The current sensor layout of train braking and air supply systems (BASSs), including the number of sensors and their installation positions, is mainly determined based on human experience and still retains the initial setup mode. This leads to issues such as unreasonable sensor quantities, imprecise installation positions, and low fault detection rates. In this chapter, the signed directed graph (SDG) is used to address the optimization of the sensor set for train BASSs. By dividing the system into units, constructing unit SDG models, combining them into a system SDG model, and finally incorporating typical faults to obtain the system SDG faulty model, the optimal sensor set by considering the sensors’ ability to observe and differentiate faults can be determined. Taking the BASS of the 350km/h train as an example, the proposed method is used to solve the optimized sensor set, which is then verified through simulation experiments. The simulation results show that an optimized sensor set can effectively identify and differentiate typical faults.