2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)最新文献_第2页

Research on text categorization model based on LDA — KNN 基于LDA - KNN的文本分类模型研究

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2017-03-25 DOI: 10.1109/IAEAC.2017.8054520

Weihua Chen, Xian Zhang

引用次数: 9

Design of simple electronic organ based on single chip microcomputer 基于单片机的简易电子琴设计

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2017-03-25 DOI: 10.1109/IAEAC.2017.8053970

Jianbo Zhang, Yin Qun

引用次数: 4

Application of HHT in SRM fault feature extraction HHT在SRM故障特征提取中的应用

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2017-03-25 DOI: 10.1109/IAEAC.2017.8053976

Ruikun Yang, Ruiqing Ma, B. Peng

{"title":"Application of HHT in SRM fault feature extraction","authors":"Ruikun Yang, Ruiqing Ma, B. Peng","doi":"10.1109/IAEAC.2017.8053976","DOIUrl":"https://doi.org/10.1109/IAEAC.2017.8053976","url":null,"abstract":"Switched Reluctance Machine (SRM) has magnetic field with strong saturation nonlinearity features, complex mathematical models and its fault output is mainly unsteady signals of strong coupling multi-physical field, which easily floods effective fault characteristics and make it difficult to extract. In this paper, Hilbert-Huang transform (HHT) is introduced to SRM fault feature extraction method to solve the problems aforesaid. Firstly, Empirical Mode Decomposition(EMD) is utilized to decompose the bus current of the faulted motor into several simple Intrinsic Mode Function(IMF) to resolve the problem of unsteady characteristics of complex fault signals. Secondly, primary IMF components are selected to form the matrix of initial parameters to calculate both the energy of singular values and the parameters of energy entropy of the matrix, which is used as a feature vector. Finally, multi-classifier based on support vector machine (SVM) are used to identify the extracted small-sample fault feature vector for classification. After verification by simulation, this method can effectively reduce the complexity of the fault signals, redundant data of faults and increase the accuracy rate of fault identification. Its application in SRM fault diagnosis has theoretical and practical value.","PeriodicalId":432109,"journal":{"name":"2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117079025","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: 3

A face recognition method based on LBP feature for CNN 基于LBP特征的CNN人脸识别方法

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2017-03-25 DOI: 10.1109/IAEAC.2017.8054074

Hongshuai Zhang, Zhiyi Qu, Liping Yuan, Gang Li

引用次数: 38

A radar-based blind spot detection and warning system for driver assistance 一种基于雷达的盲点探测和警告系统，用于驾驶员辅助

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2017-03-25 DOI: 10.1109/IAEAC.2017.8054409

Guiru Liu, Lulin Wang, Sha Zou

{"title":"A radar-based blind spot detection and warning system for driver assistance","authors":"Guiru Liu, Lulin Wang, Sha Zou","doi":"10.1109/IAEAC.2017.8054409","DOIUrl":"https://doi.org/10.1109/IAEAC.2017.8054409","url":null,"abstract":"This paper proposed a blind spot detection & warning system (BSDWS) for daytime and nighttime conditions. The proposed BSDWS included system architecture, radar system structure and algorithms, Intermediate frequency (IF) signal processor, motive target detector and blind spot area calibration method and system control strategy. Line frequency modulated continuous wave (LFMCW) millimeter-wave radar system was used to monitor the moving targets which were into the blind spot warning area behind the vehicle. Based on clutter distribution model, a cell greatest, smallest and averaging constant false-alarm rate (CGSA-CFAR) detector was proposed to maintain higher detection rate and low false detection rate by adjustment threshold in time based on the noise intensity, which was estimated according to the mean and standard deviation. The BSDWS was implemented on ADI DSP-based embedded platform. System was calibrated and tested on the Chery Arrizo7 car. Under daytime and nighttime conditions, the early average warning rates were up to respectively 98.38% and 98.34%. The experimental results show that the proposed BSDWS can really detect the moving targets which were into the behind warning area of the vehicle and give warning to driver effectively in various daytime and nighttime environments.","PeriodicalId":432109,"journal":{"name":"2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132695105","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: 29

Robustness analysis for rotorcraft pilot coupling with helicopter flight control system in loop 旋翼机驾驶员与直升机飞控系统环耦合的鲁棒性分析

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2017-03-25 DOI: 10.1109/IAEAC.2017.8053978

Chen Junfeng, Li Wuzhou, Suo Wenchao, Wang Zegang, Xu Penghui, Wang Weilong

{"title":"Robustness analysis for rotorcraft pilot coupling with helicopter flight control system in loop","authors":"Chen Junfeng, Li Wuzhou, Suo Wenchao, Wang Zegang, Xu Penghui, Wang Weilong","doi":"10.1109/IAEAC.2017.8053978","DOIUrl":"https://doi.org/10.1109/IAEAC.2017.8053978","url":null,"abstract":"Robustness analysis method is proposed for rotorcraft pilot coupling with helicopter flight control system in loop. Combining with the lateral identification model of BO-105 helicopter, McRuer's pilot model, and the designed stability augmentation system, frequency domain model is established for rotorcraft pilot coupling analysis. μ analysis method and performance specifications in ADS-33E are adopted to compare robust performances of the closed loop, furthermore, the worst case in uncertain model set is studied using robust performance detection. Moreover, the properties of root locus, damping ratio and mode frequency are studied from flight control system aspect. Feasible measures to improve the robust performance are discussed from the controller design consideration. Results show that the analysis method proposed can not only reveal the physical nature of coupling qualitatively, but also calculate the performances and boundaries quantitatively, which have theoretical reference significance in flight control system design.","PeriodicalId":432109,"journal":{"name":"2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114575955","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

Robust device-free fall detection using fine-grained Wi-Fi signatures 使用细粒度Wi-Fi签名的鲁棒设备自由落体检测

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2017-03-25 DOI: 10.1109/IAEAC.2017.8054245

Wenchang Cao, Xinhua Liu, Fangmin Li

{"title":"Robust device-free fall detection using fine-grained Wi-Fi signatures","authors":"Wenchang Cao, Xinhua Liu, Fangmin Li","doi":"10.1109/IAEAC.2017.8054245","DOIUrl":"https://doi.org/10.1109/IAEAC.2017.8054245","url":null,"abstract":"Fall is one of the main threats to the health care of elderly living alone. If not timely treated, the elderly will be threatened with death. Traditional fall detection systems based on vision, sensor networks or wearable-device are either intrusive to user's daily life, or sensitive to the changing ambient environment. However, most of them have not fully taken the dynamic environment factors into account, which makes them un-robust and hinders them from being applied in practice. In this paper, we propose a robust and unobtrusive fall detection system using off-the-shelf Wi-Fi devices, which gather fluctuant wireless signals as indicators of human actions. Specifically, we design a lightweight classifier to eliminate the “bad antennas” in channel state information (CSI) so that we can extract features from the best CSI stream; by which, the negative effects aroused by the dynamic surroundings can also be removed. We also design a novel method to intercept the valid segment of signal of fall action by utilizing wavelet analysis and dynamic time window. Finally, we implement a full robust device-free fall detection system based on the proposed novel methods. In a typical indoor environment, the recognition accuracy for the fall is 91%, and the false alarm rate is only 0.06%. Experimental results show that our system is robust to the complex indoor radio frequency environments and achieves good performance.","PeriodicalId":432109,"journal":{"name":"2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121690585","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: 5

Comparative study between passive PFC and active PFC based on Buck-Boost conversion 基于Buck-Boost转换的无源PFC与有源PFC的比较研究

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2017-03-25 DOI: 10.1109/IAEAC.2017.8053974

I. Safwat, Xiahua Wu

引用次数: 11

Research on the seismic signal denoising with the LMD and EMD method 基于LMD和EMD方法的地震信号去噪研究

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2017-03-25 DOI: 10.1109/IAEAC.2017.8054119

J. Yu, Ze Zhang

引用次数: 7

Height control method of multi — Rotor vehicle based on auto-Disturbance-rejection control 基于自抗扰控制的多旋翼飞行器高度控制方法

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2017-03-25 DOI: 10.1109/IAEAC.2017.8054283

Mengchao Fu, Min Yong, Yang Zhang, Ze Li, Boyang Xing

引用次数: 0