Fault Diagnosis via the Statistical Comparison of Relation Between Binary Parameters Using LVQ(Mechanical Systems)

In this paper, the method of extracting true abnormal information from the statistics comparison of relation between discrete parameters using LVQ is examined. In general, since a fluctuation occurs in a sensor measuring quantity in the normal state by various factors, such as a noise and environment, an incorrect diagnostics arises in the abnormality diagnosis system which use threshold value. In a lot of cases, fault detection system will detect more than the actually caused abnormalities significantly. In this case, the judgement to all the abnormal information is required, the treatment to an individual phenomenon becomes shortly, and it causes hindrance of accurate judgment. Therefore, for quick action and the maintenance, reduction of the incorrect information is desired. Then, in this paper, the method of extracting true abnormal information from the statistics comparison of relation between discrete parameters using LVQ is examined. In general, by the abnormality diagnosis system, existence or not of an abnormality is shown by the binary parameters. When identifying a time-series relation of parameters, a method suitable for correlation identification of discrete quantity is needed. LVQ was applied as an autocorrelation identification method. The simulation based on data of actual working railway monitoring system was carried out and the occurrence of the fault was detected by detecting the change of identified LVQ from a statistical test.