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计算机工程 ›› 2011, Vol. 37 ›› Issue (17): 223-226. doi: 10.3969/j.issn.1000-3428.2011.17.075

• 工程应用技术与实现 • 上一篇    下一篇

多维相空间下提升机故障时序特征分析

刘晓明1,王学俊2,张长青2,牛 强1   

  1. (1. 中国矿业大学计算机科学与技术学院,江苏 徐州 221116; 2. 开滦集团荆各庄矿业分公司,河北 唐山 063022)
  • 收稿日期:2011-03-23 出版日期:2011-09-05 发布日期:2011-09-05
  • 作者简介:刘晓明(1987-),男,硕士研究生,主研方向:数据挖掘,混沌时间序列;王学俊、张长青,高级工程师;牛 强,副教授、博士
  • 基金资助:
    国家自然科学基金资助项目(50674086)

Hoister Fault Time Series Feature Analysis Under Multi-dimension Phase Space

LIU Xiao-ming 1, WANG Xue-jun 2, ZHANG Chang-qing 2, NIU Qiang 1   

  1. (1. School of Computer Science & Technology, China University of Mining and Technology, Xuzhou 221116, China; 2. JGZ Mining Company of Kailuan Group, Tangshan 063022, China)
  • Received:2011-03-23 Online:2011-09-05 Published:2011-09-05

摘要: 针对矿井提升机故障时间序列的非线性特性,对提升机故障时间序列进行多维相空间重构,基于混沌理论并应用最大Lyapunov指数法和广义关联维数法对提升机故障时间序列进行特征分析,从而实现提升机的故障诊断。研究结果表明,矿井提升机故障时间序列具有混沌特征,提取的最大Lyapunov指数和广义关联维数可作为提升机故障诊断的特征量。

关键词: 混沌特性, 矿井提升机, 多维相空间重构, 最大Lyapunov指数, 广义关联维数

Abstract: Aiming at the complex nature of the nonlinear existing in mine hoist fault time series, this paper uses the phase space reconstruction method to reconstruct the multi-dimension phase space for mine hoister fault time series. Based on chaos theory, the correlation dimension and the largest Lyapunov exponents are applied to analyze the features of mine hoist fault time series to realize the fault diagnosis for hoister. Research results show that mine hoist fault time series possesses chaotic characteristics, and the calculated correlation dimension and the largest Lyapunov exponents can be used for the characteristics in mine hoist fault diagnosis.

Key words: chaos property, mine hoister, multi-dimension phase space reconstruction, largest Lyapunov exponent, generalized correlation dimension

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