Research on Low Power Routing Algorithm for Train Wireless Sensor Network

As the terminal of the train maintenance network, vehicle sensors are deployed in large quantities on the bogies of high-speed rail vehicles to collect signals such as axle temperature, instability, and vibration for vehicle safety monitoring and maintenance. According to actual use feedback, traditional wired sensors have drawbacks such as difficult wiring installation and limited power supply. If wireless sensors are used to replace wired sensors, challenges such as complex environment, co-channel interference, reliability and security will be faced. To address the aforementioned challenges, this paper proposes a low-power cluster routing algorithm specifically designed for train wireless sensor networks. This algorithm begins by employing an enhanced K-means algorithm to cluster the train wireless sensor network. The ordinary nodes cluster together by selecting the most suitable cluster head based on the cost function. Then, network cluster head election is conducted based on the prediction of node life cycles. Ordinary nodes cluster together by choosing cluster heads based on the cost function, followed by the incorporation of a limited message acknowledgement mechanism in the data transmission stage to enhance the reliability of the network. Finally, the strategy was implemented through simulation software to verify its effectiveness. The results indicate that this method can achieve long-term and reliable operation of sensor systems in complex environments, reduce the number of train signal lines, and improve installation, adjustment, and maintenance efficiency.