NUMERICAL STUDY OF DISTRIBUTED ACOUSTIC SENSING (DAS) FOR RAILWAY CONDITION MONITORING

One of the most paramount factors for the railroad industry is the safe transportation of cargo and passengers. For the safe movement of locomotives, real-time tracking of trains and their cargo is critical and necessary. Current tracking systems face many challenges from weather interference to expensive implementations. Fiber optic acoustic detection has been developed for application to the railroad industry to improve the reliability of tracking locomotives along their route. Due to the wide variety of circumstances that the system could encounter, the in-situ testing of these systems has proven to be highly expensive. To reduce the cost of testing, finite element analysis is used in this study to determine the effectiveness of fiber optic acoustic detection in a variety of circumstances. The numerical results indicated that the properties of the material surrounding the cable have a significant effect on the accuracy, sensitivity, and effectiveness of the system. In particular, the density and Poisson ratio of a material are highly important to the efficacy of the detection system. The more compact material surrounding the fiber, the better acoustic matching occurs, and the stress/strain distribution is more uniform causing a better detection by the fiber optic system. In addition, the location of the fiber with respect to the applied external load is a critical parameter affecting the accuracy and probability of the detection by the fiber optic system.