报告时间：2023年10月27日 (星期五) 16：00—18：00
报告人：万容椿 彭霞 徐琰淞 姚可凡 殷士才
报告题目：Energy saving control and fault diagnosis of the rail transit
摘要：With the advancement of urbanization, urban rail transit, as an important force to promote the sustained and healthy development of the city. However, its operational energy consumption has also been continuously increasing. In addition to energy control, fault diagnosis is also a key research topic in the rail transit. Due to the non-intuitive high-level semantics of fault samples, such as the fault type and operating condition, traditional unsupervised methods are not suitable for fault data augmentation in traction motors. In this report, we will introduce relevant methods for fault diagnosis and energy-saving optimization control of rail transit, including disentangled semantic embedding, model prediction, fuzzy control, linear disturbance rejection, and state recognition.