title: [Improving precision in coal moisture detection using wavelet transform].
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.
authors: State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China. jiahaocl@tju.edu.cn
authors: Hao
authors: H
authors: Jia
authors: Qiang
authors: Q
authors: Fu
authors: Chan-Juan
authors: CJ
authors: Han
authors: De-Bao
authors: DB
authors: Zou
authors: Wen-Liang
authors: WL
authors: Chen
authors: Ke-Xin
authors: KX
authors: Xu