Abstract
In recent years, large-scale renewable energy access to substations has brought overload, harmonic, short circuit and other problems, which has led to an increase in the failure rate and shortening the service life of important power equipment such as transformers. Transformer is one of the key equipment in power system, and its operation status has an important impact on the safe and stable operation of power grid. In order to realize the real-time state evaluation of transformer, a real-time vibration signal detection method based on video is proposed in this paper. Firstly, YOLOv4 is used to detect the transformer object, and then the pyramid Lucas-Kanade optical flow method and Otsu method are used to calculate the transformer vibration vector. Experimental results show that the transformer vibration vector can be calculated in real time and accurately by using the proposed algorithm, so as to realize the real-time reliable analysis of the transformer state.
Highlights
In response to the call of the state to vigorously develop new energy power generation, more and more photovoltaic power stations and wind farms are connected to the power grid, which alleviates energy shortage and environmental pollution, and brings many threats to the power grid
The performance of the proposed vibration detection method is examined in Experimental Results and Analysis Section and the conclusion is given in Conclusion Section
This paper presents a real-time transformer vibration signal detection method based on video
Summary
In response to the call of the state to vigorously develop new energy power generation, more and more photovoltaic power stations and wind farms are connected to the power grid, which alleviates energy shortage and environmental pollution, and brings many threats to the power grid. In order to save costs, some new energy power stations require direct access to the lowvoltage side of the substation and transmit electric energy to a higher voltage level through the substation. In this way, the adverse impact of new energy on the power grid will be directly applied to the power transformer in the substation. Section reviews the YOLOv4 model and the pyramid LK optical flow method. Mosaic data augmentation, Label Smoothing, DropBlock regularization, CIoU loss, cosine annealing learning rate and so on are used to improve the model performance
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
