in der wahrscheinlichkeitsrechnung. Ann. Acad. Sci. Fennicae, Ann. Acad. Sci. Fennicae. Ser. A. I. Math.- Phys.(37):1-79.
  8. Kawakatsu, H., Kawai, S., Saya, D., Nagashio, M., Kobayashi, D., Toshiyoshi, H., and Fujita, H. (2002). Towards atomic force microscopy up to 100 MHz. Review of Scientific Instrument, 73(2317).
  9. Kendall, M. G., Stuart, A., and Ord, J. K. (1977). The advanced theory of statistic. Griffin.
  10. Konstantinides, K. and Yao, K. (1988). Statistical analysis of effective singular values in matrix rank determination. Acoustics, Speech and Signal Processing, IEEE Transactions on, 36(5):757 - 763.
  11. Labuda, A., Bates, J. R., and Gr ütter, P. H. (2012). The noise of coated cantilevers. Nanotechnology, 23(025503).
  12. Loève, M. (1978). Probability theory. Graduate Texts in Mathematics, volume 2. Springer-Verlag, 4th edition.
  13. Lozano, J. and Garcia, R. (2009). Theory of multifrequency atomic force microscopy. Phys. Rev. B, 79(014110).
  14. Maccone, C. (2009). Deep Space Flight And Communication. Springer.
  15. Marple, S. L. (1987). Digital Spectral Analysis with Application. Prentice-Hal.
  16. Measures, R. M. (1984). Laser Remote Sensing: Fundamentals and Applications. Wiley-Interscience.
  17. Mokrane, B. and et al (2012). Study of thermal and acoustic noise interferences in low stiffness atomic force microscope cantilevers and characterization of their dynamic properties. Review of Scientific Instruments, 83(1).
  18. Parmeter, J. E., editor (2004). The challenge of standoff explosives detection. 0-7803-8506-3/02. IEEE.
  19. Passian, A., Lereu, A. L., Yi, D., Barhen, S., and Thundat, T. (2007). Stochastic excitation and delayed oscillation of a micro-oscillator. Physical Review B, 75:233403.
  20. Reed, I. S. and Lan, L.-S. (1994). A fast approximate karhunen-loève transform (aklt) for data compression. Journal of Visual Communication and Image Representation, 5:304-316.
  21. Sakamoto, Y., Ishiguro, M., and Kitagawa, G. (1986). Akaike Information Criterion Statistics. Springer.
  22. Van Neste, C. W., Senesac, L. R., and Thundat, T. (2009). Standoff spectroscopy of surface adsorbed chemicals. Analytical Chemistry, 81(5):1952-1956.
  23. Wang, R. (2012). Introduction to Orthogonal Transforms: With Applications in Data Processing and Analysis. Cambridge University Press.
  24. Wig, A., Arakawa, E. T., Passian, A., Ferrell, T. L., and Thundat, T. (2006). Photothermal spectroscopy of bacillus anthracis and bacillus cereus with microcantilevers. Sensors and Actuators B, 114:206.
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Paper Citation


in Harvard Style

Zaharov V., Lambertt A. and Passian A. (2016). Wireless Sensor Network Microcantilever Data Processing using Principal Component and Correlation Analysis . In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 6: WINSYS, (ICETE 2016) ISBN 978-989-758-196-0, pages 97-105. DOI: 10.5220/0005933200970105


in Bibtex Style

@conference{winsys16,
author={Viktor Zaharov and Angel Lambertt and Ali Passian},
title={Wireless Sensor Network Microcantilever Data Processing using Principal Component and Correlation Analysis},
booktitle={Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 6: WINSYS, (ICETE 2016)},
year={2016},
pages={97-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005933200970105},
isbn={978-989-758-196-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Joint Conference on e-Business and Telecommunications - Volume 6: WINSYS, (ICETE 2016)
TI - Wireless Sensor Network Microcantilever Data Processing using Principal Component and Correlation Analysis
SN - 978-989-758-196-0
AU - Zaharov V.
AU - Lambertt A.
AU - Passian A.
PY - 2016
SP - 97
EP - 105
DO - 10.5220/0005933200970105