期刊论文详细信息
Data Science Journal
Extracting Feature Information and its Visualization Based on the Characteristic Defect Octave Frequencies in a Rolling Element Bearing
Jianyu Lei1  Mingfu Liao1 
[1] Institute of Monitoring and Control for Rotating Machinery and Wind Turbines, Northwestern Polytechnical University, Xi'an, China, 710072;
关键词: Roller bearings, Roller element bearings;    Characteristic defect octave frequencies;    3-D visualization technology;    Envelope spectrum array;    Extremum envelope spectrum;   
DOI  :  10.2481/dsj.6.S596
来源: DOAJ
【 摘 要 】

Monitoring the condition of rolling element bearings and defect diagnosis has received considerable attention for many years because the majority of problems in rotating machines are caused by defective bearings. In order to monitor conditions and diagnose defects in a rolling element bearing, a new approach is developed, based on the characteristic defect octave frequencies. The characteristic defect frequencies make it possible to detect the presence of a defect and diagnose in what part of the bearing the defect appears. However, because the characteristic defect frequencies vary with rotational speed, it is difficult to extract feature information from data at variable rotational speeds. In this paper, the characteristic defect octave frequencies, which do not vary with rotation speed, are introduced to replace the characteristic defect frequencies. Therefore feature information can be easily extracted. Moreover, based on characteristic defect octave frequencies, an envelope spectrum array, which associates 3-D visualization technology with extremum envelope spectrum technology, is established. This method has great advantages in acquiring the characteristics and trends of the data and achieves a straightforward and creditable result.

【 授权许可】

Unknown   

  文献评价指标  
  下载次数:0次 浏览次数:3次