全矢谱-粗集理论在旋转机械故障频谱特征提取中的应用研究

Research on spplication of full vector spectrum-rough set in extracting fault spectrum feature of rotating machinery

随着旋转机械的大型化、高速化、高精度化,全面、及时、有效的对其进行故障特征提取的重要性愈来愈明显。传统的单通道信息采集方式有着信息量不全面易造成误判的弊端;传统的信息处理方式存在着效率低等弊端。基于同源信息融合和故障特征提取的思想,将全矢谱技术和粗集理论结合,提出了全矢-粗集理论在旋转机械故障频谱特征提取中的应用方法,给出了相关的定义和算法。并通过典型故障的实验验证,此方法在旋转机械故障频谱特征提取中有着更为准确、全面的优势,是一种有效的故障频谱特征提取方法,为旋转机械故障的在线监测提供参考。

With the rotating machinery developing more larger in scale,more faster in speed and more higher in accuracy,it is becoming more important to extract its faults feature comprehensively,timely and effectively.While the traditional extraction is characterized with its low efficiency,incomplete that may lead to wrong judgement Basing on the ideology of same source information fusion and fault feature extraction,it the vector spectrum shall be combined with rough set and propose the method on application of full vector spectrum-rough set in extracting fault spectrum feature of rotating machinery,which definition and algorithm are given.And with the experimental test for typical rotating machinery fault,this method is proven with the advantages of accuracy and comprehensiveness in fault spectrum feature extraction.therefore it is not only an effective way in fault spectrum feature extraction but also an reference for online monitoring and diagnosis.