2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA)最新文献_第7页

Measurement and Control System of Pulse Power Supply Based on HTSPPT 基于HTSPPT的脉冲电源测控系统

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2021-08-01 DOI: 10.1109/ICIEA51954.2021.9516094

Haihang Liu, Huilin Liu, Jianan Liu, D. Teng, Jingbo He

{"title":"Measurement and Control System of Pulse Power Supply Based on HTSPPT","authors":"Haihang Liu, Huilin Liu, Jianan Liu, D. Teng, Jingbo He","doi":"10.1109/ICIEA51954.2021.9516094","DOIUrl":"https://doi.org/10.1109/ICIEA51954.2021.9516094","url":null,"abstract":"In order to monitor the discharge characteristics of the pulse power, control the pulse power reliable operation, the pulse power supply control system based on high temperature superconducting pulsed power transformer (HTSPPT) was designed by using modern test technology, virtual instrument and database technology. The system is comprised of single-chip, drive circuit board, voltage and current sensor, data acquisition system and computer. The software uses LabVIEW, ActiveX Date Objects (ADO) technology was used to realize the data interaction between LabVIEW and database, and realizes the storage and query of large amount of data. In this paper, the pulse power supply of two modules synchronous and asynchronous triggering HTSPT is measured and controlled. The experimental results show that the system can accurately trigger the turn-on and turn-off time of IGBT and thyristor and control the discharge of pulse power process. From the synchronous triggering, we can accurately measure the instantaneous current with the half peak pulse width of 1.33ms and the Instantaneous load current peak value of 6.622kA. The voltage of the auxiliary capacitor is 883V. From the asynchronous cooperative triggering, the half peak pulse width is 2.866ms, the peak value of the Instantaneous load current is 4.233kA and the voltage of auxiliary capacitor is 1.1kV.","PeriodicalId":6809,"journal":{"name":"2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA)","volume":"21 1","pages":"879-883"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78764568","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

Research on data acquisition system of six-dimensional force sensor 六维力传感器数据采集系统的研究

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2021-08-01 DOI: 10.1109/ICIEA51954.2021.9516362

Jingmeng Liu, Yipeng Lu, Zhong Liu, Weihai Chen

引用次数: 0

Modeling and Mitigating LED Nonlinearity using Nonlinear ARX model with Wavelet Networks 基于小波网络的非线性ARX模型建模与缓解LED非线性

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2021-08-01 DOI: 10.1109/ICIEA51954.2021.9516063

Jundao Mo, Xiong Deng, Wenxiang Fan, Yinan Niu, Yixian Dong, Guofu Zhou, J. Linnartz

引用次数: 0

Transformer-based end-to-end scene text recognition 基于变压器的端到端场景文本识别

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2021-08-01 DOI: 10.1109/ICIEA51954.2021.9516154

Xinghao Zhu, Zhi Zhang

引用次数: 1

Performance Analysis and Comparison of Four Conventional Multi-objective Optimization Algorithms 四种传统多目标优化算法的性能分析与比较

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2021-08-01 DOI: 10.1109/ICIEA51954.2021.9516276

Maoyang Fu, Xudong Ding, Biaokun Jia, Zhongchen Liu, Xingkai Zhao, Mei Sun

{"title":"Performance Analysis and Comparison of Four Conventional Multi-objective Optimization Algorithms","authors":"Maoyang Fu, Xudong Ding, Biaokun Jia, Zhongchen Liu, Xingkai Zhao, Mei Sun","doi":"10.1109/ICIEA51954.2021.9516276","DOIUrl":"https://doi.org/10.1109/ICIEA51954.2021.9516276","url":null,"abstract":"With the development of Artificial Intelligence and Big Data, more and more heuristic multi-objective algorithms are applied to the training process of data sets. In this paper, four heuristic multi-objective optimizations which were widely used in the data set training in recent years, are selected for the performance analysis and comparison. Through the comparison and analysis of the performance index for these algorithms on the benchmark problem, the advantages and disadvantages of these strategies in ensuring the convergence of the algorithm and maintaining the diversity of the solution sets are systematically expounded. The simulation results show that these algorithms have their own advantages and disadvantages in solving different specific problems, and the setting of the parameters and the initialization of the solution sets will have a great impact on the performance of the algorithm. Moreover, the different methods have the different abilities in maintaining the convergence and diversity of the solution sets. Although the complex optimization method has a better solution effect, the calculation time cost is higher. In practical application, it is necessary to select the appropriate algorithm flexibly according to the actual problems and conditions.","PeriodicalId":6809,"journal":{"name":"2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA)","volume":"1 1","pages":"1513-1519"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89387554","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

A Feasible Method for Evaluating Energy Consumption of Industrial Robots 一种可行的工业机器人能耗评估方法

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2021-08-01 DOI: 10.1109/ICIEA51954.2021.9516218

Binquan Qiu, Si-lu Chen, Tao Xiao, Yingkui Gu, Chi Zhang, Guilin Yang

引用次数: 3

Charge-biased Synchronized Triple Bias Flip Circuit for Piezoelectric Energy Harvesting 用于压电能量收集的电荷偏置同步三偏置翻转电路

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2021-08-01 DOI: 10.1109/ICIEA51954.2021.9516398

Xue-chu Shen, Qinyao Yang, Rui Jiang, Feng Zhang, Zhibin Du, Siyu Zhang, Zhihao Liu, Zhiwei Wang, L. Bu

引用次数: 1

Face Image Based Automatic Diagnosis by Deep Neural Networks 基于深度神经网络的人脸图像自动诊断

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2021-08-01 DOI: 10.1109/ICIEA51954.2021.9516294

Lulu Niu, Gang Xiong, Zhen Shen, Z. Pan, Shi Chen, Xisong Dong

{"title":"Face Image Based Automatic Diagnosis by Deep Neural Networks","authors":"Lulu Niu, Gang Xiong, Zhen Shen, Z. Pan, Shi Chen, Xisong Dong","doi":"10.1109/ICIEA51954.2021.9516294","DOIUrl":"https://doi.org/10.1109/ICIEA51954.2021.9516294","url":null,"abstract":"In this paper, we use ResNet based networks for the automatic diagnosis of the Turner Syndrome (TS) by facial images. The TS is a common sex chromosomal disorder, which is due to the total or partial absence or structural abnormality of the X chromosome. Nowadays, the diagnosis of the TS mainly depends on peripheral blood lymphocyte chromosome karyotype analysis, which is time consuming. For inexperienced doctors, it is difficult to diagnose the TS only based on facial features, and there may be missed and inaccurate diagnosis. In order to help the TS patients to get timely diagnosis, we design and train ResNet-based networks to recognize patients' facial features, and build an intelligent system for automatic diagnosis. We evaluate the performance of the ResNet-based networks by sensitivity, specificity, and accuracy. We increase the average sensitivity from 67.6% to 91.54%, average specificity from 87.9% to 98.52%, compared with the AdaBoost method with local features. In the future, we aim to set up the intelligent system on a smart-phone to achieve fast and convenient screening of the TS at an early stage.","PeriodicalId":6809,"journal":{"name":"2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA)","volume":"56 1 1","pages":"1352-1357"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83657862","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

Development of Cascade H Bridge SVG 级联H桥SVG的开发

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2021-08-01 DOI: 10.1109/ICIEA51954.2021.9516073

Gang Li, B. Hu, Chunwei Shao

引用次数: 0

Removal of R134a from air/R134a mixture based on cryogenic condensation method 低温冷凝法去除空气/R134a混合物中的R134a

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA) Pub Date : 2021-08-01 DOI: 10.1109/ICIEA51954.2021.9516311

Boshi Shao, Xiping Kou, Hongbo Tan, Xinghua Yang, Jun Zha, Huizhuo Zhang

{"title":"Removal of R134a from air/R134a mixture based on cryogenic condensation method","authors":"Boshi Shao, Xiping Kou, Hongbo Tan, Xinghua Yang, Jun Zha, Huizhuo Zhang","doi":"10.1109/ICIEA51954.2021.9516311","DOIUrl":"https://doi.org/10.1109/ICIEA51954.2021.9516311","url":null,"abstract":"The emission of greenhouse gases is aggravating the global warming. Nowadays, R134a is widely used in refrigeration engineering, and its globe warming potential (GWP) is relatively high (1301). So, it is imperative to recover the R134a in refrigerating devices, and prevent it from being released to the atmosphere. In present study, the R134a/nitrogen mixture is cooled by cryogenic nitrogen and R134a is removed and captured based on the different boiling point of the mixture. The self-programming approach was adopted to calculate the heat and mass transfer process of the mixture in different molar concentration in a sleeve-type heat exchanger with recuperating. The results of the calculation shown that, the required length of the heat exchanger is different under various molar concentrations. The temperature distribution of the mixture gas, the wall temperatures of the heat exchanger and the cold nitrogen, as well as the molarity and the accumulation of R134a at different length are also computed and plotted into graphs. From the obtained data, it could be found that the molar concentration of R134a in the mixture could be reduced to 100ppm which is low enough to discharge. This work could be referenced by further studies and engineering applications.","PeriodicalId":6809,"journal":{"name":"2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA)","volume":"42 1","pages":"1713-1718"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87529819","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