Electrolysis tanks are used to smeltmetals based on electrochemical principles,and the short-circuiting of the pole plates in the tanks in the production process will lead to high temperatures,thus affecting normal pr...Electrolysis tanks are used to smeltmetals based on electrochemical principles,and the short-circuiting of the pole plates in the tanks in the production process will lead to high temperatures,thus affecting normal production.Aiming at the problems of time-consuming and poor accuracy of existing infrared methods for high-temperature detection of dense pole plates in electrolysis tanks,an infrared dense pole plate anomalous target detection network YOLOv5-RMF based on You Only Look Once version 5(YOLOv5)is proposed.Firstly,we modified the Real-Time Enhanced Super-Resolution Generative Adversarial Network(Real-ESRGAN)by changing the U-shaped network(U-Net)to Attention U-Net,to preprocess the images;secondly,we propose a new Focus module that introduces the Marr operator,which can provide more boundary information for the network;again,because Complete Intersection over Union(CIOU)cannot accommodate target borders that are increasing and decreasing,replace CIOU with Extended Intersection over Union(EIOU),while the loss function is changed to Focal and Efficient IOU(Focal-EIOU)due to the different difficulty of sample detection.On the homemade dataset,the precision of our method is 94%,the recall is 70.8%,and the map@.5 is 83.6%,which is an improvement of 1.3%in precision,9.7%in recall,and 7%in map@.5 over the original network.The algorithm can meet the needs of electrolysis tank pole plate abnormal temperature detection,which can lay a technical foundation for improving production efficiency and reducing production waste.展开更多
Diagnosing the operational status of High-voltage circuit breakers(HVCBs)is crucial for ensuring the safe and stable operation of the grid.Mechanical characteristic parameters are effective indicators for evaluating t...Diagnosing the operational status of High-voltage circuit breakers(HVCBs)is crucial for ensuring the safe and stable operation of the grid.Mechanical characteristic parameters are effective indicators for evaluating the performance of HVCBs.Recent studies have shown that the actions of the springs and cams in HVCBs can be used to detect the operational status of the mechanical mechanisms,which occur extremely quickly,usually in the speed of m/ms.In this paper,dynamic vision sensing technology was employed to rapidly and dynamically capture the movements of the springs and cam of the HPL245B1 HVCB.The data volume of a single experiment is less than 100 MB,whereas the data collected by a high-speed camera at the same frame rate exceeds 1 GB.Action data streams of the springs and cam were obtained and images were reconstructed from the event streams.The Lucas-Kanade optical flow algorithm and the normalised cross-correlation algorithm are applied to calculate the parameters of spring deformation characteristics and cam rotation characteristics for mechanical feature detection of HVCBs.This is the first attempt to utilize brain-inspired hardware technology for the status monitoring of electrical equipment.The advantages of dynamic vision sensing technology,such as high dynamic range,low data transmission,and low energy con-sumption,also offer significant benefits for air discharge monitoring and status moni-toring of electrical equipment.展开更多
文摘Electrolysis tanks are used to smeltmetals based on electrochemical principles,and the short-circuiting of the pole plates in the tanks in the production process will lead to high temperatures,thus affecting normal production.Aiming at the problems of time-consuming and poor accuracy of existing infrared methods for high-temperature detection of dense pole plates in electrolysis tanks,an infrared dense pole plate anomalous target detection network YOLOv5-RMF based on You Only Look Once version 5(YOLOv5)is proposed.Firstly,we modified the Real-Time Enhanced Super-Resolution Generative Adversarial Network(Real-ESRGAN)by changing the U-shaped network(U-Net)to Attention U-Net,to preprocess the images;secondly,we propose a new Focus module that introduces the Marr operator,which can provide more boundary information for the network;again,because Complete Intersection over Union(CIOU)cannot accommodate target borders that are increasing and decreasing,replace CIOU with Extended Intersection over Union(EIOU),while the loss function is changed to Focal and Efficient IOU(Focal-EIOU)due to the different difficulty of sample detection.On the homemade dataset,the precision of our method is 94%,the recall is 70.8%,and the map@.5 is 83.6%,which is an improvement of 1.3%in precision,9.7%in recall,and 7%in map@.5 over the original network.The algorithm can meet the needs of electrolysis tank pole plate abnormal temperature detection,which can lay a technical foundation for improving production efficiency and reducing production waste.
基金National Natural Science Foundation of China,Grant/Award Numbers:52077118,62411560155Guangdong Basic and Applied Basic Research Foundation,Grant/Award Number:2024A1515012597。
文摘Diagnosing the operational status of High-voltage circuit breakers(HVCBs)is crucial for ensuring the safe and stable operation of the grid.Mechanical characteristic parameters are effective indicators for evaluating the performance of HVCBs.Recent studies have shown that the actions of the springs and cams in HVCBs can be used to detect the operational status of the mechanical mechanisms,which occur extremely quickly,usually in the speed of m/ms.In this paper,dynamic vision sensing technology was employed to rapidly and dynamically capture the movements of the springs and cam of the HPL245B1 HVCB.The data volume of a single experiment is less than 100 MB,whereas the data collected by a high-speed camera at the same frame rate exceeds 1 GB.Action data streams of the springs and cam were obtained and images were reconstructed from the event streams.The Lucas-Kanade optical flow algorithm and the normalised cross-correlation algorithm are applied to calculate the parameters of spring deformation characteristics and cam rotation characteristics for mechanical feature detection of HVCBs.This is the first attempt to utilize brain-inspired hardware technology for the status monitoring of electrical equipment.The advantages of dynamic vision sensing technology,such as high dynamic range,low data transmission,and low energy con-sumption,also offer significant benefits for air discharge monitoring and status moni-toring of electrical equipment.
