2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)最新文献_第5页

Design of DTMF signal experiment system based on MATLAB 基于MATLAB的DTMF信号实验系统设计

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315651

J. Long

引用次数: 1

Short-time and Spectrum Features of Noises Made by Vehicles for Recognition 车辆噪声的短时频谱特征识别

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315641

Ding Kai, Zhang Shigong, Zhang Kesheng, Lei Zhen

{"title":"Short-time and Spectrum Features of Noises Made by Vehicles for Recognition","authors":"Ding Kai, Zhang Shigong, Zhang Kesheng, Lei Zhen","doi":"10.1109/AUTEEE50969.2020.9315641","DOIUrl":"https://doi.org/10.1109/AUTEEE50969.2020.9315641","url":null,"abstract":"The recognition and classification of moving maneuvering targets play an important role in intelligent vehicle highway system. In this paper, based on short-time and spectrum technologies, some general used features of noises made by vehicles are analyzed. Short-time zero-crossing rate and short-time energy do not show obvious identifiable characteristics for recognition. While, spectrum features of noises made by different vehicles represent obvious characteristics. These features include amplitude frequency spectrum, power spectrum density, and short time amplitude frequency spectrum, Engine speed and vehicle weight can be estimated from the spectrum features. Besides, nonlinear idle engine noise features can also be used in vehicle recognition. With a good theory basis, the voice-print features, such as pitch and formant frequencies, are considered the best methods for recognition, but the two features do not really display the corresponding role. Feature extraction based on spectrum features can provide a powerful theoretical and experimental basis for the next pattern recognition.","PeriodicalId":6767,"journal":{"name":"2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"140 1","pages":"501-504"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82086781","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}

引用次数: 0

Forward and Inverse Kinematics Modeling and Simulation of Six-axis Joint Robot Arm Based on Exponential Product Method 基于指数积法的六轴关节机械臂正逆运动学建模与仿真

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315719

Yunhao Pan, Jingdi Tang, Qing-Hao Zhao, Shengyi Zhu

引用次数: 2

A 32-channel FPGA-based multi-phase sampling TDC for RPC detector 基于32通道fpga的RPC检测器多相采样TDC

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315718

Z. Xue, H. Liang, F. Deng, J. Ge

引用次数: 1

Event-driven Fast Frequency Response Based on Fuzzy Logic Controller 基于模糊控制器的事件驱动快速频率响应

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315572

Yongji Cao, Hengxu Zhang, Changgang Li, Chen Li, Qi Guo, Yihua Zhu

{"title":"Event-driven Fast Frequency Response Based on Fuzzy Logic Controller","authors":"Yongji Cao, Hengxu Zhang, Changgang Li, Chen Li, Qi Guo, Yihua Zhu","doi":"10.1109/AUTEEE50969.2020.9315572","DOIUrl":"https://doi.org/10.1109/AUTEEE50969.2020.9315572","url":null,"abstract":"The increasing penetration of renewable energy sources (RESs) brings about critical challenges on power system frequency stability. More specially, the RESs are integrated into power systems through electronic converters, and provide less inertia to counter frequency deviations after contingencies. This paper proposes an event-driven fast frequency response (EFFR) approach based on fuzzy logic controller (FLC), in order to improve the frequency control under serious contingencies. An event-driven control framework is established, in which the contingencies and corresponding disturbance power are monitored. And once the specific contingencies are detected, the EFFR scheme will be actuated rapidly. Then, the FLC is employed to attain the control commands for EFFR, which are the required extra power of controlled units. Using the disturbance power and frequency deviation as input variables, the FLC can consider both the occurred contingencies and current power system states simultaneously. A case study is carried out to verify the feasibility and effectiveness of the proposed approach.","PeriodicalId":6767,"journal":{"name":"2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"17 1","pages":"116-120"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88326550","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}

引用次数: 1

A New Scheme of Level Difference Protection of Distribution Network 配电网电位差保护新方案

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315606

Yanxia Chen, J. Gu, Xijuan Yu, Tao Lin, Zhiyong Wang, Liping Lv

引用次数: 0

Dynamic Detection of Infants’ Video Based on All-Programmable SoC in NICU 基于全可编程SoC的新生儿重症监护病房视频动态检测

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315691

Mingxin Zhao, Zhenyu Dai, W. Huang, Kai Sun

{"title":"Dynamic Detection of Infants’ Video Based on All-Programmable SoC in NICU","authors":"Mingxin Zhao, Zhenyu Dai, W. Huang, Kai Sun","doi":"10.1109/AUTEEE50969.2020.9315691","DOIUrl":"https://doi.org/10.1109/AUTEEE50969.2020.9315691","url":null,"abstract":"The traditional Neonatal Intensive Care Unit (NICU) is equipped with camera monitoring. Medical personnel can obtain the monitoring videos of newborn babies in real time, so that the corresponding care and treatment can be performed according to the actual situation. However, the medical personnel’s energy is limited after all, and it is impossible to keep staring at the baby’s surveillance screen all the time. Once the condition of the newborn occurs and the medical staff fails to detect it in time, it may lead to the occurrence of nursing accidents in the neonatal intensive care unit. When babies feel pain, in addition to crying, they will express their discomfort by shaking their arms, kicking their legs violently, arching their backs, etc. This paper proposes a method that integrates newborn video picture acquisition, infant over-amplitude motion detection, and an audio alarm system. The single Gaussian background modeling algorithm is used to detect the baby’s large-scale movement. When the baby in the picture detects a large movement, the audio alarm system responds in time to notify the medical staff. The hardware platform on which this design relies is the Zynq System-on-Chip (SoC) development board, and the software platform uses the Vivado series design tools. This method can reduce the occurrence of nursing accidents in the neonatal intensive care unit, while freeing medical personnel from paying attention to the newborn’s video at all times. Therefore, it greatly reduces the workload of medical personnel and improves work efficiency.","PeriodicalId":6767,"journal":{"name":"2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"11 1","pages":"161-165"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74419329","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}

引用次数: 1

Design and Implementation of Scalable DBF Multi Beam Receiving Module Based on Multi-level FPGA 基于多级FPGA的可扩展DBF多波束接收模块的设计与实现

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315611

Zhihuang Lin, Wei-ling Guo, Shangyu Xie, Zhaojian Jin

引用次数: 0

A Multi-Loop Control for Software Defined Control System 软件定义控制系统的多回路控制

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315566

Xiaoxiang Ji, Jianghong Li, Jiao Ren, Yafeng Wu

引用次数: 1

Face Attribute Recognition with Multimodal Fusion 基于多模态融合的人脸属性识别

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315630

Ming Zhao, Chang Liu, Zeyu Zheng, Qingfeng Yao, Nan Yang, Yuanye Xu

{"title":"Face Attribute Recognition with Multimodal Fusion","authors":"Ming Zhao, Chang Liu, Zeyu Zheng, Qingfeng Yao, Nan Yang, Yuanye Xu","doi":"10.1109/AUTEEE50969.2020.9315630","DOIUrl":"https://doi.org/10.1109/AUTEEE50969.2020.9315630","url":null,"abstract":"Facial attribute recognition is a challenging question, especially the potential high-level semantic features between attributes are a research focus of attribute recognition research. In this paper, a face attribute recognition network is proposed based on multimodal fusion, which is completely data-driven and incorporates image features and advanced semantic features of attributes: 1) We design an image feature extraction network with an underlying shared network that does not restrict the specific form. Meanwhile, a layer-parameter orthogonalization operation is unveiled, which can increase the expressive power of the features. 2) Using graph convolutional networks (GCN), we build a semantic feature extraction network to extract advanced semantic features of face attributes and mine correlations between attributes. 3) To enhance the representation of features, we propose a multimodal fusion module to fuse two complementary representations of image features and semantic features. 4) We construct fused feature classification networks using attribute-independent high-level networks to predict multiple attributes separately. We have conducted extensive experiments to demonstrate the effectiveness of the proposed method and have obtained results that are competitive with state-of-the-art methods.","PeriodicalId":6767,"journal":{"name":"2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"29 1","pages":"478-483"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76100767","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}

引用次数: 0