Characteristic identification of oil dampers for railway vehicles using Neural Networks

Abstract

This paper developed a characteristic identification system for devices of railway vehicles which is an essential component in a system of ‘Virtual Running Test Environment’ based on Hardware In the Loop Simulation (HILS) technology, as developed by Railway Technical Research Institute (RTRI) to replace running tests with bench tests. This report describes the outline and the effect of the characteristic identification system for oil dampers using a Neural Network (NN), which estimates input-output relation of the target in 6 degree-of-freedom using multi-axis damper test equipment.