2022 IEEE Industrial Electronics and Applications Conference (IEACon)最新文献_第3页

Fault Diagnosis for Uncertain Steer-by-Wire System via Uncertain Bond Graph and the Adaptive Difference Evolution Mutation Operation 基于不确定键合图和自适应差分演化突变操作的不确定线控转向系统故障诊断

2022 IEEE Industrial Electronics and Applications Conference (IEACon) Pub Date : 2022-10-03 DOI: 10.1109/IEACon55029.2022.9951809

Zhicheng Wang, Ming Yu

引用次数: 1

Evaluation of YOLO-X and MobileNetV2 as Face Mask Detection Algorithms YOLO-X和MobileNetV2作为人脸检测算法的评价

2022 IEEE Industrial Electronics and Applications Conference (IEACon) Pub Date : 2022-10-03 DOI: 10.1109/IEACon55029.2022.9951831

Aaron Berliano Handoko, Vaya Candida Putra, Iwan Setyawan, Darmawan Utomo, Jaewook Lee, Ivanna K. Timotius

{"title":"Evaluation of YOLO-X and MobileNetV2 as Face Mask Detection Algorithms","authors":"Aaron Berliano Handoko, Vaya Candida Putra, Iwan Setyawan, Darmawan Utomo, Jaewook Lee, Ivanna K. Timotius","doi":"10.1109/IEACon55029.2022.9951831","DOIUrl":"https://doi.org/10.1109/IEACon55029.2022.9951831","url":null,"abstract":"Even though COVID-19 still exists, people are more reluctant to wear masks in public places, in fact only 73% of Indonesian still do. Hence, automatic mask surveillance in public places is still needed. In this paper, we compare two algorithms named YOLO-X and MobileNetV2 to detect face masks. YOLO-X was able to outperform other YOLO algorithms in object detection. While, according to researchers, MobileNetV2 achieved 9S% in face mask detection. To fairly evaluate both algorithms we need to conduct research under controlled variables including using the same datasets and devices. We used public datasets which consists of 1493 mask images and 6451 non mask images for training and testing. The results show that YOLO-X outperforms MobileNetV2 as it achieves 95.0%, 98.7%, 93.7%, and 96.1% for accuracy, average precision, recall, and F1-score respectively. YOLO-X also performs better in detecting faces with occlusion such as glasses, hands, and postures than MobileNetV2. However, YOLO-X detects faces and face masks 31.9% slower than MobileNetV2.","PeriodicalId":197307,"journal":{"name":"2022 IEEE Industrial Electronics and Applications Conference (IEACon)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132385600","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

IPL Player Selection using Fuzzy Logic 用模糊逻辑选择IPL球员

2022 IEEE Industrial Electronics and Applications Conference (IEACon) Pub Date : 2022-10-03 DOI: 10.1109/IEACon55029.2022.9951755

Rudra Dutt, Tarun Aditya Kusupati, Akshat Srivastava, Debirupa Hore

引用次数: 2

Modeling of Six-Phase Induction Machine with Two Isolated Neutrals under One Open Phase Fault 一开相故障下双隔离中性点六相感应电机的建模

2022 IEEE Industrial Electronics and Applications Conference (IEACon) Pub Date : 2022-10-03 DOI: 10.1109/IEACon55029.2022.9951719

W. Munim, H. S. Che, M. Tousizadeh, R. Baharom, K. S. Muhammad

{"title":"Modeling of Six-Phase Induction Machine with Two Isolated Neutrals under One Open Phase Fault","authors":"W. Munim, H. S. Che, M. Tousizadeh, R. Baharom, K. S. Muhammad","doi":"10.1109/IEACon55029.2022.9951719","DOIUrl":"https://doi.org/10.1109/IEACon55029.2022.9951719","url":null,"abstract":"Due to the COVID-19 pandemic, traditional laboratory sessions or face-to-face demonstrations for advanced electrical engineering level students in the field of power electronics and drives had to be substituted by e-learning to accommodate the new virtual teaching environment. This paper explains the operation of a symmetrical six-phase induction drive having two isolated neutrals configuration (2N) under one open phase fault (OPF) as a case study. The whole system, including the OPF, has been modeled in MATLAB Simulink which is intended for teaching and research purposes in the field of power electronics and drives. The aim of this paper is to elaborate the pre- and post-fault behaviour of the stator current, speed and torque. The machine model presented here is based on vector space decomposition (VSD) and controller using Indirect Rotor Field Oriented Control (IRFOC). In addition, this paper explains the external resistance used to initiate the OPF. The described MATLAB simulation helps the students to understand and observed the amplitude of stator current during pre- and post-fault conditions with respect to the mechanical loading. This model allows preliminary analysis for monitoring and comparison of machine performance.","PeriodicalId":197307,"journal":{"name":"2022 IEEE Industrial Electronics and Applications Conference (IEACon)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130803225","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

The Role of EEG-based Brain Computer Interface using Machine Learning Techniques: A Comparative Study 基于脑电图的脑机接口与机器学习技术的比较研究

2022 IEEE Industrial Electronics and Applications Conference (IEACon) Pub Date : 2022-10-03 DOI: 10.1109/IEACon55029.2022.9951740

Shazia Khaliq, K. Sivani

{"title":"The Role of EEG-based Brain Computer Interface using Machine Learning Techniques: A Comparative Study","authors":"Shazia Khaliq, K. Sivani","doi":"10.1109/IEACon55029.2022.9951740","DOIUrl":"https://doi.org/10.1109/IEACon55029.2022.9951740","url":null,"abstract":"A brain-computer interface (BCI) is a way for humans and machines to communicate directly. It has been used in many successful ways over the last few decades. A wide variety of fields, from economics to biology, make heavy use of machine and deep learning techniques these days. In general, these strategies may be employed in two ways: adapting well-known models and architectures to the given data or creating custom architectures. There are a lot of ways to speed up the research process, so it is important to know which types of models work best for a certain problem and/or data set. For the first time, a machine learning benchmark for EEG signal classification is presented in this paper. This review article takes a close look at the Brain-Computer Interface (BCI) and how it makes use of Machine Learning (ML) technology. It examines the many sorts of research in this area and explores the significance of ML in executing various BCI tasks. These include mental state detection, task categorization, categorization of emotional states, classification of electroencephalogram signals and the occurrence of event-related potentials (ERP), as well as motor imagery classification. A comparative assessment of the studied approaches is provided in this study, which investigates feature extraction, selection, and classification. BCI and ML advancements are discussed in this article, as well as the types of improvements that will be necessary in the future to produce better BCI applications.","PeriodicalId":197307,"journal":{"name":"2022 IEEE Industrial Electronics and Applications Conference (IEACon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131218379","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

An Appreciation of using Halbach Magnets Array in Axial Flux Permanent Magnet Machines 哈尔巴赫磁体阵列在轴向磁通永磁电机中的应用评述

2022 IEEE Industrial Electronics and Applications Conference (IEACon) Pub Date : 2022-10-03 DOI: 10.1109/IEACon55029.2022.9951746

A. Habib, Muhammad Ammirrul Atiqi Mohd Zainuria, H. S. Che, Ahmad Asrul Ibrahim

{"title":"An Appreciation of using Halbach Magnets Array in Axial Flux Permanent Magnet Machines","authors":"A. Habib, Muhammad Ammirrul Atiqi Mohd Zainuria, H. S. Che, Ahmad Asrul Ibrahim","doi":"10.1109/IEACon55029.2022.9951746","DOIUrl":"https://doi.org/10.1109/IEACon55029.2022.9951746","url":null,"abstract":"Using Halbach magnets array in an axial flux machine offers many benefits, including the needlessness of back iron in the rotor, making it practically ironless. Being ironless, the electric machine becomes highly efficient since there are no core losses. Apart from that, the Halbach magnets array essentially reduces the machine’s axial length. Halbach magnets array uses a unity magnet width to pole pitch ratio $(lambda p)$. In contrast, conventional magnets need an optimized fractional value of magnet width to pole pitch ratio to get higher magnetic flux density. In this study, the strength of the magnetic field density for the Halbach magnets array is examined and compared with that of the conventional magnets array. A fair comparison between the Halbach array and conventional array is only conceivable concerning their magnet volume for an optimized magnet width to pole pitch ratio. A lower machine thickness is always preferable for axial flux machines, where the Halbach array can meet this condition. All the experiments have been conducted in a simulation environment developed in ANSYS Maxwell software.","PeriodicalId":197307,"journal":{"name":"2022 IEEE Industrial Electronics and Applications Conference (IEACon)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122155237","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

Cough Recognition Using Tiny ML 使用微小ML进行咳嗽识别

2022 IEEE Industrial Electronics and Applications Conference (IEACon) Pub Date : 2022-10-03 DOI: 10.1109/IEACon55029.2022.9951763

R. Shankar, K. M. Gautham Mythireyan, Nikitha Reddy Nalla, M. Venkateshkumar

引用次数: 1

Effect of Pole Position and Rotor Geometry in IPMSM with FSCW Stator: An Analytical Study 磁极位置和转子几何形状对FSCW定子永磁同步电动机影响的分析研究

2022 IEEE Industrial Electronics and Applications Conference (IEACon) Pub Date : 2022-10-03 DOI: 10.1109/IEACon55029.2022.9951822

Jaison Christal Jothi, Ria Maria Mathew, K. Akash Phillip, Dona Joy, P. Emmanuel Babu, Sija Gopinathan, B. M. Jos

引用次数: 0

Predictive Model to Compute Eligibility Test for Loans 计算贷款资格测试的预测模型

2022 IEEE Industrial Electronics and Applications Conference (IEACon) Pub Date : 2022-10-03 DOI: 10.1109/IEACon55029.2022.9951727

S. Sripriya, Sai Divya Santoshi Varrey, M. Venkateshkumar

引用次数: 0

Voice Recognition Vehicle Movement System 声音识别车辆运动系统

2022 IEEE Industrial Electronics and Applications Conference (IEACon) Pub Date : 2022-10-03 DOI: 10.1109/IEACon55029.2022.9951743

Muhamad Ridzuan, S. F. S. Adnan

{"title":"Voice Recognition Vehicle Movement System","authors":"Muhamad Ridzuan, S. F. S. Adnan","doi":"10.1109/IEACon55029.2022.9951743","DOIUrl":"https://doi.org/10.1109/IEACon55029.2022.9951743","url":null,"abstract":"Cars are one of the types of transport that people use daily and automotive technology has advanced at an incredible rate. In this study, the researcher developed and tested an automotive innovation by utilizing smartphones, in which existing automotive features can be managed by voice commands. The implementation completed will be able to add another feature to the vehicle. Voice recognition is the procedure of consequently perceiving a certain statement talked by a specific speaker focused around individual data included in discourse waves. This paper tries to control a car with the voice of a human. Recognizing the presence of noise is an important pre-processing task in Voice Recognition systems. Sensitivity to speech fluctuation, a lack of recognition precision, and the inability to mimic are some of the main specialized barriers that prevent a wide range of speech-based recognition systems from being chosen. Voice recognition systems work sensibly well with a quiet condition however inadequately under loud conditions. As a result, the accuracy for the command by the user was around 88.57%. Other than that, the accent user that has been used for the trial was around 100% and for the range of Bluetooth to receive commands from user around 77%. For the percentage area, every time the user gives commands, and the ranges are 11.43% and 33% respectively.","PeriodicalId":197307,"journal":{"name":"2022 IEEE Industrial Electronics and Applications Conference (IEACon)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114207578","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