Recently, the PHM2024-Beijing International Fault Diagnosis Data Competition, organized by the IEEE Global Conference on Reliability and Prognostics and Health Management, concluded. Students from our school achieved third place overall and first place among universities.

It is reported that after more than ten years of development, the IEEE Global Conference on Reliability and Prognostics and Health Management has become the most prominent and recognized international academic conference in the PHM field. The international fault diagnosis data competition held under its auspices is based on the challenge of autonomous safety assurance for rail transit trains. A total of 160 teams from renowned universities, leading industry enterprises, and research institutions at home and abroad participated, with academic backgrounds spanning numerous disciplines such as transportation, mechanical engineering, computer science, and artificial intelligence.

In this competition, two student teams led by Professor Liu Hui, Professor Wang Tiantian, and Associate Professor Xie Jinsong from our school achieved second and third place, respectively. Among them, the method titled ‘Data Augmentation Enhancement Based on Diffusion and Fault Feature Decoupling Using TFNN,’ guided by Professors Wang Tiantian and Xie Jinsong, received high praise from the competition’s official evaluation.

First Review: Yi Yang  Second Review: Shangjun Wang Third Review: Yuan Li