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The Wavelet Filtration Denoising in the Raman Distributed Temperature Sensing 14

The Wavelet Filtration Denoising in the Raman Distributed Te...

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14th IEEE International Scientific and Technical Conference on Dynamics of Systems, Mechanisms and Machines (Dynamics)

作者： Ershov, Ivan A. Stukach, Oleg, V Sychev, Igor, V Tsydenzhapov, Igor B. Novosibirsk State Tech Univ Novosibirsk Russia Natl Res Univ Higher Sch Econ Moscow Russia KEEPLINE R&D Novosibirsk Russia

ISBN: (纸本)9781728180960

Up to now a Distributed optical fiber Temperature Sensor (DTS) based on the Raman scattering exhibits a relatively low characteristic causes sharp temperature changes to be improved. Modeling metrological characteristics has a long history but essential progress did not achieved. This paper presents a novel technique of the extremal filtration developed to improve the DTS temperature and partially spatial resolution. The algorithm is based on wavelet transformation of backscattered anti-Stokes and Stokes signals and deconvolution on high-frequency components with total regularization of variations. Experimental results correctly agree with real modeling values with denoising ones. The advantage is the ability to reconstruct temperature with 0.01 degree accuracy at fixed spatial resolution. We present a lot of simulations and figures demonstrated the efficacy of the proposed technique.

关键词： fiber optical temperature sensor DTS spatial resolution measurement accuracy emd data processing Raman scattering observation of unsafe production

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The Resolution Enhancement in the Distributed Temperature Sensor with the Extremal Filtration Method 14

The Resolution Enhancement in the Distributed Temperature Se...

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14th IEEE International Scientific and Technical Conference on Dynamics of Systems, Mechanisms and Machines (Dynamics)

作者： Ershov, Ivan A. Stukach, Oleg, V Myasnikova, Nina, V Tsydenzhapov, Igor B. Sychev, Igor, V Novosibirsk State Tech Univ Novosibirsk Russia Natl Res Univ Higher Sch Econ Moscow Russia Penza State Univ Penza Russia KEEPLINE R&D Novosibirsk Russia

ISBN: (纸本)9781728180960

High resolution DTS research has sufficiently advanced. However further progress will be achieved due to mathematical techniques and algorithms. Novel mathematical algorithms can expand measurement traceability. Outcomes from discrete wavelet transformations are not sufficient for many practical applications. We propose the extremal filtration method as an analog of the empirical mode decomposition (emd) approach. Advantage of the extremal filtration is the simplification of mathematical calculations. The essence of the method is finding the moving average value of extremums with the continued removing of the highest frequency components from the signal, smoothing of the curve, and subsequent transformations. Difference between the modeling reference signal and signal with Gaussian noise as error of the method is very small: most of the samples (90 %) are within an interval of +/- 0.003. It is an excellent result for the low signal-to-noise ratio (SNR). However, significant short-term splashes of error (which can reach the value of 0.038) occurred during the transition process. The method can filter low-SNR DTS signals. We expect that the extremal filtration of one target signal is much more effective than a simple averaging of many target OTDR pulses often used in practice. Also, this method can be customized for specific problems connected with subtracting the high-frequency components from the signal. This expands the field of use for the method.

关键词： fiber optical temperature sensor DTS spatial resolution measurement accuracy emd data processing Raman scattering observation of unsafe production

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