2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)最新文献_第5页

A Robust R Peak Recognition Procedure of a cardiac Signal using Modified Db 20 Wavelet Transform 基于改进db20小波变换的心脏信号鲁棒R峰识别方法

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) Pub Date : 2023-02-10 DOI: 10.1109/PIECON56912.2023.10085881

Pragati Tripathi, M. A. Ansari, T. Gandhi, Rajat Mehrotra, Chandresh Singh, Apoorva Singh, Sejal Chauhan

{"title":"A Robust R Peak Recognition Procedure of a cardiac Signal using Modified Db 20 Wavelet Transform","authors":"Pragati Tripathi, M. A. Ansari, T. Gandhi, Rajat Mehrotra, Chandresh Singh, Apoorva Singh, Sejal Chauhan","doi":"10.1109/PIECON56912.2023.10085881","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085881","url":null,"abstract":"Electrocardiogram signal is the utmost crucial parameter for recognition and analysis of cardiovascular disorders. The feature of the ECG signal is removed by the changeable parameter with time by applying some signal processing approach because the graph obtained from analysis is not clear in the case of graphical ECG signal. For analysis purpose a type of WT that is Daubechies wavelet transform is a robust device. In this paper an algorithm for automatic detection of ECG signals the features are extracted and calculated. The data has been occupied from the physio-net.org arrythmia database. For wavelet transform Daubechies wavelet has been used as the scaling functions of this kind of wavelet filter are same to the shape of the ECG. In the primary section, the ECG signal was denoised by excluding the associated higher scale wavelet coefficients. Then in the next section, R wave peaks were diagnosed that have higher dominated amplitude. These diagnosed R peaks were afterwards applied to diagnose the other peaks as P, Q, R.S, T and also the zero-crossing stage. From the distinct peaks, the features of the ECG signal have been extracted. Relying on different features the distinct kinds of disorders are classified.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123549829","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

Statistical Techniques for Prediction of Breakdown Voltage of Liquid Dielectrics used in Power Transformers 电力变压器用液体介质击穿电压预测的统计技术

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) Pub Date : 2023-02-10 DOI: 10.1109/PIECON56912.2023.10085859

Suhaib Ahmad Khan, M. Tariq, M. Farhan, Zuhair Ali Khan

{"title":"Statistical Techniques for Prediction of Breakdown Voltage of Liquid Dielectrics used in Power Transformers","authors":"Suhaib Ahmad Khan, M. Tariq, M. Farhan, Zuhair Ali Khan","doi":"10.1109/PIECON56912.2023.10085859","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085859","url":null,"abstract":"Due to growing energy demand and high transmission voltage, it is desired to have high breakdown strength of the insulating oil to avoid failure of the transformer, which may lead to power supply disruption. Dielectric properties of the conventional insulating oil can be improved by substituting a suitable nanofluid. This paper analyses the AC breakdown strength of transformer oil and TiO2 nanofluid using two statistical techniques, i.e., Weibull distribution and Normal distribution. From the normal distribution, mean value and standard deviation are estimated, while the Weibull distribution is used to estimate the scale and shape parameters. The estimated skewness factor for the normal distribution is observed to be non-zero. The experimental data are distributed asymmetrically according to this non-zero skewness. The asymmetrical form of the Weibull distribution fits the experimental data nicely. The typical breakdown voltage magnitude is provided by the Weibull distribution and is considered more favorable for predicting dielectric breakdown.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121748878","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

Analysis on Misc Type Permanent Magnet Synchronous Reluctance Machine for Transportation Systems 运输系统用复合型永磁同步磁阻电机分析

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) Pub Date : 2023-02-10 DOI: 10.1109/PIECON56912.2023.10085747

S. Prabhu, V. Arun, M. Balaji, V. Kalaimagal, A. Manikandan, V. Chandrasekar

引用次数: 1

Power Quality Improvement using Hopfield Neural Network in Grid Distribution System 在电网配电系统中使用 Hopfield 神经网络改善电能质量

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) Pub Date : 2023-02-10 DOI: 10.1109/PIECON56912.2023.10085879

Pranshu Bansal, Prashant Bharati, Sambhav Jeswani, Ankita Arora

引用次数: 0

A Review on Non-Intrusive Load Monitoring 非侵入式负荷监测技术综述

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) Pub Date : 2023-02-10 DOI: 10.1109/PIECON56912.2023.10085808

Prabhash Kumar Sonwani, Manini Swarnkar, Gurpinder Singh, Amit Soni, A. Swarnkar, K. R. Niazi

引用次数: 0

Review: Lane Detection for Autonomous Vehicles Using Image Processing Techniques 综述:基于图像处理技术的自动驾驶汽车车道检测

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) Pub Date : 2023-02-10 DOI: 10.1109/PIECON56912.2023.10085756

Tanviruzzama, S. Mehfuz

{"title":"Review: Lane Detection for Autonomous Vehicles Using Image Processing Techniques","authors":"Tanviruzzama, S. Mehfuz","doi":"10.1109/PIECON56912.2023.10085756","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085756","url":null,"abstract":"Lane line detection is given great attention in the study on autonomous driving and driver support systems, which, in the last few years, has become a crucial area in the field of intelligent transportation. Without any human involvement, autonomous vehicles can genuinely assess their surroundings, navigate, and provide transportation for people. The transportation system of the entire world will soon be replaced by autonomous vehicles. In order to accomplish this goal, the automobile industries are now researching in this area to maximize the benefits and address the issues [1]. Image processing is a major aspect of the electronic industry’s automation, protection, and surveillance-related applications. This study examined a detailed literature on autonomous vehicle systems, including various types of image preprocessing techniques, lane detection and tracking techniques, and these techniques are utilized to improve lane edge detection. Along with the Canny edge detection methodology, a cutting-edge method known as the Spiking Neural Network for lane boundary detection is also described in this paper. In order to speed up processing, an on-board camera of a vehicle initially sets the region of interest (ROI) on the original picture. The ROI is next subjected to picture preprocessing, which includes converting RGB to grayscale, stretching the grayscale, and using a median filter to remove noise. Hough transform is employed to identify the lane in this study work. Research findings demonstrate that such a strategy is much more reliable and accurate than alternative approaches.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129272673","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

Overview of EV Charging Smart Control Architecture-Recent Developments 电动汽车充电智能控制体系结构综述-最新进展

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) Pub Date : 2023-02-10 DOI: 10.1109/PIECON56912.2023.10085827

Babita Faujdar, R. K. Pandey

{"title":"Overview of EV Charging Smart Control Architecture-Recent Developments","authors":"Babita Faujdar, R. K. Pandey","doi":"10.1109/PIECON56912.2023.10085827","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085827","url":null,"abstract":"Electric Vehicle Charging Infrastructure is an essential component in deployment of Electric Vehicles at large scale in the world. The Smart Control Architecture is the backbone for facilitating the EV charging/Battery swapping in real time environment. The massive usage of EV in transportation is only feasible once the charging infrastructure is structured/facilitated intelligently to provide seamless charging in the respective region with upcoming EV penetration. The massive integration of EVs charging point/bay in Distribution System may also result in an unacceptable performance at given point of time in case the power infeed to the charging infrastructure is not properly regulated depending on the vehicle penetration. The paper firstly reviews the concept for Smart Control Architecture for upcoming EV Charging points/bay in each distribution/sub-transmission system and also highlights the requirements of intelligent power control to the respective charging infrastructure for quality and quick charging in order to ensure regulated power control for distribution system sustainability and reliability.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128042454","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

Effect of Unbalanced Grid Voltage Conditions on The Performance of a Variable Frequency Transformer 电网电压不平衡条件对变频变压器性能的影响

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) Pub Date : 2023-02-10 DOI: 10.1109/PIECON56912.2023.10085818

M. Khan, Imdadullah, M. Bilal

{"title":"Effect of Unbalanced Grid Voltage Conditions on The Performance of a Variable Frequency Transformer","authors":"M. Khan, Imdadullah, M. Bilal","doi":"10.1109/PIECON56912.2023.10085818","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085818","url":null,"abstract":"Power grids are interconnected for economical operation, reliable power supply, and maintaining power supply under contingencies. The grid interconnection can be realized using AC tie lines and HVDC systems. Like the HVDC link, a variable frequency transformer (VFT) is another option available for grid interconnection. The VFT is considered a better option due to its natural damping capability, considerable overloading limit, and lesser requirement of reactive power compensation. This paper analyzes the VFT system connecting two asynchronous power systems under different unbalanced voltage sag conditions. The system performance under symmetrical voltage sag is analyzed for light voltage sag (10% dip), medium voltage sag (30% dip), and severe voltage sag (80% dip). Moreover, it is also analyzed for asymmetrical voltage sag of Type-C, Type-D, and Type-F. The effect of symmetrical and asymmetrical sags on the sending end current, receiving end current, and real power are discussed in detail. The VFT system under various sag conditions is simulated in PSCAD/EMTDC environment.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130963587","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

Low Cost Microcontroller based Experimental Setup to Study Sinusoidal Pulse Width Modulation for Multilevel Inverter 基于低成本单片机的多电平逆变器正弦脉宽调制实验研究

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) Pub Date : 2023-02-10 DOI: 10.1109/PIECON56912.2023.10085863

B. Sakthisudhursun, S. Muralidharan

引用次数: 0

Hybrid Machine Learning Algorithms for Optimal Diagnosis of Heart Disease with Feature Analysis 基于特征分析的心脏疾病最优诊断混合机器学习算法

2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) Pub Date : 2023-02-10 DOI: 10.1109/PIECON56912.2023.10085781

G. Ahmad, H. Fatima, Shafiullah, M. Haris

{"title":"Hybrid Machine Learning Algorithms for Optimal Diagnosis of Heart Disease with Feature Analysis","authors":"G. Ahmad, H. Fatima, Shafiullah, M. Haris","doi":"10.1109/PIECON56912.2023.10085781","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085781","url":null,"abstract":"Timely prediction of heart disease and its cause is the most challenging issue in medical science. This paper uses various machine learning algorithms such as Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Naive Bayes, K-Nearest Neighbourhood, and K-fold cross-validation are used to predict heart diseases. The system uses a K-fold cross-validation technique to enhance the accuracies of algorithms. The UCI Kaggle Cleveland heart disease datasets is used to analyse the performance of the models. It is found in the experiment that the training accuracy of K-Nearest Neighbour is 88.52%, and Recall is 93.30%. The Random Forest produced the highest and most comparable Receiver Operating Characteristics Curve accuracy. Moreover, the experimental results of the recommended techniques are compared with previous heart disease prediction studies, and it is found that among the suggested technique, the performance of K-Nearest Neighbour is best. The fundamental goal of this study is to design a novel and distinctive model-creation approach for resolving practical issues.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116363233","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