Neural-network-based method of calibration and measurand reconstruction for a high-pressure measuring system

IEEE Transactions on Instrumentation and Measurement

Volumn 47, Issue 2, 1998, Pages 362-370

  Massicotte, Daniel ^a,b   Legendre, Sylvie ^a,b   Barwicz, Andrzej ^a,b  

^a IEEE   (Canada)

^b UNIVERSITÉ DU QUÉBEC À TROIS RIVIÈRES   (Canada)

Author keywords

Algorithms; Calibration; Measurement; Microcontrollers; Neural networks; Optical fiber transducers; Signal reconstruction

Indexed keywords

ALGORITHMS; CALIBRATION; FIBER OPTIC SENSORS; MICROCONTROLLERS; MULTILAYER NEURAL NETWORKS; SIGNAL RECONSTRUCTION;

HIGH-PRESSURE MEASURING SYSTEMS;

PRESSURE MEASUREMENT;

EID: 0032035554     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/19.744175     Document Type: Article

References (17)

1. A. Barwiczand W. J. Bock, "An electronic high-pressure measuring system using a polarimetric fiber-optic sensor," IEEE Trans. Instrum. Meas., vol. 39, pp. 976-981,Dec. 1990.
2. W. J. Bockand A. W. Domanski, "High hydrostatic pressure effects in highly birefrengent optical fibers," J. Lightwave Technol., vol. 7, pp. 1279-1283, 1989.
3. A. Barwicz,R. Z. Morawski,L. Lemire,and W. J. Bock, "Calibration of an electronic multisensor system for measuring high pressures," IEEE Trans. Instrum. Meas., vol.39, pp. 269-273,Apr. 1990.
4. D. E. Rumelhartand J. L. McClelland, Parallel Distributed Processing.Cambridge, MA: MIT Press, 1986.
5. P. K. Simpson, "Foundations of neural networks," Artificial Neural Networks,E. Sànchez-Sinencio and C. Lau, Eds. New York: IEEE Press, 1992, pp. 3-24.
6. P. Simpson, Artificial Neural Systems: Foundations, Paradigms, Applications and Implementations.Elmsford, NY: Pergamon, 1990.
7. R. P. Lippmann, "An introduction to computing with neural nets," IEEE Acoust., Speech, Signal Processing Mag., pp.4-22,Apr. 1987.
8. J. de Villiersand E. Barnard, "Backpropagation neural nets with one and two hidden layers," IEEE Trans. Neural Networks, vol. 4, pp. 136-141,Jan. 1992.
9. S. Singhaland L. Wu, "Training feed-forward networks with the extended Kalman algorithm," in Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing,May 1989, pp.1187-1190.
10. T. Huang,M. Tsuyuki,and M. Yasuhara, "A learning algorithm of neural network based on Kalman filtering," IEICE Trans., vol.E74, no. 5, pp. 1059-1065, 1991.
11. R. S. Scaleroand N. Tepedelenlioglu, "A fast new algorithm for training feedforward neural networks," IEEE Trans. Signal Processing, vol. 40, pp. 102-210,Jan. 1992.
12. Y. liguni,H. Sakai,and H. Tokumaru, "A real-time learning algorithm for a multilayered neural network based on the extended Kalman filter," IEEE Trans. Signal Processing, vol. 40, pp. 959-966,Apr. 1992.
13. B. D. O. Andersenand J. B. Moore, Optimal Filtering.Englewood CLiffs, NJ: Prentice-Hall, 1979.
14. MATLAB, User's Guide,The MathWorks Inc., p. 3.173, 1989.
15. Motorola, M68HC11 Family Croos C Compiler User's Manual for MS-DOS/PC-DOS, Motorola Inc, 1990.
16. L. Lemire, "Static calibration of high-pressure measuring system using a fiber-optic sensor,"Master's thesis, Univ. Québec at Trois-Riviéres, 1994, in French.
17. S. Legendre, "Study of the application of multilayered neural networks for calibration and measurand reconstruction in a measuring system," Master's thesis, Univ. Québec at Trois-Riviéres, 1995, in French.