A Method for Rotor Speed Measurement and Operating State Identification of Hydro-Generator Units Based on YOLOv5

Abstract

With the rapid development of artificial intelligence, machine vision and other information technologies in the construction of smart power plants, the requirements of power plants for the state monitoring of hydro-generator units (HGU) are becoming higher and higher. Based on this, this paper applies YOLOv5 to the state monitoring scenario of HGU, and proposes a method for rotor speed measurement (RSM) and operating state identification (OSI) of HGUs based on the YOLOv5. The proposed method is applied to the actual RSM and OSI of HGUs. The experimental results show that the Precision and Recall of the proposed method for rotor image are 99.5% and 100%, respectively. Compared with the traditional methods, the online image monitoring based on machine vision not only realizes high-precision RSM and the real-time and accurate determination of operating states, but also realizes video image monitoring of the rotor, the operation trend prediction of the rotor and the early warning of abnormal operating states, so that staff can find the hidden dangers in time and ensure the safe operation of the HGU.