Rolling stock has generally been inspected and maintained on the basis of preventive maintenance. However, the reliability of sensors and information technology has drastically improved and, with this background, the objective of this research is to develop a condition monitoring system for the bogies of Shinkansen cars. This paper describes two algorithms for detecting faults in some parts of bogies. These algorithms are based on the statistical analysis of vibration acceleration during some periods. One algorithm detects the difference in the vibration peak distribution between normal operation and operation with faulty parts. The other algorithm compares the vibration states between the front and rear bogies in the same car when one bogie has faulty parts. To examine the details of the vibration characteristics of the bogie with some faults, experiments simulating some faults in bogie parts are conducted in the rolling stock field simulator at Komaki Research Center of JR Central. Through this experiments and analysis, we can demonstrate the reliability and validity of the schemes developed in this study for monitoring the conditions of Shinkansen bogies.
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