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RDTS noise reduction: A fast method study based on signal waveform type

机译:RDTS noise reduction: A fast method study based on signal waveform type

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摘要

In order to reduce the measurement error of Raman-based distributed temperature sensor (RDTS) caused by random noise, we have proposed an effective noise reduction method, which can reduce the time consumption of data processing due to the low time complexity of the method. We classified the signal as five models based on the waveform types, thus to filter the raw data according to the waveform types. Then, we established an experimental device to test the effects of different signal noise reduction methods, including maximum deviation (MD), root mean square error (RMSE), smoothness, and time consumption. Experimental results show that it can efficiently suppress random noise and reduce temperature measurement errors in RDTS compared with direct demodulation of the raw data, and significantly improve the curve smoothness compared with D-SVD and WT-Soft. The time consumption test based on three different devices shows that the time consumption of the pro-posed method is approximately 10 of the D-SVD method, and about 30 of the WT-Soft method. It proves that this method is an effective and fast noise reduction method in RDTS systems.

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