Chouqet Fuzzy Integral Based Condition Monitoring and Analysis Approach Using Simulation Framework for Rail Faults

Today, railway systems are one of the most preferred means of transportation worldwide. Some faults may occur on railway tracks due to several reasons and such faults may cause accidents. For this reason, railway tracks should be periodically inspected. In this study, a study was performed which was aimed to locate possible faults such as cracks, holes and wear on rail surfaces fast and with high accuracy levels in accordance with real systems. The study is made in two stages and distance values read on laser cameras constitute the input data of the system. Rail profiles marked as working and out-of-order are presented as input data of the sysem and a random forest is created for learning after a pretreatment on the data, four different feature extraction methods are obtained with attribute. In test phase, a second attribute is obtained via feature extraction methods, classified and produced after diagnosis. General accuracy rates of the system are increased with fuzzy integral method and a system which can work in real time and with high accuracy rates on railways with a physical tester was proposed.