Design of Fuzzy Inference Rule Model for Decision Support of Railway Safety Asset Management Based on Weather Environment Data Process

This paper proposed an a fuzzy inference rule model for decision support to maximize the safe asset management of railway systems by utilizing data information on the climate environmental risks of railway facilities. The state monitoring sensor information of the railway operation line and the operation agency operation handling information were fused, and real-time climate data information was used. Climate condition digital information used anemometer, avalanche, visibility, and earthquake information, while radar, 3D camera, and ultrasonic sensor information were used for information mounted on the train. As a digital intelligence convergence algorithm, a fuzzy inference rule model that processes multiple generation environmental data was proposed. The implemented fuzzy inference rule model can be applied to the train operation management system and can be applied as an asset management and operation management decision-making algorithm of railway facilities.