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近红外光谱灰分预测模型中煤炭样本的优化方法 被引量:12
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作者 赵凯 雷萌 《工矿自动化》 北大核心 2012年第9期35-38,共4页
针对近红外光谱灰分预测模型中样本数据特有的问题,首先采用主成分分析方法剔除建模样本集中的异常样本,并提取出煤炭光谱的特征信息;然后提出一种集成自组织映射神经网络和模糊C均值聚类算法的双层聚类方法,将样本集分为5个子集,并滤... 针对近红外光谱灰分预测模型中样本数据特有的问题,首先采用主成分分析方法剔除建模样本集中的异常样本,并提取出煤炭光谱的特征信息;然后提出一种集成自组织映射神经网络和模糊C均值聚类算法的双层聚类方法,将样本集分为5个子集,并滤除其中的争议点;最后搭建基于GA-BP神经网络的煤炭灰分预测子模型,单独分析各子集的测试集样本。实验结果表明,基于主成分分析和双层聚类方法的煤炭样本优化方法不仅能准确排除异常样本和可疑样本,还能有效地压缩样本数据,使得各子模型的学习精度和运算速度得到显著提高。该方法为近红外光谱煤质分析技术的发展应用提供了一种有效可行的新途径。 展开更多
关键词 煤质分析 煤炭灰分 煤炭样本优化 灰分预测模型 近红外光谱分析 煤炭光谱特征 双层聚类方法
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Spectral characteristics of micro-seismic signals obtained during the rupture of coal 被引量:2
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作者 Liu jikun Li Chengwu +2 位作者 Wang Cuixia Zhang Ruming Zhang Hao 《Mining Science and Technology》 EI CAS 2011年第5期641-645,共5页
This study was performed to investigate the spectral characteristics of micro-seismic signals observed during the rupture of coal. Coal rupture micro-seismic observations were obtained on a test system that included a... This study was performed to investigate the spectral characteristics of micro-seismic signals observed during the rupture of coal. Coal rupture micro-seismic observations were obtained on a test system that included an electro-hydraulic servo pressure tester controlled by a YAW microcomputer, a micro-seismic sensor, a loading system, and a signal collection system. The results show that the micro-seismic signal increases with increasing compressive stress at the beginning of coal rupture. The signal remains stable for a period at this stage. A large number of micro-seismic signals appear immediately before the main rupture event. The frequency of micro-seismic events reaches a maximum immediately after the coal ruptures. Micro-seismic signals were decomposed into several Intrinsic Mode Functions (IMF's) by the empirical mode decomposition (EMD) method using a Hilbert-Huang transform (HHT). The main fre- quency band of the micro-seismic signals was found to range from 10 to 100 Hz in the Hilbert energy spectrum and from marginal spectrum calculations. The advantage of applying an HHT is that this can extract the main features of the signal. This fact was confirmed by an HHT analysis of the coal micro-seis- mic signals that shows the technique is useful in the field of coal rupture. 展开更多
关键词 CoalRuptureMicro-seismic signalSpectrum characteristic
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