Neural-network-based robust linearization and compensation technique for sensors under nonlinear environmental influences

IEEE Transactions on Circuits and Systems I: Regular Papers

Volumn 55, Issue 5, 2008, Pages 1316-1327

  Patra, Jagdish Chandra ^a   Chakraborty, Goutam ^b   Meher, Pramod Kumar ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b IWATE PREFECTURAL UNIVERSITY   (Japan)

Author keywords

Artificial neural networks (NNs); Auto compensation; Harsh environment; Intelligent and smart sensors; Linearization; Pressure sensor

Indexed keywords

CAPACITIVE SENSORS; LINEARIZATION; MULTILAYER NEURAL NETWORKS; MULTILAYERS; PRESSURE SENSORS; SMART SENSORS; TEMPERATURE;

AUTO COMPENSATIONS; CAPACITIVE PRESSURE SENSORS; COMPENSATION TECHNIQUES; COMPUTATIONALLY EFFICIENT; ENVIRONMENTAL INFLUENCES; EXTREME LEARNING MACHINE; HARSH ENVIRONMENT; RESPONSE CHARACTERISTIC;

LEARNING SYSTEMS;

EID: 45549097966     PISSN: 10577122     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCSI.2008.916617     Document Type: Article

References (31)

1. F. M. L. van der Goes and G. C. M. Meijer, "A simple accurate bridgetransducer interface with continuous autocalibration," IEEE Trans. Instrum. Meas., vol. 46, no. 3, pp. 704-710, Jun. 1997.
2. X. Li and G. C. Meijer, "An accurate interface for capacitive sensors," IEEE Trans. Instrum. Meas., vol. 51, no. 5, pp. 935-939, Oct. 2002.
3. M. Yamada, T. Takebayashi, S.-I. Notoyama, and K. Watanabe, "A switched-capacitor interface for capacitive pressure sensors," IEEE Trans. Instrum. Meas., vol. 41, no. 1, pp. 81-86, Feb. 1992.
4. M. Yamada and K. Watanabe, "A capacitive pressure sensor interface using oversampling Δ - Σ demodulation techniques," IEEE Trans. Instrum. Meas., vol. 46, no. 1, pp. 3-7, Feb. 1997.
5. P. Hille, R. Hohler, and H. Strack, "A linearization and compensation method for integrated sensors," Sens. Actuat.s - B, vol. 44, pp. 95-102, 1994.
6. A. M. Sabatini, "A digital signal-processing technique for compensating ultrasonic sensors," IEEE Trans. Instrum. Meas., vol. 46, no. 4, pp. 869-874, Aug. 1995.
7. I. Maric, "Automatic digital correction of measurement data based on M-point autocalibration and inverse polynomial approximation," IEEE Trans. Ind. Electron., vol. 35, no. 2, pp. 317-322, May 1988.
8. K. F. Lyahou, G. van der Horn, and J. H. Huijsing, "A noniterative polynomial 2-D calibration method implemented in a microcontroller," IEEE Trans. Instrum. Meas., vol. 46, no. 4, pp. 752-757, Aug. 1997.
9. X. Li, G. C. Meijer, and G. W. de Jong, "A microcontroller-based self-calibration technique for a smart capacitance angular-position sensor," IEEE Trans. Instrum. Meas., vol. 46, no. 4, pp. 888-892, Aug. 1997.
10. X. Li, M. Bao, and S. Shen, "Study on linearization of capacitive pressure sensors," Sens. Actuat.s A, vol. 63, pp. 1-6, 1997.
11. S. Poussier, H. Rabah, and S. Weber, "Adaptable thermal compensation system for strain gause sensors based on programmable chip," Sens. Actuat.s A, vol. 119, pp. 412-417, 2005.
12. J. M. Dias Pereira, O. Postolache, and P. Silva Girao, "Adaptive self-calibration algorithm for smart sensors linearization," in Proc. IEEE Instrum. Meas. Technol. Conf. (IMTC 2005), Ottawa, ON, Canada, May 2005.
13. S. Haykin, Neural Networks. Ontario, Canada: Maxwell MacMillan, 1994.
14. L. F. Pau and F. S. Johansen, "Neural network signal understanding for instrumentation," IEEE Trans. Instrum. Meas., vol. 39, no. 4, pp. 558-564, Aug. 1990.
15. P. Daponte and D. Grimaldi, "Artificial neural networks in measurements," Measurement, vol. 23, pp. 93-115, 1998.
16. J. M. Dias Pereira, P. M. B. Silva Girao, and O. Postolache, "Fitting transducer characteristics to measured data," IEEE Instrum. Meas. Mag., pp. 26-39, Dec. 2001.
17. R. Z. Morawski, "Digital signal processing in measurement microsystems," IEEE Instrum. Meas. Mag., pp. 43-50, Jun. 2004.
18. A. P. Singh, S. Kumar, and T. S. Kamal, "Fitting transducer characteristics to measured data using a virtual curve tracer," Sens. Actuat. A, vol. 111, pp. 145-153, 2004.
19. J. C. Patra, A. C. Kot, and G. Panda, "An intelligent pressure sensor using neural networks," IEEE Trans. Instrum. Meas., vol. 49, no. 4, pp. 829-834, Aug. 2000.
20. J. C. Patra, A. van den Bos, and A. C. Kot, "An NN-based smart capacitive pressure sensor in dynamic environment," Sens. Actuat. B vol. 86, pp. 26-38, 2000.
21. J. C. Patra, E. L. Ang, N. S. Chaudhari, and A. Das, "Neural- networkbased smart sensor framework operating in a harsh environment," J. Appl. Signal Process., vol. 4, pp. 558-574, 2005.
22. J. M. Dias Pereira, O. Postolache, and P. M. B. Girao, "A temperature compensated system for magnetic field measurements based on artificial neural networks," IEEE Trans. Instrum. Meas., vol. 47, no. 2, pp. 494-498, Apr. 1998.
23. A. Carullo, F. Ferraris, S. Graziani, U. Grimaldi, and M. Parvis, "Ultrasonic distance sensor improvement using a two-level neural networks," IEEE Trans. Instrum. Meas., vol. 45, no. 4, pp. 677-682, Apr. 1996.
24. P. Arpaia, P. Daponte, D. Grimaldi, and L. Michaeli, "ANN-based error reduction for experimentally modeled sensors," IEEE Trans. Instrum. Meas., vol. 51, no. 1, pp. 23-30, Feb. 2002.
25. A. P. Singh, S. Kumar, and T. S. Kamal, "Development of ANN-based virtual fault detector for Wheatstone bridge-oriented transducer," IEEE Sensors J., vol. 5, pp. 1043-1049, Oct. 2005.
26. A. P. Singh, S. Kumar, and T. S. Kamal, "Virtual compensator for correcting the disturbing variable effect in transducers," Sens. Actuat. A, vol. 116, pp. 1-9, 2004.
27. N. J. Medrano-Marques and B. Martin-del-Brio, "Sensor linearization with neural networks," IEEE Trans. Ind. Electron., vol. 48, no. 6, pp. 1288-1290, Dec. 2001.
28. G.-B. Huang, Q.-Y. Zhu, and C.-K. Siew, "Extreme learning machine: Theory and applications," Neurocomp., vol. 70, pp. 489-501, 2006.
29. G.-B. Huang, Q.-Y. Zhu, and C.-K. Siew, "Real-time learning capability of neural networks," IEEE Trans. Neural Netw., vol. 17, no. 4, pp. 863-878, Jul. 2006.
30. G.-B. Huang, L. Chen, and C.-K. Siew, "Universal approximation using incremental constructive feedforward networks with random hidden nodes," IEEE Trans. Neural Netw., vol. 17, no. 4, pp. 879-892, Jul. 2006.
31. N.-Y. Liang, G.-B. Huang, P. Saratchandran, and N. Sundararajan, "A fast and accurate online sequential learning algorithm for feedforward networks," IEEE Trans. Neural Netw., vol. 17, no. 6, pp. 1141-1423, Nov. 2006