2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO)最新文献_第3页

A transients segmentation based control for SMES to enhance power system stability 一种基于暂态分段的中小企业控制方法，以提高电力系统的稳定性

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) Pub Date : 2015-09-10 DOI: 10.1109/EESCO.2015.7253961

Xiaohan Shi, Shaorong Wang, A. Waqar, Wenxuan Wu, Jianzhao Guo, Yiyong Zhu

引用次数: 0

Comparison of different DC-DC converter for MPPT application of photovoltaic system 不同DC-DC变换器在光伏系统MPPT应用中的比较

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) Pub Date : 2015-09-10 DOI: 10.1109/EESCO.2015.7253764

Tadiparthi Ramki, L. Tripathy

引用次数: 22

Robotic system using fuzzy logic for person following 机器人系统采用模糊逻辑进行人的跟踪

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) Pub Date : 2015-09-10 DOI: 10.1109/EESCO.2015.7253862

D. Sanjay, P. Kumar, T. Savithri

引用次数: 2

Study of PV array configuration and its effects on performance under non uniform irradiance 非均匀辐照下光伏阵列结构及其对性能影响的研究

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) Pub Date : 2015-09-10 DOI: 10.1109/EESCO.2015.7253902

Mona Marodkar, S. Adhau

引用次数: 4

A low cost robust digital signal analyser (DSO) for measurement applications 用于测量应用的低成本鲁棒数字信号分析仪(DSO)

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) Pub Date : 2015-09-10 DOI: 10.1109/EESCO.2015.7253866

D. Sharma, K. Kishore, Shahid Malik, Dheeraj K. Singhal, Ashish Kumar, S. A. Akbar

引用次数: 0

Classification of brain tumors by mining MRS spectrums using LabVIEW metabolite peak height scanning method 利用LabVIEW代谢物峰高扫描法挖掘MRS谱对脑肿瘤进行分类

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) Pub Date : 2015-01-01 DOI: 10.1109/EESCO.2015.7253868

Jayalaxmi S. Gonal, V. Kohir

引用次数: 1

A novel symmetrical multilevel inverter topology with reduced switching devices using different PWM techniques 一种新颖的对称多电平逆变器拓扑结构，使用不同的PWM技术减少了开关器件

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) Pub Date : 2015-01-01 DOI: 10.1109/EESCO.2015.7253616

Abhishek Kumar, Praveen Bansal

引用次数: 6

Fuzzy control of zero current switching resonant buck converter 零电流开关谐振降压变换器的模糊控制

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) Pub Date : 2015-01-01 DOI: 10.1109/EESCO.2015.7254059

Y. Babu, Tripura Pidikiti, P. Prasanna

引用次数: 1

Environment based threshold for Speaker Identification 基于环境的说话人识别阈值

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) Pub Date : 2015-01-01 DOI: 10.1109/EESCO.2015.7253615

Soumen Kanrar

{"title":"Environment based threshold for Speaker Identification","authors":"Soumen Kanrar","doi":"10.1109/EESCO.2015.7253615","DOIUrl":"https://doi.org/10.1109/EESCO.2015.7253615","url":null,"abstract":"Speaker Identification process is to identify a particular vocal cord from a set of existing speakers. In the speaker identification processes, the unknown speaker voice sample targets each of the existing speakers in the system and gives a predication. The predication is more than one existing known speaker voice and is very close to the unknown speaker voice. It is a one to many mapping. The mapping function gives a set of predicated values associated with the order pair of speakers. In the order pair, the first coordinate is the unknown speaker and the second coordinates is the existing known speaker from the speaker recognition system. The set of predicated values helps to identify the unknown speaker. The identification process makes a comparison of the unknown speaker model with the models of the existing voice in the system. In this paper, the model is a Gaussian mixture model built by the extraction of the acoustic feature vectors. This paper presents the impact of the decision threshold based on false accepts and false reject for an unknown number of speaker conversion in the speaker identification result. In the simulation, the considered known speaker voices are collected through different channels. In the testing, the GMM voice models of the known speakers are distributed among the numbers of clusters in the test data set.","PeriodicalId":305584,"journal":{"name":"2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133219693","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

DFA and DWT based severity detection and discrimination of induction motor stator winding short circuit fault from incipient insulation failure 基于DFA和DWT的异步电动机定子绕组早期绝缘故障的严重程度检测与判别

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO) Pub Date : 1900-01-01 DOI: 10.1109/EESCO.2015.7254026

D. Barman, S. Sarkar, G. Das, S. Das, P. Purkait

{"title":"DFA and DWT based severity detection and discrimination of induction motor stator winding short circuit fault from incipient insulation failure","authors":"D. Barman, S. Sarkar, G. Das, S. Das, P. Purkait","doi":"10.1109/EESCO.2015.7254026","DOIUrl":"https://doi.org/10.1109/EESCO.2015.7254026","url":null,"abstract":"Modern research surveys emphasize that stator winding fault holds a significant percentage in induction motor failures. In Motor Current Signature Analysis (MCSA) based stator winding fault diagnosis, it has been found to be a challenging task to discriminate inter turn short circuit faults from inter-turn incipient insulation failures providing unbalances in three phase motor currents identical to short circuit faults. This paper proposes an approach to achieve this objective by applying Discrete Wavelet Transform (DWT) as signal decomposition tool on the faulty phase motor current captured through CRIO-9075 integrated controller and chassis system having 400MHz power PC controller, LX 25 Gate FPGA with NI 9227. Inverse Discrete Wavelet Transform (IDWT) as signal reconstruction tool has been employed to extract relevant frequency band which is sensitive to stator winding faults. Reconstructed or filtered currents under different fault cases containing specific band of frequency signals are then fed to Detrended Fluctuation Analysis (DFA) algorithm which has the competency to assess trend of fluctuations present in signals under consideration. Results of DFA in the form of short term fluctuation coefficient (αs) and long term fluctuation coefficient (αl) are found to be capable in discriminating the inter-turn short circuit fault from incipient insulation failure. Proposed method is also capable in detecting the severity levels of two different types of fault cases. Entire analysis reported in this work is based on experimentally obtained motor current signals.","PeriodicalId":305584,"journal":{"name":"2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO)","volume":"499 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123565610","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