| 基于支持向量机的矿浆管道堵塞信号识别方法 |
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| 引用本文： | 马帅,王晓东,吴建德,范玉刚,黄国勇.基于支持向量机的矿浆管道堵塞信号识别方法[J].江南学院学报,2013(5):571-575. |
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| 作者姓名： | 马帅 王晓东 吴建德 范玉刚 黄国勇 |
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| 作者单位： | [1]昆明理工大学信息工程与自动化学院,云南昆明650500 [2]云南省矿物管道输送工程技术研究中心,云南昆明650500 |
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| 基金项目： | 国家自然科学基金项目（51169007）;云南省科技计划项目（2011DA005 ＆ 2012CA022）;云南省中青年学术和技术带头人后备人才培养计划项目（2011CI017）. |
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| 摘 要： | 针对传统统计学理论的局限性,提出一种基于支持向量机的矿浆管道堵塞信号识别方法.该方法可以有效地识别矿浆管道中压力信号、流量信号的异常,通过分析压力信号、流量信号的异常从而准确识别堵塞信号.对于矿浆管道堵塞发生的早期发现起到一个很好的预警效果.研究结果表明,该方法分类效果好,泛化能力强,在识别正确率上优于径向基核函数人工神经网络方法,为矿浆管道安全生产监测提供了可靠的理论支持.
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| 关 键 词： | 管道堵塞监测 矿浆管道安全 压力信号 支持向量机 |
Support Vector Machine Based Recognition Method for Pipeline Blockage |
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| MA Shuai;WANG Xiao-dong;WU Jian-de;FAN Yu-gang;HUANG Guo-yong.Support Vector Machine Based Recognition Method for Pipeline Blockage[J].Journal of Jiangnan College,2013(5):571-575. |
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| Authors: | MA Shuai;WANG Xiao-dong;WU Jian-de;FAN Yu-gang;HUANG Guo-yong |
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| Institution: | MA Shuai;WANG Xiao-dong;WU Jian-de;FAN Yu-gang;HUANG Guo-yong(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500, China;Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500, China ;Engineering Research Center for Mineral Pipeline Transportation Yunnan, Kunming 650500, China) |
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| Abstract: | An SVM-based recognition method is discussed for the blockage of slurry pipelines.The method can effectively identify slurry pipeline pressure signal abnormalities,by analyzing the pressure signals to accurately identify the blockage signals,and can give an early warning for slurry pipeline clogging.The research results show that the proposed method has better classification performance and generalization ability,provide support for the slurry pipeline safety production monitoring. |
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| Keywords: | pipeline blockage detection safety of slurry pipeline pressure signal support vector machines |
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