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Research on Noise Reduction Approach of Raman-Based Distributed Temperature Sensor Based on Nonlinear Filter

机译:基于非线性滤波的拉曼分布式温度传感器降噪方法研究

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The accuracy of temperature measurement is often reduced due to random noise in Raman-based distributed temperature sensor (RDTS). A noise reduction method based on a nonlinear filter is thus proposed in this paper. Compared with the temperature demodulation results of raw signals, the proposed method in this paper can reduce the average maximum deviation of temperature measurement results from 4.1°C to 1.2°C at 40.0°C, 50.0°C and 60.0°C. And the proposed method in this paper can improve the accuracy of temperature measurement of Raman-based distributed temperature sensor better than the commonly used wavelet transform-based method. The advantages of the proposed method in improving the accuracy of temperature measurement for Raman-based distributed temperature sensor are quantitatively reflected in the maximum deviation and root mean square error of temperature measurement results. Therefore, this paper proposes an effective and feasible method to improve the accuracy of temperature measurement results for Raman-based distributed temperature sensor.
机译:由于基于拉曼的分布式温度传感器(RDTS)中的随机噪声,温度测量的准确性通常会降低。因此,本文提出了一种基于非线性滤波器的降噪方法。与原始信号的温度解调结果相比,本文提出的方法可以将温度测量结果的平均最大偏差在40.0°C,50.0°C和60.0°C下从4.1°C减小到1.2°C。并且,与常用的基于小波变换的方法相比,本文提出的方法可以更好地提高基于拉曼的分布式温度传感器的温度测量精度。所提出的方法在提高基于拉曼的分布式温度传感器的温度测量精度方面的优势被定量地反映在温度测量结果的最大偏差和均方根误差上。因此,本文提出了一种有效,可行的方法来提高基于拉曼的分布式温度传感器的温度测量结果的准确性。

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