2020 7th International Forum on Electrical Engineering and Automation (IFEEA)最新文献

{"title":"Research on small target detection based on improved Faster R-CNN depth network method","authors":"Liu Qinghe, Chen Weihao, Q. Hao","doi":"10.1109/IFEEA51475.2020.00175","DOIUrl":"https://doi.org/10.1109/IFEEA51475.2020.00175","url":null,"abstract":"In order to solve the problem of detecting the cone barrel targets on both sides of the unmanned formula racing car, the traditional method is to extract features based on artificial design and select appropriate classifiers for detection and identification. This method is not ideal for detecting small targets of cone buckets. It is difficult to meet the requirements in terms of accuracy and speed of detection, and there are very large limitations. A new method based on improved Faster R-CNN for cone bucket target detection is proposed. This method can effectively avoid the problem of relying on artificial design features and classifier selection, and the speed and accuracy of detection are significantly improved. Method The method is based on a deep convolutional neural network. First, we have to determine the target object to be detected: the cones with the same shape and size on both sides of the track but different colors can be divided into red, yellow and blue cones according to the color. Next, the data set of the cone bucket target is created, and the corresponding configuration file is generated according to the format of the VOC 2007 data set. The sample data in the training set is sent to the network to obtain a convolution feature map. In order to fully extract the characteristics of the sample data, the method uses a deep residual network as the feature extraction network. After obtaining the convolution feature map, it is sent to the Region Proposal Network (RPN) for generating anchor boxes. Distinguish whether the target object belongs to the foreground or the background and perform a rough position correction on the region proposals. In order to enhance the detection effect on the small target cone, the finer division of the anchor boxes in the RPN. The traditional image processing method is used to realize the Region of Interest pooling (ROI pooling), and the output region proposals is fixed to a unified scale. The region proposals are extracted by optimizing the non-maximum suppression (NMS) algorithm to reduce the missed detection rate of the adjacent cone bucket target. Finally, the Softmax classifier is used to judge the category to which the target object belongs and to use the bounding box regression to achieve accurate position correction. Result The network model of target detection was obtained by using four-step training on the self-made cone bucket dataset. We compare the original Faster R-CNN model with the improved Faster R-CNN model to test the detection effect under different weather and environment. The improved model improves the detection of mutual occlusion between small targets and adjacent targets. The average accuracy on the test set is as high as 88.1%, and the detection frame rate reaches 10FPS. The improved method for cone bucket target detection proposed in this paper avoids the problem that traditional target detection methods need to manually select features and time-consuming. There is an obvious impr","PeriodicalId":285980,"journal":{"name":"2020 7th International Forum on Electrical Engineering and Automation (IFEEA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127260434","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":"Application Analysis of Anti-Stealing Decision System Model in Business Management System","authors":"Chunmei Zhang, Junfeng Wei, Wenhu Li","doi":"10.1109/ifeea51475.2020.00183","DOIUrl":"https://doi.org/10.1109/ifeea51475.2020.00183","url":null,"abstract":"Stealing electricity is highly harmful to stealing electricity, which will cause serious interference to the normal operation of the electricity market, and will also cause serious safety electricity accidents. Based on the analysis of anti-stealing technology, this paper puts forward eight kinds of characteristic parameters to judge whether electricity is stolen or not. After accommodating, it plans the anti-stealing method relying on the big data of electricity consumption data collection platform. The function of the module. Then, the corresponding decision-making model framework of anti-theft electricity system and its internal algorithm process are established to diagnose and warn the users of electricity theft. Finally, the effectiveness and accuracy of the decision system model are proved by the actual performance.","PeriodicalId":285980,"journal":{"name":"2020 7th International Forum on Electrical Engineering and Automation (IFEEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127418859","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":"Simulation and Algorithm Optimization of VAV Air Conditioning Room Temperature Model","authors":"Zaiying Wang, Keting Yuan, Xinyi Huang","doi":"10.1109/IFEEA51475.2020.00189","DOIUrl":"https://doi.org/10.1109/IFEEA51475.2020.00189","url":null,"abstract":"With the rapid development of intelligent buildings, the research and development of VAV air-conditioning systems have become the focus of attention. This article mainly studies the temperature control loop of the VAV air-conditioning room, and optimizes the control effect of the temperature control loop of the air-conditioning room by combining intelligent algorithm and PID control. At the same time, a fuzzy PID controller is designed. Fuzzy PID control is added to the temperature control loop of the air-conditioning room. Matlab/Simulink is used for modeling and simulation. The experimental results show that the fuzzy PID control effectively improves the stability of the indoor temperature. The resulting maximum dynamic deviation is smaller, the adjustment time is shorter, and the interference resistance is better, which has certain theoretical significance for improving the comfort of the VAV system air-conditioned room.","PeriodicalId":285980,"journal":{"name":"2020 7th International Forum on Electrical Engineering and Automation (IFEEA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122784879","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":"Fault diagnosis of transformer based on W-FCM","authors":"Ming Yan-Ming, Yun Qian-Yun, Wu-Ren Ding","doi":"10.1109/IFEEA51475.2020.00077","DOIUrl":"https://doi.org/10.1109/IFEEA51475.2020.00077","url":null,"abstract":"Dissolved gas analysis (DGA) in transformer oil is an important method for fault diagnosis of power transformer insulation. The fuzzy C-mean clustering algorithm (FCM) is used to improve the traditional fuzzy clustering method by using weighted fuzzy clustering (W-FCM) method. The Euclidean distance from the sample point to the cluster center is adjusted by increasing the weighted average distance σ. An improved weighted fuzzy kernel C- mean clustering algorithm is proposed, and its weighting coefficient is optimized for gas data analysis in transformer oil. In order to achieve transformer fault diagnosis. The results of case analysis show that the algorithm can cluster samples quickly and effectively, and is especially suitable for environments containing noisy samples.","PeriodicalId":285980,"journal":{"name":"2020 7th International Forum on Electrical Engineering and Automation (IFEEA)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121388709","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":"Modeling of Total Electron Content in Regional Ionosphere Based on GPS","authors":"Xiyan Sun, Menglin You, Yuanfa Ji, Suqing Yan, Wentao Fu, Weibin Liang","doi":"10.1109/IFEEA51475.2020.00030","DOIUrl":"https://doi.org/10.1109/IFEEA51475.2020.00030","url":null,"abstract":"Ionospheric delay can cause Global Navigation Satellite System (GNSS) deviations of several meters or even hundreds of meters in the positioning process. The Total Electron Content (TEC) is one of the important parameters in ionosphere. Starting from the basic principle of using GNSS to extract TEC of ionosphere, we analyze the shortcomings of pseudorange method and carrier phase method in the calculation of ionospheric TEC. And a method of calculating TEC by using smoothing algorithm is proposed. A polynomial function model combined with the smoothing algorithm is used to model TEC. The results show that the accuracy of TEC extraction and TEC model is higher than the previous two methods.","PeriodicalId":285980,"journal":{"name":"2020 7th International Forum on Electrical Engineering and Automation (IFEEA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121953493","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":"Frequency and Chirp Rate Estimation of FMICW Signals","authors":"L. Dongze, Zhang Li","doi":"10.1109/IFEEA51475.2020.00138","DOIUrl":"https://doi.org/10.1109/IFEEA51475.2020.00138","url":null,"abstract":"The frequency difference between adjacent pulses is hard to tell due to the poor performance of Kay algorithm. So it is hard to estimate the chirp rate of FMICW (Frequency Modulated Interrupted Continuous Wave, FMICW) signals with small chirp rate. To solve the problem, new frequency chirp rate estimation for FMICW signals is proposed in this paper. Firstly, the improved iterative Kay algorithm is proposed to improve the performance of frequency estimation for FMICW signals. So the frequency difference between adjacent pulses can be estimated. Secondly, the chirp rate estimation by LS (Least Squares, LS) fitting is proposed based on the improved iterative Kay algorithm. The effectiveness, applicable conditions, influence by SNR (Signal Noise Ratio) and iterative number are simulated. Simulation results show that the performance of frequency estimation for FMICW signals is improved dramatically. The problem of chirp rate estimation for FMICW signals with small chirp rate is solved by using the algorithm.","PeriodicalId":285980,"journal":{"name":"2020 7th International Forum on Electrical Engineering and Automation (IFEEA)","volume":"55 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120870670","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 Smart Grid State Monitoring and Data Analysis Technology Based on Cloud Computing","authors":"Zifeng Chen, Hui Cheng, Zemeng Shan","doi":"10.1109/ifeea51475.2020.00188","DOIUrl":"https://doi.org/10.1109/ifeea51475.2020.00188","url":null,"abstract":"Due to the comprehensive development of the smart grid construction in recent years, various monitoring data and operating data have increased exponentially, including not only traditional structured data, but also unstructured data such as images. Massive amounts of data are generated during the operation of the smart grid. Among these grid data, condition monitoring data occupies a large proportion, especially sufficient condition monitoring data for substation equipment. Power accidents occur to a large extent due to the poor quality and aging of power equipment. Therefore, in order to effectively avoid failures during the operation of power equipment, it is necessary to strengthen the monitoring of the operation status of the key equipment of the smart grid. By monitoring the status of important equipment and analyzing the monitoring data, obtain the relevant operating status data of power equipment, and evaluate the basic status of the smart grid through effective analysis of real-time data and perform fault warnings, and the equipment that has problems can be repaired or replaced to improve the security of the smart grid. Therefore, this article first analyzes the current development status of smart grid monitoring systems, analyzes cloud computing technology, and combines the advantages of cloud computing, proposes a Hadoop-based monitoring of the operating status of smart substation equipment, and verifies it through experiments.","PeriodicalId":285980,"journal":{"name":"2020 7th International Forum on Electrical Engineering and Automation (IFEEA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130101745","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":"Modal Calculation and Experimental Study on Electric Cabinet of Rail Vehicle","authors":"Jun Zhang, Xiangli Lin, Yingying Liu, X. Han","doi":"10.1109/IFEEA51475.2020.00110","DOIUrl":"https://doi.org/10.1109/IFEEA51475.2020.00110","url":null,"abstract":"Using finite element analysis method and force hammer method to identify the modal parameters of a certain type of Metro electric cabinet of rail vehicles, and comparative analysis of the calculation and test results, the modal characteristics of the electric cabinet are obtained, which provides a reference for the modal analysis and structural design of the electric cabinet in the future.","PeriodicalId":285980,"journal":{"name":"2020 7th International Forum on Electrical Engineering and Automation (IFEEA)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133071959","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":"Development of split truck mounted drilling rig","authors":"Lu Feifei","doi":"10.1109/ifeea51475.2020.00028","DOIUrl":"https://doi.org/10.1109/ifeea51475.2020.00028","url":null,"abstract":"vehicle mounted drilling rig is an ideal model for surface coalbed methane exploitation and mine surface emergency rescue drilling construction. In the past, it was mainly imported. In recent years, many manufacturers have developed domestic vehicle mounted drilling rig, and the market competition is becoming increasingly fierce. Through research and research, the ground mounted drilling rig is improved and optimized to meet the requirements of license plate and driving on the road. The electric control system is independently developed. At the same time, the pipeline layout and component reliability are optimized and improved to form a separate vehicle mounted drilling rig.","PeriodicalId":285980,"journal":{"name":"2020 7th International Forum on Electrical Engineering and Automation (IFEEA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122917236","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":"Application research of the voiceprint imaging technology in substation patrol","authors":"Gong Wenlan, Lin Dajian, Yu ZhangTing","doi":"10.1109/ifeea51475.2020.00068","DOIUrl":"https://doi.org/10.1109/ifeea51475.2020.00068","url":null,"abstract":"In order to make full use of the noise information of substation power equipment and to deeply explore the value of noise, a voiceprint imaging technology in substation patrol was proposed in this paper which replace the the noise monitoring by human ear. The basic principle, algorithm, array selection and other technical details of the voiceprint imaging technology were introduced in detail. The effectiveness of the technical measure in substation patrol was proved by an application case. The voiceprint imaging technology in substation patrol is safe, fast and accurate. It fills the technical gap of power equipment noise patrol and greatly improves the efficiency of substation patrol.","PeriodicalId":285980,"journal":{"name":"2020 7th International Forum on Electrical Engineering and Automation (IFEEA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116769731","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}