On October 29-30, the final of the 17th “IE Liangjian” National Industrial Engineering Application Case Competition was held. The graduate and undergraduate group from the Department of Industrial Engineering and Management of the School of Mechanical Engineering both won the grand prize awards.

Introduction to the Grand Prize Project of the Graduate Group

Project name: Remote intelligent monitoring and diagnosis platform based on big data and industrial Internet for the world's first 300MVar dual water internal condenser

Project members: Tongtong Yan, Yu Wang, Yuting Wang, Yikai Chen, Yanqing Deng

Instructors: Dong Wang, Tangbin Xia, Jian Dai, Zhike Peng

To help achieve carbon peaking and carbon neutrality goals and meet the urgent needs of the intelligent operation and maintenance of the condenser, this study proposed three advanced methodologies and developed three key technologies for condenser health monitoring, including anomaly monitoring technology based on a digital twin model and statistical process control, performance degradation trend prediction technology based on convex optimization, data fusion and Bayesian theory and fault diagnosis technology based on binary tree. Afterward, three key technologies were integrated to develop a remote intelligent monitoring and fault diagnosis platform for the world's first 300MVar dual water internal condenser, which realizes intelligent monitoring and diagnosis, data visualization, analysis, and interaction. Moreover, the proposed remote intelligent monitoring and diagnosis platform of the condenser based on big data and industrial Internet has been stably applied in many power plants.