Data Driven Rul Estimation Of Rolling Stock Using Intelligent Functional Test

The rolling stock health condition is important for both passenger and freight trains in terms of safety, availability, punctuality and efficiency. Various inspection and maintenance methodologies are performed on rolling stock equipment to fulfill the above performance measures. This paper suggests a new approach, namely, intelligent functional test (IFTest) to estimate the remaining useful life (RUL) of the equipment, subsystems and systems of rolling stock dynamically by data driven methods. IFTest generates a baseline of the current operational abilities in contrast to the required abilities. The test integrates the historical and new set of data to track the trend of degradation of equipment. With this approach, the operation and maintenance personnel have ample time to make decisions for the maintenance and failure consequences. In addition, it is supposed that by using such data we are achieving a more accurate result for the estimation of reliability and RUL of critical rolling stock equipment.