Optimization of Symptom Observation Matriz in Vibration Condition Monitoring
In diagnostics of complex machines,for their condition assessment we often use many would be symptoms at the beginning,especially at the diagnostic startup of a new machine. The discrete observation of this would be1 symptom vector creates so called symptom observation matrix (SOM).Using next the singular value decomposition (SVD) for the given SOM,one can extract the generalized fault symptoms,describing the fault evolution in a given case, and also diagnostic contribution of measured symptoms.Using the symptom reliability concepts further, and the grey system forecast methodology,it is possible to asses the generalized symptoms limit value.In this way one can establish the needed dimensionality of symptom observation matrix, and moreover assess the residual system life.However, doing this we have to establish new criteria for the dimensionality of SOM,based not on the number of symptoms in use,but the quality of diagnostic decision.This concept was verified in the paper using the data taken from real cases of vibration condition monitoring practice.
machine condition multidimensional monitoring singular value decomposition (SlD) grey system,rolling forecasting diagnosis quality.
Czeslaw CEMPEL
Poznan University of Technology Piotrowo 3 St.,60-965 Poznan.Poland
国际会议
2009 8th International Conference on Reliability,Maintainability and Safety(第八届中国国际可靠性、维修性、安全性会议)
成都
英文
944-950
2009-08-24（万方平台首次上网日期，不代表论文的发表时间）