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铁道科学与工程学报

JOURNAL OF RAILWAY SCIENCE AND ENGINEERING

第11卷    第5期    总第61期    2014年10月

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文章编号:1672-7029(2014)05-0046-06
盲反卷积去噪在机车走行部故障分析上的应用
于天剑1 ,陈特放2,陈雅婷2,陈春阳1

(1. 中南大学 交通运输学院, 湖南 长沙 410075;
2. 中南大学 信息科学与工程学院,湖南 长沙410075
)

摘 要: 基于一种新的机车齿轮箱振动信号去噪的模型及算法,在分析总结大量实际振动信号的基础上,探讨运用盲反卷积去噪的方法以提高信号信噪比和信号质量,通过提取机车齿轮的故障特征信息并与TSA(时间同步平均)方法相比较,其在准度和精度方面都有较大改善。不仅能满足在线监测和故障诊断的实时性和可靠性的要求,同时显示出属性的可靠性、耐用性和高置信度性,提高了诊断和预警的技术。

 

关键字: 机车故障诊断;盲反卷积;振动信号;故障预测

Application of blind deconvolution de-noising in locomotive running gear failure analysis
YU Tianjian1 ,CHEN Tefang2 ,CHEN Yating2,CHEN Chunyang1

1.School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China;
2.School of Information Science and Engineering, Central South University, Changsha 410075, China

Abstract:This paper introduced a new gearbox vibration signal de-noising locomotive model and algorithm based on the analysis of a lot of the actual vibration signals, to discusses the use of blind deconvolution de-noising methods so as to improve the noise ratio and signal quality, by extracting characteristic information of the motorcycle gear and comparing with TSA (time Synchronization average) method, by which the results were greatly improved in accuracy and precision. The proposed method can not only meet the requirements of real-time characteristics and reliability in the respect of online monitoring and fault diagnose, but also show the reliability properties, durability and high degree of confidence, which improves the diagnosis and early warning techniques.

 

Key words: locomotive fault diagnose; blind-deconvolution; vibration signal; failure prediction

ISSN 1672-7029
CN 43-1423/U

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