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Abstract
Coal spontaneous combustion risk assessment is a global technical challenge for the sustainable development of deep mining technology, and C2H4 is a key indicator for early warning of coal spontaneous combustion. Tunable diode laser absorption spectroscopy (TDLAS) has the advantages of high selectivity, high sensitivity, high accuracy and real-time on-line measurement, and it can detect multiple gases simultaneously, so it has significant advantages in the accurate detection of coal spontaneous combustion indicator gases. To address the problem of cross-interference between the near-infrared absorption lines of CH4 and C2H4, which are the indicator gases of spontaneous combustion in coal, a multi-line fitting method was proposed in this study to calibrate the concentration of C2H4. The high-precision Environics2000 automatic standard gas dispenser from the United States, which has a built-in CPU computer control and data control and processing system, was used. Its gas concentration accuracy: ± 1.0%, gas flow accuracy: ± 1.0%, gas repeatability accuracy: ± 1.0%, flow linearity accuracy: ± 0.5%, and inlet operating pressure: minimum 10 psig (0.67 bar) ~ 75 psig (5.04 bar). The measured and simulated WMS-2f/1f signals were multilinearly fitted using a multilinear fitting algorithm and wavelength modulation spectroscopy (WMS), and the measurement of C2H4 concentration was achieved based on the extracted spectral line information. The results show that the maximum relative error of C2H4 concentration measurement is 2.40%, which is 54% lower than that of the conventional 2f peak measurement method, thus demonstrating the effectiveness of the multilinear fitting algorithm in the inversion of C2H4 concentration under the interference of absorption lines. In addition, this study has far-reaching implications for the application of TDLAS technology in the accurate detection of coal spontaneous combustion indicator gases.
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Details
1 Xi’an University of Science and Technology, School of Safety Science and Engineering, Xi’an, China (GRID:grid.440720.5) (ISNI:0000 0004 1759 0801); Xi’an University of Science and Technology, Key Laboratory of Mine and Disaster Prevention and Control of Ministry of Education, Xi’an, People’s Republic of China (GRID:grid.440720.5) (ISNI:0000 0004 1759 0801)