Robust Fault Tolerant Rail Door State Monitoring Systems: Applying the Brooks-Iyengar Sensing Algorithm to Transportation Applications

In a moving train, the acceleration and deceleration adversely effects the sensor systems, which may induce errors into the system. Todays technology does not guarantee success and safety in all situations. There are two important situations that are critical for the safety of passengers when embarking and disembarking. Distributed sensing networks needed to control the train doors require a fusion of the sensor inputs to provide accurate automatic opening and closing with minimum traction. Brooks-Iyengar Distributed Sensing algorithm can be used to provide a fault tolerant automatic sensing platform for closing doors based on the following scenario. An automatic sensor network can be installed in the motor circuit to collect current data through a wireless protocol. The data can be transmitted by cellular communication to servers, where the Brooks-Iyengar distributed sensing algorithm can be applied to identify and categorize the data signals to safely and automatically open and close the doors. This paper describes the performance evaluation of the signal output of Brooks-Iyengar algorithm in this application. Based upon the performance results, the Brooks-Iyengar Algorithm provides the best robust algorithm for implementation under faulty sensor conditions, such as those encountered in real-world transportation applications.