Transformation of Symptom Observation Matrix in Multidimensional Vibration Condition Monitoring of Machines
With the modern metrology we can measure almost all variables in the phenomenon field of a working machine, and much of measuring quantities can be symptoms of machine condition. On this basis we can form the symptom observation matrix (SOM) for condition monitoring. From the other side we know, that contemporary complex machines may have many modes of failure, so called faults. The paper presents a method for the extraction of fault information from the symptom observation matrix by means of singular value decomposition (SVD), in the form of generalized fault symptoms. As the readings of the symptoms can be unstable, the moving average of the SOM was applied with the success. The attempt to assess the diagnostic contribution of primary measured symptoms was undertaken, and also some possibility to assess symptom limit value is considered. This possibilities are illustrated in the paper by processing the data taken directly from the machine vibration condition monitoring area.
multidimensional observation vibration SVD decomposition fault space observation space symptom reliability limit value
Czeslaw Cempel
Pozna(n) University of Technology, Poland
国际会议
The First International Conference on Maintenance Engineering(首届维修工程国际学术会议)
成都
英文
319-327
2006-10-15（万方平台首次上网日期，不代表论文的发表时间）