Wireless sensor network (WSN) technology plays a crucial role in enabling the dynamic monitoring of underground structures. Owing to its dynamic networking, ultralow power consumption, strong environmental adaptation, real-time monitoring, and remote monitoring capabilities, it is often utilized for structural monitoring in challenging environments. Traditional WSN monitoring instruction tends to emphasize abstract principles of WSN communication and networking, failing to engage students in real-world operations. This paper establishes a WSN dynamic monitoring platform based on WSN and TJ_UWIS sensors and designs teaching experiments to involve students in practical WSN monitoring applications. By enriching teaching content in this manner, the study enhances students’ practical, operational and innovative capabilities.
The developed monitoring platform consists of three primary components: wireless monitoring nodes, intelligent gateway nodes, and a data terminal processing module. The wireless monitoring node integrates various sensors, such as TJ_UWIS inclination sensors and strain sensors. These nodes can automatically network with intelligent gateways and autonomously monitor structural conditions, uploading the collected data to the intelligent gateways. The intelligent gateway nodes receive, store, and transmit monitoring data to the data terminal via mobile networks. They also facilitate command reception and transmission between the data terminal and wireless monitoring nodes. The data terminal processing module enables data display, processing, and command issuance, granting users comprehensive control over the monitoring system. For educational purposes, a teaching experiment is designed. First, suitable monitoring sensors are selected, and a rational monitoring program based on the structural characteristics of the monitoring site is developed. Afterward, the appropriate deployment locations and monitoring parameters are determined. Subsequently, sensor networking and data transmission are verified to ensure the quality of the monitoring system. Finally, monitoring data on the monitoring platform are acquired, and data analysis is performed.
In this study, the monitoring platform and TJ_UWIS sensors are employed to monitor the freezing deformation of a tunnel in a cold area, and five monitoring sections are established. The results reveal the following: 1) The temperature variation pattern of each monitoring section is influenced by its location. Sections close to the sunny side exhibit similar temperature trends, whereas those near the shady side display slightly different patterns. Moreover, the temperature drop on the shady side is more pronounced during sudden temperature decreases. 2) The rate of change in tunnel lining inclination correlated with temperature fluctuations. Specifically, when temperatures change abruptly, the rate of lining inclination alteration is also increased. 3) In certain monitoring sections, the variation in lining inclination is asymmetrical, suggesting potential asymmetric stress on the lining due to uneven freezing or biased pressure. 4) The utilization of this monitoring platform provides students with comprehensive engagement in WSN monitoring procedures, thereby enriching the depth and breadth of the course curriculum.
The WSN dynamic monitoring platform enables real-time monitoring of underground structures. Integrating this platform into teaching facilitates students’ comprehension of WSN networking principles, deployment methods, and data processing. This hands-on approach can improve students’ practical skills and problem-solving abilities, ultimately enhancing their professionalism and fostering innovative thinking.