Spectroscopy and Spectral Analysis, Volume. 32, Issue 11, 3010(2012)
Improving Precision in Coal Moisture Detection Using Wavelet Transform
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.
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JIA Hao, FU Qiang, HAN Chan-juan, ZOU De-bao, CHEN Wen-liang, XU Ke-xin. Improving Precision in Coal Moisture Detection Using Wavelet Transform[J]. Spectroscopy and Spectral Analysis, 2012, 32(11): 3010
Received: May. 17, 2012
Accepted: --
Published Online: Nov. 22, 2012
The Author Email: Hao JIA (jiahaocl@tju.edu.cn)