Tianpeng He, Wenzheng Li, Xijia Du, Huina Yang, Haoxi Cong
{"title":"Garbage Classification and Recognition System Based on Neural Network","authors":"Tianpeng He, Wenzheng Li, Xijia Du, Huina Yang, Haoxi Cong","doi":"10.1109/AEERO52475.2021.9708200","DOIUrl":"https://doi.org/10.1109/AEERO52475.2021.9708200","url":null,"abstract":"Traditional garbage classification has many errors and consumes resources seriously, which no longer meets the current needs of garbage classification. In response to these problems, this research proposes a garbage classification model based on migration learning and the application of this model to the actually created garbage separation device. First, pre-train the ResNet50 deep network learning model on the ImageNet dataset; Secondly, transfer the underlying features shared by the edges, colors, and textures learned by the convolution module of the ResNet50 deep network model to the residual network layer of the network model for garbage classification as the initialization parameters; Then use the extracted feature map as input to train the garbage classification model; Finally, modify the fully connected layer to a four-classification problem to accurately classify the garbage. By using the improved Trashnet training set to compare the three pre-training networks, namely alexnet, googlenet and resnet50, the results show that resnet50 has a relatively good recognition accuracy. After fine-tuning the training parameters and the training set, the final verification rate is 91.42%. which basically meet the accuracy requirements of garbage classification. At the same time, this garbage sorting network is implanted into the STM32F4 single-chip microcomputer through the Raspberry Pi to obtain a rubbish sorting device that can identify garbage. The photos recorded by the camera in real time are transmitted to the single-chip microcomputer for processing to obtain the classification result. At this time, the motor starts to work so that the garbage can fall into the corresponding bucket. While reducing the consumption of human and material resources, it greatly improves the accuracy of garbage classification and provides a new method for garbage classification.","PeriodicalId":6828,"journal":{"name":"2021 International Conference on Advanced Electrical Equipment and Reliable Operation (AEERO)","volume":"68 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89193016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qiji Dai, Mingyong Xin, J. Zhu, B. Tian, Zhong Liu, Yanze Zhang
{"title":"Implementation of Current Transformer Algorithm Based on Machine Learning","authors":"Qiji Dai, Mingyong Xin, J. Zhu, B. Tian, Zhong Liu, Yanze Zhang","doi":"10.1109/AEERO52475.2021.9708138","DOIUrl":"https://doi.org/10.1109/AEERO52475.2021.9708138","url":null,"abstract":"With the development of the construction of “Smart Grids”, new requirements have been raised for the efficiency and accuracy of current measurement. Nowadays, current measurement system based on giant magnetoresistance effect (GMR) becomes a new research direction in related fields. The working principle of this measurement system is obtaining the measured current information indirectly by analyzing the magnetic field data, which is collected by a series of GMR magnetic field sensor array around the wire. Essentially, it is an inverse problem from magnetic field to current. At present, optimization algorithm is mainly used for this kind of inverse calculation, which, however, is difficult to balance the efficiency and accuracy of the algorithm. Thus, we propose the idea of realizing the inverse calculation by using machine learning. Based on a specific kind of circular sensor structure, we propose a neural network-based inverse calculation algorithm and verifies the feasibility of this algorithm.","PeriodicalId":6828,"journal":{"name":"2021 International Conference on Advanced Electrical Equipment and Reliable Operation (AEERO)","volume":"3 5 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89659343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Research on Supporting Control Technology of Wind driven generator Auxiliary Power Grid Based on Energy Storage DC Access","authors":"Haiyuan Lian, S. Hu, Yanfeng Meng","doi":"10.1109/AEERO52475.2021.9708401","DOIUrl":"https://doi.org/10.1109/AEERO52475.2021.9708401","url":null,"abstract":"Under MPPT mode, It is very difficult for permanent magnet direct drive wind driven generator to respond correctly to changes in the frequency of the grid. Large-scale wind driven generators connected to the power grid will increase the frequency regulation pressure of the power system. The traditional frequency control system reserves a part of active power for frequency regulation by reducing the generating efficiency of wind driven generator, but there are also some problems such as small frequency range and frequent adjustment of pitch Angle. Therefore, this paper proposes a control method based on hybrid energy storage DC access to single wind driven generator auxiliary power grid frequency support, and designed a set of energy storage equipment and wind driven generator with complementary advantages of battery and super capacitor to respond to the power grid FM regulation wind power generation system.","PeriodicalId":6828,"journal":{"name":"2021 International Conference on Advanced Electrical Equipment and Reliable Operation (AEERO)","volume":"8 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89779685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiali Chen, Ruihai Li, Zaixing Peng, Kai Liu, Shuai Zhang, H. Qian
{"title":"Research on Mechanism Design Scheme of 500kv Fast Circuit Breaker","authors":"Jiali Chen, Ruihai Li, Zaixing Peng, Kai Liu, Shuai Zhang, H. Qian","doi":"10.1109/AEERO52475.2021.9708351","DOIUrl":"https://doi.org/10.1109/AEERO52475.2021.9708351","url":null,"abstract":"Reducing the fault isolation time of 500kV transmission line is of great significance for enhancing the transmission capacity of transmission line and improving the security and stability of power grid. In this paper, the CTY-5/10/20 series hydraulic operating mechanism is improved. The electromagnetic repulsion mechanism is used to drive the hydraulic valve directly in the 500kV fast circuit breaker mechanism, which cancels the response time of the primary valve of the original transmission hydraulic mechanism. Finally, the action time of the mechanism is reduced to 4ms to achieve the fast response of the mechanism, and then the breaking time of the circuit breaker is reduced. Through simulation and test verification, the average opening speed of the improved 500kV fast circuit breaker mechanism can reach 10m / s, and the opening time is about 8mm.The research results of this paper accumulate experience for the future engineering application of 550kV fast AC circuit breaker in China Southern Power Grid, and provide reference for the future planning and safe and stable operation of China Southern Power Grid.","PeriodicalId":6828,"journal":{"name":"2021 International Conference on Advanced Electrical Equipment and Reliable Operation (AEERO)","volume":"171 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87598766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhijie Shi, W. Wang, K. Han, Yuanyuan Li, Jiancheng Song, Z. Lei
{"title":"Influence of particle size on Lichtenberg Figure technique for surface charge characterization","authors":"Zhijie Shi, W. Wang, K. Han, Yuanyuan Li, Jiancheng Song, Z. Lei","doi":"10.1109/AEERO52475.2021.9708157","DOIUrl":"https://doi.org/10.1109/AEERO52475.2021.9708157","url":null,"abstract":"The Lichtenberg Figure technique is a method that can directly observe the surface charge distribution of the insulating material. It is widely used in the observation of the charge at the gas-solid interface and the study of the discharge mechanism. A needle-plate electrode was used to corona charge the polyimide film. The influence of the particle size on the spatial resolution of the surface charge measurement presented by the Lichtenberg Figure was studied by selecting dust of different particle sizes. A surface potential measurement system was constructed for verifying whether the dust affects the original charge distribution on the insulating surface. The results show that as the particle size of the dust becomes smaller, the accuracy of the Lichtenberg Figure is improved, and the influence of the dust on the original charge distribution can be reduced through the improvement of the test method.","PeriodicalId":6828,"journal":{"name":"2021 International Conference on Advanced Electrical Equipment and Reliable Operation (AEERO)","volume":"34 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84309565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Y. Qiao, T. Hu, T. Luo, C. Zhu, F. Zhou, D. Wang, R. Zhuo, Z. Huang, Y. Jing
{"title":"Influence of the Defects in RIP bushings on Electric Field Distortion","authors":"Y. Qiao, T. Hu, T. Luo, C. Zhu, F. Zhou, D. Wang, R. Zhuo, Z. Huang, Y. Jing","doi":"10.1109/AEERO52475.2021.9708178","DOIUrl":"https://doi.org/10.1109/AEERO52475.2021.9708178","url":null,"abstract":"Epoxy resin impregnated paper (RIP) dry bushings are an important part of transformers. The defects in the core insulation will seriously threaten the safe operation of the substation. This paper studies the influence of different types of defects on the electric field distortion of the RIP bushings. Constructed a model of dry casing, and set up bubble, crack and water drop defects in the model to study the influence of defect development on electric field distortion. It is indicated that the bubble defects, crack defects, and damp defects have an important impact on the electric field. Among them, the larger ones have a more serious effect on the electric field distortion. In addition, if the defect is inside the epoxy insulation, and located relatively close to the current conduit, the degree of electric field distortion is much greater than in other locations.","PeriodicalId":6828,"journal":{"name":"2021 International Conference on Advanced Electrical Equipment and Reliable Operation (AEERO)","volume":"17 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85430521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meng Cao, Chi Zhang, Q. Tang, Jin He, Xuliang Zhu, Qi Zhao
{"title":"Short-term prediction study on the development trend of free particle defects within GIS based on ARMA model","authors":"Meng Cao, Chi Zhang, Q. Tang, Jin He, Xuliang Zhu, Qi Zhao","doi":"10.1109/AEERO52475.2021.9708119","DOIUrl":"https://doi.org/10.1109/AEERO52475.2021.9708119","url":null,"abstract":"The prediction of the development trend of metal free particle defects is crucial to the maintenance and operation of GIS equipment, and an accurate prediction can effectively reduce the probability of GIS equipment failure. This paper proposes a short-term prediction method for the development trend of metal own particle defects based on ARMA model. Compared with the experimental data, it is found that this method can accurately achieve the prediction of the development trend of the partial discharge characteristic parameter of step mutability, and it is more difficult to predict the partial discharge characteristic parameter of nonlinear change, but the general trend of change can be basically predicted.","PeriodicalId":6828,"journal":{"name":"2021 International Conference on Advanced Electrical Equipment and Reliable Operation (AEERO)","volume":"30 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80289457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Gao, Tengfei Li, Min Lin, Gangjie Zhou, Yong Ma, Lijun Jin
{"title":"Simulation of GIS Epoxy Insulator Surface Discharge Channel Based on Fractal Theory","authors":"K. Gao, Tengfei Li, Min Lin, Gangjie Zhou, Yong Ma, Lijun Jin","doi":"10.1109/AEERO52475.2021.9708378","DOIUrl":"https://doi.org/10.1109/AEERO52475.2021.9708378","url":null,"abstract":"Metal particles in gas insulated switchgear (GIS) can cause partial discharge or even flashover on the surface of basin insulator. Based on the fractal theory and streamer breakdown theory, a simulation model of discharge channel on the surface of epoxy insulator is established. By assuming that the defect is metal particles, the discharge channels with different defect locations and different defect degrees are simulated. The fractal dimension of discharge channel is calculated by box width counting method, and its characteristics are analyzed. The results show that the extending velocity of the discharge channel increases exponentially with the development of discharge. With the metal particles close to the high voltage electrode, the critical voltage of flashover decreases, and the fractal dimension of discharge channel increases. The research results can provide theoretical support for exploring the flashover characteristics of metal particles on GIS insulators.","PeriodicalId":6828,"journal":{"name":"2021 International Conference on Advanced Electrical Equipment and Reliable Operation (AEERO)","volume":"101 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82255648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yinan Wu, H. Mu, Yiming Zheng, J. Zhan, Xianjun Shao, Chen Li, Chi Zhang, Guanjun Zhang
{"title":"A Novel Method for Extracting Features of Partial Discharge Pulse Current Signal","authors":"Yinan Wu, H. Mu, Yiming Zheng, J. Zhan, Xianjun Shao, Chen Li, Chi Zhang, Guanjun Zhang","doi":"10.1109/AEERO52475.2021.9708217","DOIUrl":"https://doi.org/10.1109/AEERO52475.2021.9708217","url":null,"abstract":"Partial discharge (PD) not only causes the aging of the internal insulation of the power transformer but also characterizes the deterioration of the insulation system. During the operation of the power transformer, different types of partial discharges (PDs) may occur inside. The opportune PD pattern recognition is of great significance to the maintenance and operation stability of the transformer. The pulse current method is a widely used PD detection method, and the feature extraction of pulse current signal is a key step in PD pattern recognition. The present feature extraction method of pulse current signal usually uses a complex algorithm and takes a long computing time, which is not suitable for field application. This paper proposed a fast and effective method for extracting features of PD pulse current signals. The features extracted by this method can correctly classify the three typical insulation defects in transformers.","PeriodicalId":6828,"journal":{"name":"2021 International Conference on Advanced Electrical Equipment and Reliable Operation (AEERO)","volume":"37 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82737858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Blind Separation of Transformer Vibration Signal Based on Sensitive IMFs","authors":"Zhen Li, Qingshuai Ren, Jing Ding, Renjie Wang, Ping Ju, Qingquan Li","doi":"10.1109/AEERO52475.2021.9708096","DOIUrl":"https://doi.org/10.1109/AEERO52475.2021.9708096","url":null,"abstract":"The vibration signal measured from the wall of the transformer oil tank is a mixture of various vibration source signals, and it is difficult to extract the characteristics of the transformer vibration signal and fault diagnosis. In this paper, a blind separation method of transformer vibration signal based on sensitive IMF is proposed aiming at the problem that the single-channel transformer vibration signal is difficult to separate. First, this paper analyzes the transformer vibration characteristics, and then the Intrinsic Mode Function (IMF) decomposed by the Variational Mode Decomposition (VMD) algorithm is screened and reconstructed based on the sensitive factor. The VMD algorithm is combined with the Fast Independent Component Analysis (FastICA) algorithm to separate the vibration signal. The method is verified by constructing a simulation signal according to the transformer vibration characteristics, and the method is applied to separate the transformer vibration signal to prove the effectiveness of the method.","PeriodicalId":6828,"journal":{"name":"2021 International Conference on Advanced Electrical Equipment and Reliable Operation (AEERO)","volume":"54 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89818190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}