LS-SVM算法在近红外光谱煤质分析中的应用  

Application of LS-SVM Algorithm in Coal Quality Indicators Prediction Using Near-Infrared Spectroscopy

作　　者：王帅[1] 张云佳[1] 王雪梅[1] 乔建仙[1] 

机构地区：[1]解放军后勤工程学院化学与材料工程系,重庆401331

出　　处：《计算机系统应用》2017年第5期232-238,共7页Computer Systems & Applications

基　　金：2015重庆市基础与前沿研究计划(cstc2015jcyjA100009);2014解放军后勤工程学院青年基金

摘　　要：针对目前电力行业煤质分析的需求,提出了基于Hadamard近红外光谱的煤质分析技术,对Hadamard近红外光谱仪研制、控制分析软件设计、煤炭光谱信号采集、指标特征信息提取、定量模型建立五个环节综合考虑,研发了Hadamard近红外煤质分析系统.研究中,对41个不同质量指标的标准煤样进行了定量分析预测,考察了在相同粒径的条件下Hadamard近红外光谱对煤炭指标的预测能力,提出了基于ICA+LS-SVM算法的的煤炭指标预测方法,光谱数据与煤炭指标具有很好的相关性,相关系数普遍在0.9以上,取得了较好预测效果.In order to meet the demand of coal quality analysis in power industry, this paper proposes a new technology of coal analysis based on Hadamard near infrared spectroscopy. On the basis of comprehensive consideration of five aspects, such as development of near infrared spectrometer, the design of control and analysis software, the acquisition of coal spectral signal, the extraction of characteristic information and the establishment of quantitative model, the Hadamard near infrared coal quality analysis system is developed. In the study, 41 standard coal samples with different quality indicators are quantitatively analyzed and predicted. The ability of Hadamard near infrared spectroscopy to predict coal indicators in conditions of same particle size is investigated. Based on LS-SVM algorithm, a coal indicators prediction method is proposed, which has a good correlation with the coal index, and the correlation coefficients is above 0.9.

关 键 词：近红外光谱 煤质分析 HADAMARD变换 最小二乘支持向量机 快速检测 

分 类 号：TH744.1[机械工程—光学工程] TP18[机械工程—仪器科学与技术]