Day 2 Tue, March 22, 2022最新文献_第4页

Diagnosis of Partial Discharge in Power Transformer using Convolutional Neural Network 用卷积神经网络诊断电力变压器局部放电

Day 2 Tue, March 22, 2022 Pub Date : 2022-04-30 DOI: 10.36548/jscp.2022.1.004

S. Sowndarya, S. Balaraman

{"title":"Diagnosis of Partial Discharge in Power Transformer using Convolutional Neural Network","authors":"S. Sowndarya, S. Balaraman","doi":"10.36548/jscp.2022.1.004","DOIUrl":"https://doi.org/10.36548/jscp.2022.1.004","url":null,"abstract":"In an electric power system, power transformers are essential. Transformer failures can degrade the quality of the power and create power outages. Partial Discharges (PD) are a condition that, if not adequately monitored, can cause power transformer failures. This project addresses the diagnosis of PD in power transformer using the Phase Amplitude (PA) response of PRPD (Phase-Resolved Partial Discharge) patterns recorded using PD Detectors. It is a widely used pattern for analysing Partial Discharge. A Convolutional Neural Network (CNN) is used to classify the type of PD defects. The PRPD patterns of 240 PA sample images have been taken from power transformer of rating 132/11 KV and 132/25 KV for training and testing the network. The feature extraction has also been done using CNN. In this work, the classification of PD faults is done using a supervised machine learning technique. The three different classes of PD faults such as Floating PD, Surface PD and Void PD are considered and predicted using Support Vector Machine (SVM) classifier. Simulation study is carried out using MATLAB. Based on the results obtained, it is found that CNN model has achieved a greater classification accuracy and thereby the life span of power transformer is enhanced.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89351469","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

Emotion Recognition from Speech using SVM and Random Forest Classifier 基于SVM和随机森林分类器的语音情感识别

Day 2 Tue, March 22, 2022 Pub Date : 2022-04-30 DOI: 10.36548/jscp.2022.1.005

A. S. Wincy Pon Annal, R. Manonmani, C. Booma

{"title":"Emotion Recognition from Speech using SVM and Random Forest Classifier","authors":"A. S. Wincy Pon Annal, R. Manonmani, C. Booma","doi":"10.36548/jscp.2022.1.005","DOIUrl":"https://doi.org/10.36548/jscp.2022.1.005","url":null,"abstract":"Speech is the most natural way of people to communicate with one another. It is a vital medium for communicating a person's thoughts, feelings, and mental condition to others. The process of identifying the intellectual state is the recognition of basic emotion through speech. In human life, emotions are incredibly significant. In this project, the emotion is recognized from speech using Support Vector Machine (SVM) and Random Forest classifiers. These are supervised machine learning algorithms used for both classification and regression problems. SVM classifies data by creating N-dimensional hyper planes that divide the input into different categories. The classification is accomplished using a linear and non-linear separation surface in the dataset's input feature. Random Forest is a classifier that combines a number of decision trees on different subsets of a dataset and averages the results to increase the dataset's predicted accuracy. These classifiers are used to categorize emotions like happiness, rage, sadness and neutral for a certain incoming voice signal. Here, the system is trained and developed to recognize emotion in real-time speech. The result demonstrates that the Random Forest classifier is significantly better, when compared to the SVM classifier.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"10 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89825144","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

Hardware Implementation of IoT based Smart Power Protection Unit for Power Distribution System 基于物联网的配电系统智能电源保护单元硬件实现

Day 2 Tue, March 22, 2022 Pub Date : 2022-04-30 DOI: 10.36548/jucct.2022.1.002

G. Uma Shankar, S. Chitra

引用次数: 0

An IoT based Automated and Intelligent System for Patient Health 基于物联网的患者健康自动化智能系统

Day 2 Tue, March 22, 2022 Pub Date : 2022-04-30 DOI: 10.36548/jscp.2022.1.006

S. Nivedita, R. Kala

{"title":"An IoT based Automated and Intelligent System for Patient Health","authors":"S. Nivedita, R. Kala","doi":"10.36548/jscp.2022.1.006","DOIUrl":"https://doi.org/10.36548/jscp.2022.1.006","url":null,"abstract":"The Internet of Things (IoT) has remained extensively to connect accessible medical resources and provide smooth, dependable, and in effect of healthcare services to patients, and it has the potential to disrupt healthcare innovation. Health monitoring system using IoT application is the recent trend in medical field, by discovering the potential of the technology. Humans are incrassating the several issues and precocious death due to numerous illness, and by deficiency in providing medical treatment to the patients. To obtain the solution to this issue, a real time health monitoring system is proposed based on the recent technology such as IoT. Enhanced and intelligent healthcare system is the representation of developed and prosperous nation. The proposed method improves the monitoring system by shrinking the use of sensors, which have been attempted to exploit the new technology to obtain the solution for the healthcare problem currently society is facing, and a remote healthcare system is designed. The proposed automated and intelligent system involved with the different phases such as revealing the vitality of patient’s using sensors, sends patients data to cloud storage and thus providing it to the doctors to utilize it, which will help to access and observe the patient’s well-being improvement away from hospital locations. The proposed automated and intelligent system is used to interconnect the accessible medical resources and offer smart, reliable, and effective healthcare system to the people. An IoT architecture with customized healthcare applications have been developed to support remote health monitoring system.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78842639","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

Design and Implementation of MPPT based Solar Powered Wireless Battery Charger 基于MPPT的太阳能无线充电器的设计与实现

Day 2 Tue, March 22, 2022 Pub Date : 2022-04-30 DOI: 10.36548/jucct.2022.1.003

P. Aswin, T. Thamizh Malar Mathi, R. Vikraman, S. Chitra

引用次数: 1

Analysis of AC-DC Load Flow using G-S Approach 用G-S方法分析交直流负荷潮流

Day 2 Tue, March 22, 2022 Pub Date : 2022-04-29 DOI: 10.36548/jei.2022.1.001

Reshma Muralidharan, Rajeswari Ramachandran, G. T. Subham, Jeevitha Kandasamy

引用次数: 0

Model Predictive Control Based Grid Connected Inverter for Renewable Energy Applications 基于模型预测控制的可再生能源并网逆变器

Day 2 Tue, March 22, 2022 Pub Date : 2022-04-29 DOI: 10.36548/jei.2022.1.003

K. Balakrishnan, K. Yasoda

引用次数: 0

Simulation of Standalone Hybrid Solar-Battery Fed Water Pumping System 独立混合太阳能-电池供水泵系统仿真

Day 2 Tue, March 22, 2022 Pub Date : 2022-04-29 DOI: 10.36548/jei.2022.1.004

A. Sumithara, S. Chitra

引用次数: 1

Single Phase Water Pumping System using Adaptive Neuro Fuzzy Inference MPPT for PV system 基于自适应神经模糊推理的光伏系统单相抽水系统

Day 2 Tue, March 22, 2022 Pub Date : 2022-04-29 DOI: 10.36548/jei.2022.1.002

M. Kabilan, V. Gopalakrishnan

{"title":"Single Phase Water Pumping System using Adaptive Neuro Fuzzy Inference MPPT for PV system","authors":"M. Kabilan, V. Gopalakrishnan","doi":"10.36548/jei.2022.1.002","DOIUrl":"https://doi.org/10.36548/jei.2022.1.002","url":null,"abstract":"The demand for water in India steadily increases as the population grows. Due to its numerous advantages, research in AC motor-based Water Pumping Systems (WPS) has recently got a lot of attention. Because of its natural abundance and ecologically beneficial properties, renewable energy-based solar photovoltaic (PV) generation is the ideal substitute for conventional energy sources. Maximum power extraction from the PV system is critical for increasing solar power generation efficiency. This proposed work presents a solar power system using Adaptive Neuro-Fuzzy Inference System (ANFIS) Maximum Power Point Tracking (MPPT) for pumping system. A MPPT controller based on ANFIS has been introduced in this research. This approach has the advantage of having a higher tracking accuracy. This tracker captures irradiance and temperature from the solar panel as inputs. This system uses a battery backup for energy storage purpose. The battery is recharged using the solar supply. In this system, Pulse Width Modulated (PWM) inverter is used, where it converts the battery voltage (DC), into AC voltage for running the pumping system. For validation, the proposed model is analysed using MATLAB/Simulink.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"455 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80255508","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

Sinhala Sign Language Recognition using Leap Motion and Deep Learning 使用跳跃运动和深度学习的僧伽罗手语识别

Day 2 Tue, March 22, 2022 Pub Date : 2022-04-16 DOI: 10.36548/jaicn.2022.1.004

Priyantha Kumarawadu, M. Izzath

引用次数: 0