抄録
Rolling stock has been generally inspected and maintained on the basis of the preventive maintenance. However, the reliability of the sensors and information technology has drastically improved, and with this background the objective of this research is to develop the condition monitoring system for the bogies of the Shinkansen cars. This paper describes an algorithm for detecting fault in some parts of bogies. This scheme is based on the statistic analysis of vibration acceleration during some period. This algorithm named peak average method detects the difference of the vibration peak distribution between fault cases and normal ones. For examining the possibility to detect fault in the bogie, experiments simulating some fault modes in bogie parts are conducted in the rolling stock test plant at Komaki Research Center of CJRC. From the results of these experiments, we can show the reliability and the validation of this scheme for monitoring conditions of Shinkansen bogies developed in this research.
