2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)最新文献_第10页

Sea clutter hybrid denoising algorithm based on VMD 基于VMD的海杂波混合去噪算法

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2019-11-01 DOI: 10.1109/ICEMI46757.2019.9101554

Sun Jiang, Xing Hongyan, Wu Jiajia

引用次数: 0

Methods and research on detection of transmittance of muzzle smoke 枪口烟雾透过率检测方法与研究

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2019-11-01 DOI: 10.1109/ICEMI46757.2019.9101447

Du Enwu, Jiang Jian, L. Jiannan, Zou Hai

引用次数: 1

Bearing fault diagnosis from raw vibration signals using multi-layer extreme learning machine 基于多层极限学习机的原始振动信号轴承故障诊断

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2019-11-01 DOI: 10.1109/ICEMI46757.2019.9101840

Z. Guangquan, Wu Kankan, Gao Yong-cheng, L. Yongmei, Hu Cong

{"title":"Bearing fault diagnosis from raw vibration signals using multi-layer extreme learning machine","authors":"Z. Guangquan, Wu Kankan, Gao Yong-cheng, L. Yongmei, Hu Cong","doi":"10.1109/ICEMI46757.2019.9101840","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101840","url":null,"abstract":"In recent years, machine learning technology is widely used in the field of fault diagnosis for bearings. Although these methods usually work well, the following defects still exist when they are dealing with large amount of fault data: (1) feature extraction methods need to rely on expertise or signal processing technologies. Therefore, there is a lack of a feature extraction method that is common to different diagnostic problems; (2) shallow models can't learn more complex mapping relationships well; (3) traditional intelligent diagnostic methods are usually computationally intensive and slow in convergence. Inspired by the Auto-encoder’s (AE) feature extraction capability and fast training speed of the Extreme Learning Machine (ELM), a new fault diagnosis method for bearings based on Extreme Learning Machine-Autoencoder (ELM-AE) is proposed in this paper. With its automatic feature extraction capability and very efficient learning strategy, the raw vibration signals of bearings are directly sent to the model without any manual feature extraction for fault diagnosis, which overcomes the above drawbacks. The experimental results on CWRU bearing dataset show that the proposed method takes into account both diagnostic accuracy and time efficiency. Compared with existing literatures, our proposed method obtains superior accuracy.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131602800","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

Incremental fault diagnosis method for space on-orbit equipment 空间在轨设备故障增量诊断方法

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2019-11-01 DOI: 10.1109/ICEMI46757.2019.9101518

Wang Zhenya, Yong Yingqiong, Zheng Benchang, Lu Ying

引用次数: 0

Design of high-speed information channel for satellite test based on serial Rapid I/O 基于串行快速I/O的卫星试验高速信息通道设计

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2019-11-01 DOI: 10.1109/ICEMI46757.2019.9101656

Zhang Bo, L. Jun, Liu Li, Gao Qi, Cui Xiuhai

{"title":"Design of high-speed information channel for satellite test based on serial Rapid I/O","authors":"Zhang Bo, L. Jun, Liu Li, Gao Qi, Cui Xiuhai","doi":"10.1109/ICEMI46757.2019.9101656","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101656","url":null,"abstract":"With the increasing demand for test data and increasing timeliness requirement of the satellite on-orbit test system, the traditional satellite on-orbit test system exposes the problem of insufficient rate, low efficiency and large software resource overhead during data transmission between units in the system. Aiming at problem stand above, this paper proposes a high-speed transmission channel based on serial Rapid IO (SRIO) protocol to realize data transmission between units of the system. The proposed high-speed data transmission channel uses SRIO protocol and DMA technology, based on the ZYNQ MPSoC, to design the data transmission channel between the information processing unit and the data storage-unit. Finally, we tested two Xilinx Zynq-7000 SoC Devices, and built 4 SRIO channels between boards developed by the laboratory. Under the condition of less software resources, the single-channel transmission speed can reach 4.4Gb/s and the transmission efficiency is over 88%. The result indicates that the proposed channel has the characteristics of high speed, high efficiency, light weight and high reliability.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122901412","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: 2

An energy node-based modelling method for indoor energy flow state of industrial buildings 基于能量节点的工业建筑室内能量流状态建模方法

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2019-11-01 DOI: 10.1109/ICEMI46757.2019.9101494

Shi Xin, Tian Wenbin

引用次数: 0

Study on BP neural network model of optical system parameters based on temperature variation 基于温度变化的光学系统参数BP神经网络模型研究

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2019-11-01 DOI: 10.1109/ICEMI46757.2019.9101803

L. Liwei, Zhao Zijun, Xu Qian, Wu Liang

引用次数: 1

Research on fault-tolerant flight control computer for unmanned air vehicle 无人机容错飞控计算机研究

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2019-11-01 DOI: 10.1109/ICEMI46757.2019.9101629

Pan Jihui

引用次数: 1

Traffic sign classification network using inception module 网络交通标志分类使用inception模块

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2019-11-01 DOI: 10.1109/ICEMI46757.2019.9101433

Zhao Dongfang, Kang Wenjing, Li Tao, Li Gongliang

{"title":"Traffic sign classification network using inception module","authors":"Zhao Dongfang, Kang Wenjing, Li Tao, Li Gongliang","doi":"10.1109/ICEMI46757.2019.9101433","DOIUrl":"https://doi.org/10.1109/ICEMI46757.2019.9101433","url":null,"abstract":"With the rapid development of the automobile industry, the demand for autonomous driving becomes more and more urgent, and the traffic sign recognition technology in autonomous driving is an indispensable technology. This paper proposes a GoogLeNet based convolutional neural network for traffic signs. This convolutional neural network improves each of the underlying Inception Modules and adds the Batch Normalization layer, effectively avoiding over-fitting of the network. We use a sparse structure that conforms to the Hebbain principle to reduce the parameters and improve the generalization ability of the network, which can extract the features of the image more accurately. Meanwhile, the network also reduces the parameters of the full connection layer by 20 times through the continuous two-layer pooling layer, which greatly speeds up the network training. Finally, the network is trained using the GTSRB data set and the classification accuracy rate can reach 98%. At the same time, we also verified the validity of the network on the MNIST dataset and the pneumonia dataset. The classification accuracy rate can reach 100% on the above two datasets. Experimental results on the above data sets show the validity of the convolutional neural network.","PeriodicalId":419168,"journal":{"name":"2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128722420","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

Measurement of air attenuation and recombination correction factors in synchrotron radiation X-rays 同步辐射x射线中空气衰减和复合校正因子的测量

2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2019-11-01 DOI: 10.1109/ICEMI46757.2019.9101519

Guo Siming, Wan PeiWei, Wang Ji, Wu Jinjie, Zhang Jian

引用次数: 0