On the afternoon of April 15, the 16th session of the "Research Navigation Program" was held in Classroom E130 of the teaching building at the East Coast Campus. Speakers Yang Chaoyue and Chen Jiewei delivered lectures successively on major cognition and research initiation in civil engineering and intelligent sensing-driven structural health monitoring, presenting cutting-edge knowledge and industry trend analysis to students majoring in civil engineering.
Starting from the current situation of the civil engineering industry, Yang Chaoyue sorted out the core development context of the major and introduced the five major directions covered in this field. He noted that the traditional construction sector has cooled down amid industry restructuring. At the research level, he analyzed innovative research methods in civil engineering, emphasizing that research should always focus on frontline engineering pain points and technical demands of the industry, be application-oriented, and achieve theoretical development and technological improvement while solving on-site problems.
Regarding the intelligent transformation of the industry, Yang objectively analyzed the core bottlenecks in the implementation of intelligent construction and pointed out that opportunities and challenges coexist. Combining the content of the lecture, he also provided specific learning and career development suggestions for undergraduate students, helping them stay grounded and clarify their future directions.
Chen Jiewei began with the issue of damage to key components of large-scale engineering facilities under complex environments. He reviewed the evolution of structural health monitoring technology from manual inspection and electronic sensors to intelligent monitoring, and introduced the applications of advanced sensing technologies such as fiber Bragg grating (FBG) and distributed optical fiber. Driven by the warning from the Meizhou-Dabu Expressway collapse incident, such technologies have become an urgent necessity.
In terms of technological upgrading, he explained how deep learning automatically extracts mechanical features through neural networks and realizes end-to-end damage prediction, breaking the limitations of manually designed features. The future trend of intelligent structural monitoring will shift from pure data-driven to a physics-data dual-driven model, which balances interpretability and nonlinear learning capability to form a closed-loop intelligent monitoring system.
Focusing on cutting-edge technologies including magnetorheological materials and intelligent structural monitoring, as well as the current industry situation and research approaches, this lecture built a scientific research exchange platform for civil engineering students and helped them clarify their professional development paths.
Photos and Text by: Yao Yao
