Signal Processing of Fluorescent Optical Fiber Temperature Measurement Based on Hilbert-Huang Transform

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The technology of fluorescent optical fiber temperature measurement has been used in many fields to accurately measure the variations of temperature, especially in some extreme environment, such as strong electromagnetic interference under, high voltage conditions. Wavelet analysis is the most frequent method used for signal processing in this technology. This method has excellent local characteristics and its precise of processing is high, whereas its result relies heavily on the selection of the wavelet basis, and has certain limitation. In this paper, a novel approach for fluorescent signal processing based on Hilbert-Huang transform is presented. A given signal is decomposed into a collection of intrinsic mode functions (IMF) by empirical mode decomposition, then Hilbert spectral analysis is performed for each of the IMF. According to the difference of signal and noise characteristics, HHT can generate adaptive modal functions and remove the noise from signal effectively, so that the signal to noise ratio can be improved. The result of experiment shows that HHT features convenient usage, fast processing and high resolution in time and frequency domains.

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447-453

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October 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] K.T.V. Grattan, A.W. Palmer, Z.Y. Zhang: Development of a High Temperature Fiber-optic Thermometer Probe Using Fluorescence Decay. Sci. Vol. 62(1991), p.1210.

DOI: 10.1063/1.1142001

Google Scholar

[2] W.M. Sun, J.Z. Zhang, Y. Lei: Measurment of decay time based on FFT. Optical & Laser Technology. Vol. 36(2004), No. 4, p.323.

Google Scholar

[3] Y. T Wang, L.K. Geng: Fluorescent Temperature Measuring System Based on the Theory of Sampling Points and Chaos. Acta Metrologica Sinica. Vol. 28(2007), p.103. (In Chinese).

Google Scholar

[4] S.T. Wang, R.S. Che, D.S. Wang: Sapphire Fluorescence Optical Fiber Thermometer Based on Wavelet Transform. Applied Optics. Vol. 27(2008), p.432. (In Chinese).

Google Scholar

[5] J. G Song, S.H. Lin, C.X. Zhaol, in: Business Management and Electronic Information. (Institute of Electrical and Electronics Engineers, Guang Zhou 2011), p.813.

Google Scholar

[6] B. Liu, S. Riemenschneider: Gearbox Fault Diagnosis Using Empirical Mode Decomposition and Hilbert Spectrum. Mechanical Systems and Signal Processing. Vol. 20(2006), p.718.

DOI: 10.1016/j.ymssp.2005.02.003

Google Scholar

[7] Ozgonenel Okan, Karagol Serap: A novel transformer protection method based on Hilbert Huang Transform and Artificial Neural Network. Electrical and Electronics Engineering. (2013), p.225.

DOI: 10.1109/eleco.2013.6713836

Google Scholar

[8] Z.K. Peng, P. W, Tse, F.L. Chu: A Comparison Study of Improved Hilbert-Huang Transform and Wavelet Transform: Application to Fault Diagnosis for Rolling Bearing. Mechanical Systems and Signal Processing. Vol. 19(2005), p.974.

DOI: 10.1016/j.ymssp.2004.01.006

Google Scholar

[9] J. D Zhu, C. F Lin, in: Advanced Materials Research. (Trans Tech Publications, Switzerland 2012). Vol. 461, p.411.

Google Scholar

[10] X. Li, L.G. Zhang, Y.L. Wang: Bio-medical Temperature Measurement System Based on Fiber Fluorescence and Wavelet Analysis. Chinese Journal of Sensors and Actuators. Vol. 1(2003), p.88. (In Chinese).

Google Scholar

[11] Z. Wu, N.E. Huang: Ensemble Empirical Mode Decomposition: a Noise-assisted Data Analysis Method. Advances in Adaptive Data Analysis. Vol. 1(2009), p.1.

DOI: 10.1142/s1793536909000047

Google Scholar

[12] Z.K. Peng, P.W. Tseb: AnIimproved Hilbert-Huang Transform and Its Application in Vibration Signal Analysis. Journal of Sound and Vibration. Vol. 286(2005), p.187.

DOI: 10.1016/j.jsv.2004.10.005

Google Scholar

[13] Y.L. Wang, P. Cai, J.Y. Hui: Estimating the Azimuth of an Instantaneous Signal by Using Hilbert-Huang Transform with a Vector Sensor. Journal of Harbin Engineering University, Vol. 29(2008), No. 3, p.256.

Google Scholar