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. C...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.展开更多
The successful return of lunar soil samples from the northern Oceanus Procellarum by the Chang’E 5(CE-5) mission has provided unprecedented ground-truth information for the previously unexplored region of the Moon. I...The successful return of lunar soil samples from the northern Oceanus Procellarum by the Chang’E 5(CE-5) mission has provided unprecedented ground-truth information for the previously unexplored region of the Moon. In particular, the particle size and mineral constituents of the CE-5 soil samples are of critical importance to interpret remote sensing data. With a Raman-based particle analysis system, we show that the particle size properties and mineral constituents of the CE-5 soil can be simultaneously determined with a small sample size(ca. 30 μg). The CE-5 sample scooped from the lunar surface has an overall small size between 0.4 μm and 73.9 μm(mean=3.5 μm), and mainly consists of pyroxene(39.4%), plagioclase(37.5%), olivine(9.8%), Fe-Ti oxides(1.9%), glass(8.3%) and other minor or trace phases. The results are consistent with previous analyses with larger sample sizes. In addition to minimum sample consumption, this method requires very little sample preparation, and can rapidly build a large database with each particle precisely traceable. Therefore, this novel technique is particularly suitable for the analysis of future returned soil samples from extraterrestrial bodies.展开更多
文摘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.
基金supported by the Pre-Research Project on Civil Aerospace Technologies funded by CNSA (Grant No. D020205)the National Natural Science Foundation of China (Grant No. 42172337)the Program of the State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences (Grant No. GBL12101)。
文摘The successful return of lunar soil samples from the northern Oceanus Procellarum by the Chang’E 5(CE-5) mission has provided unprecedented ground-truth information for the previously unexplored region of the Moon. In particular, the particle size and mineral constituents of the CE-5 soil samples are of critical importance to interpret remote sensing data. With a Raman-based particle analysis system, we show that the particle size properties and mineral constituents of the CE-5 soil can be simultaneously determined with a small sample size(ca. 30 μg). The CE-5 sample scooped from the lunar surface has an overall small size between 0.4 μm and 73.9 μm(mean=3.5 μm), and mainly consists of pyroxene(39.4%), plagioclase(37.5%), olivine(9.8%), Fe-Ti oxides(1.9%), glass(8.3%) and other minor or trace phases. The results are consistent with previous analyses with larger sample sizes. In addition to minimum sample consumption, this method requires very little sample preparation, and can rapidly build a large database with each particle precisely traceable. Therefore, this novel technique is particularly suitable for the analysis of future returned soil samples from extraterrestrial bodies.
