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井下粉尘多参数检测的自适应方法
引用本文:石广岩,赵永林.井下粉尘多参数检测的自适应方法[J].中国粉体技术,2004,10(4):9-12.
作者姓名:石广岩  赵永林
作者单位:1. 山东科技大学动力与控制工程学院,山东,济南,250031
2. 山东交通学院,信息工程系,山东,济南,250031
摘    要:为提高井下粉尘计重含量检测精度并同时获得粒度分布参数,根据井下粉尘衍射光的角谱特征,提出了一种适合于在单片机上运行的算法。首先将衍射光角谱归一化,使得不同浓度但粒度分布相同的尘样具有相同的归一化角谱,而该角谱与给定模式的角谱的贴近程度则用差值平方和表征。由几个优选模式求得的计重含量或粒度分布取加权平均即可获得待求参数。考虑到现场环境中噪声抑制能力和对尘样多样性的适应能力至关重要,本文中最后给出了针对这两个方面的仿真实验结果。

关 键 词:粉尘传感器  粒度检测  识别算法  衍射光角谱
文章编号:1008-5548(2004)04-0009-04

Self-adapt Method for Multi-parameter Detect of Coal Mine Dust
SHI Guang-yan,ZHAO Yong-lin.Self-adapt Method for Multi-parameter Detect of Coal Mine Dust[J].China Powder Science and Technology,2004,10(4):9-12.
Authors:SHI Guang-yan  ZHAO Yong-lin
Affiliation:SHI Guang-yan~1,ZHAO Yong-lin~2
Abstract:For the purposes of improving the detect precision of weight density and size distribution parameters of coal mine dust, based on the mathematical model of angular distribution coal mine dust diffraction and its feature, the algorithm suitable for single-chip computer is put forward. The light diffraction angular distribution is normalized to ensure that dust samples with the same size distribution will have the same angular distribution despite the difference of weight density. While the square sum of difference of angular distribution between the real-time dust sample and the known model represent the approaching degree of the two. Selecting several known models according to the degrees of approaching and using the weighed averages of these selected models, the parameters of dust are gained. To coal mine circumstances, anti-noise ability and adaptive ability to diverse dust samples are of great importance. The simulation results concerning these two aspects are obtained.
Keywords:coal mine dust sensor  detection of particle size  recognizing algorithm  angular distribution of diffraction
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