Improving Precision in Coal Moisture Detection Using Wavelet Transform
JIA Hao1, FU Qiang2, HAN Chan-juan3, ZOU De-bao1, CHEN Wen-liang1, 4*, XU Ke-xin1
1. State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China 2. Environment Monitoring Station of Jinnan District, Tianjin 300350, China 3. School of Environment Science and Engineering, Tianjin University, Tianjin 300072, China 4. Key Laboratory of Micro-Optical-Electro-Mechanical System Technology (Tianjin University), Ministry of Education, Tianjin 300072, China
Abstract：Moisture, as a core determination of the economic value of coal, can result in the utilization and energy inefficiency. Near-infrared (NIR) spectroscopy, with advantages of high accuracy and low cost, provides significant solution to the quick and non-invasive detection of coal moisture. In the present paper, the improvement of the coal moisture analysis was conducted based on the precision of 1% and insufficient comparisons in recent experiments, and aspects of spectrum pretreatment and wavelength selection were mainly discussed. The optimized result with R-square of 0.995, RMSEC of 0.06% and RMSEP of 0.27% indicates the priority of wavelet decomposition and reconstruction, compared with other methods, in the noise reduction and baseline removing of original spectra (1 300～2 400 nm) before PLS modeling, and the stability experiment validates its robust potential in improving precision of coal moisture detection based on the NIR spectroscopy.
Key words：Near-infrared spectroscopy;Wavelet decomposition and reconstruction;Partial least square (PLS) modeling
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