A Method for Rotor Speed Measurement and Operating State Identification of Hydro-Generator Units Based on YOLOv5
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 appli...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Machines |
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| Online Access: | https://www.mdpi.com/2075-1702/11/7/758 |
| _version_ | 1797588537779945472 |
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| author | Jiajun Liu Lei Xiong Ji Sun Yue Liu Rui Zhang Haokun Lin |
| author_facet | Jiajun Liu Lei Xiong Ji Sun Yue Liu Rui Zhang Haokun Lin |
| author_sort | Jiajun Liu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T00:53:28Z |
| format | Article |
| id | doaj.art-0e5d2c71b1c64401a3b52e2901b418c9 |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-11T00:53:28Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-0e5d2c71b1c64401a3b52e2901b418c92023-11-18T20:13:10ZengMDPI AGMachines2075-17022023-07-0111775810.3390/machines11070758A Method for Rotor Speed Measurement and Operating State Identification of Hydro-Generator Units Based on YOLOv5Jiajun Liu0Lei Xiong1Ji Sun2Yue Liu3Rui Zhang4Haokun Lin5School of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, ChinaSchool of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, ChinaSchool of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, ChinaSchool of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, ChinaSchool of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, ChinaSchool of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, ChinaWith 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.https://www.mdpi.com/2075-1702/11/7/758artificial intelligencehydro-generator unitYOLOv5rotor speed measurementonline monitoring |
| spellingShingle | Jiajun Liu Lei Xiong Ji Sun Yue Liu Rui Zhang Haokun Lin A Method for Rotor Speed Measurement and Operating State Identification of Hydro-Generator Units Based on YOLOv5 Machines artificial intelligence hydro-generator unit YOLOv5 rotor speed measurement online monitoring |
| title | A Method for Rotor Speed Measurement and Operating State Identification of Hydro-Generator Units Based on YOLOv5 |
| title_full | A Method for Rotor Speed Measurement and Operating State Identification of Hydro-Generator Units Based on YOLOv5 |
| title_fullStr | A Method for Rotor Speed Measurement and Operating State Identification of Hydro-Generator Units Based on YOLOv5 |
| title_full_unstemmed | A Method for Rotor Speed Measurement and Operating State Identification of Hydro-Generator Units Based on YOLOv5 |
| title_short | A Method for Rotor Speed Measurement and Operating State Identification of Hydro-Generator Units Based on YOLOv5 |
| title_sort | method for rotor speed measurement and operating state identification of hydro generator units based on yolov5 |
| topic | artificial intelligence hydro-generator unit YOLOv5 rotor speed measurement online monitoring |
| url | https://www.mdpi.com/2075-1702/11/7/758 |
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