چكيده به لاتين
Abstract:
Today, the railway network has become an important place in the field of economics as a means of public transportation and freight transportation. Therefore, with increasing demand of the railway network, the system needs to operate with increased reliability, accessibility, repairability and safety.
The signaling system is a subset of the rail transportation system. For the safe operation of the signaling system, followed by the rail network, it is very important to recognize the presence of a train on each track. One of the most commonly methods to detect the presence of a train is the use of track circuit. The track circuits work fail-safe, but to avoid potential hazards and to minimize train delays, it's necessary to use a monitoring system for detection and isolation of the faults.
One of the new methods of the condition monitoring, is fault detection by the petri nets. Petri net is a powerful graphical tool that can be used not only for modeling discrete event systems, but also for modeling continuous dynamic systems.
In this thesis, a petri net model is used to detection and isolation of the faults of the TI21-M audio frequency track circuit. The TI21-M track circuit is simulated in Simulink Matlab and its data is used as Petri net inputs. Since the track circuit is a continuous dynamic system, for modeling and detecting the faults of the system using Petri nets, track circuit behavior is considered discrete; in fact, petri's model of the voltage and current variations of different components of the track circuit, the cable resistance variations, and the impedance rail variations are simulated in Matlab's Statflow environment. Then, according to changing in states of the simulated petri's model, not only faulty track circuit, but also the location of the faults is also determined. It should be noted that this network can detect the faults simultaneously.
Keywords: Rail network, Signaling system, TI21-M track circuit, Condition monitoring, Petri nets
