Pub Date : 2024-09-16DOI: 10.1109/ICJECE.2024.3446351
{"title":"IEEE Canadian Journal of Electrical and Computer Engineering","authors":"","doi":"10.1109/ICJECE.2024.3446351","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3446351","url":null,"abstract":"","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"C2-C2"},"PeriodicalIF":2.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10680488","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-02DOI: 10.1109/ICJECE.2024.3439867
Kola Leleedhar Rao
Different cases have been exercised to create real-time feasibility for erecting solar photovoltaic (PV) system on the roofs of the seven sheds being utilized as six workshops (WSs) and one central store (CS) within a higher educational institution. The obtained results are so intensive that for the WS and CS sheds, the average daily normalized production (ADNP) in kWh/kWp/Day is more on the south-facing roofs (4.20) followed by west- (4.06), east- (3.96), and north-facing roofs (3.78). The mean average additional energy (MAAE) of about 11.27% and 2.52% can be generated on south- and west-facing roofs compared to the north- and east-facing roofs, respectively. In comparison to the vertical installation (VI), the average specific production (ASP) in kWh/kWp/Annum is more with the horizontal installation (HI) of PV modules on either side of the exposed roofs for WS (1459.25) and less for CS (1454.5). The total maximum energy that can be generated on the roofs of total seven sheds is about 969 566 kWh/Annum, which may reduce about 824.12 ton of CO2 emissions per annum. It is an appreciable figure and could pave a path for establishing green electricity. The outcomes of the presented study address the energy sustainability challenges of a higher educational institution.
{"title":"Green Electricity Share Enhancement Through Rooftop Solar PV System on Institutional Sheds","authors":"Kola Leleedhar Rao","doi":"10.1109/ICJECE.2024.3439867","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3439867","url":null,"abstract":"Different cases have been exercised to create real-time feasibility for erecting solar photovoltaic (PV) system on the roofs of the seven sheds being utilized as six workshops (WSs) and one central store (CS) within a higher educational institution. The obtained results are so intensive that for the WS and CS sheds, the average daily normalized production (ADNP) in kWh/kWp/Day is more on the south-facing roofs (4.20) followed by west- (4.06), east- (3.96), and north-facing roofs (3.78). The mean average additional energy (MAAE) of about 11.27% and 2.52% can be generated on south- and west-facing roofs compared to the north- and east-facing roofs, respectively. In comparison to the vertical installation (VI), the average specific production (ASP) in kWh/kWp/Annum is more with the horizontal installation (HI) of PV modules on either side of the exposed roofs for WS (1459.25) and less for CS (1454.5). The total maximum energy that can be generated on the roofs of total seven sheds is about 969 566 kWh/Annum, which may reduce about 824.12 ton of CO2 emissions per annum. It is an appreciable figure and could pave a path for establishing green electricity. The outcomes of the presented study address the energy sustainability challenges of a higher educational institution.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"158-167"},"PeriodicalIF":2.1,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165085","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}
Pub Date : 2024-08-20DOI: 10.1109/ICJECE.2024.3417470
Goturu Sai Abhishek;Satish Kumar Injeti;Deepak Reddy Pullaguram
This article presents the development and application of a microgrid (MG) power system simulator, with an emphasis on AC MG systems. The simulator’s modeling intends to replicate the dynamic behavior MG and interactions of the MG’s various components, including generators, photovoltaic (PV) systems, energy storage units, and loads. The simulator is compatible with both reactive and active power set points from the controller, enabling a comprehensive analysis of the efficacy of the system. The simulation is correlated with direct field testing; this method offers numerous advantages. It provides a safe and cost-effective environment for conducting extensive simulations, thereby avoiding the potential risks and damages associated with conducting experiments in the real world. The flexibility and scalability of the simulator enable researchers to examine a wide variety of operating scenarios, test various control strategies, and assess the impact of system uncertainties. By utilizing the power system simulator’s capabilities, researchers can obtain valuable insights into the behavior of MGs. They are able to evaluate the efficacy of control algorithms in regulating voltage and frequency, managing power flows, and facilitating seamless transitions between grid-connected and isolated modes of operation. In addition, the simulator permits the identification of prospective obstacles and challenges, the evaluation of various control strategies, and the validation of system performance under a variety of operating conditions. The results of simulations run on the power system simulator provide valuable data for optimizing the design and operation of MGs. They contribute to improving the MG systems’ dependability, stability, and resilience. The power system simulator will continue to play a crucial role in the development and deployment of efficient and sustainable MG systems as modeling techniques and simulation capabilities advance.
{"title":"Enhanced Validation of Intelligent Control Algorithms in AC Microgrids","authors":"Goturu Sai Abhishek;Satish Kumar Injeti;Deepak Reddy Pullaguram","doi":"10.1109/ICJECE.2024.3417470","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3417470","url":null,"abstract":"This article presents the development and application of a microgrid (MG) power system simulator, with an emphasis on AC MG systems. The simulator’s modeling intends to replicate the dynamic behavior MG and interactions of the MG’s various components, including generators, photovoltaic (PV) systems, energy storage units, and loads. The simulator is compatible with both reactive and active power set points from the controller, enabling a comprehensive analysis of the efficacy of the system. The simulation is correlated with direct field testing; this method offers numerous advantages. It provides a safe and cost-effective environment for conducting extensive simulations, thereby avoiding the potential risks and damages associated with conducting experiments in the real world. The flexibility and scalability of the simulator enable researchers to examine a wide variety of operating scenarios, test various control strategies, and assess the impact of system uncertainties. By utilizing the power system simulator’s capabilities, researchers can obtain valuable insights into the behavior of MGs. They are able to evaluate the efficacy of control algorithms in regulating voltage and frequency, managing power flows, and facilitating seamless transitions between grid-connected and isolated modes of operation. In addition, the simulator permits the identification of prospective obstacles and challenges, the evaluation of various control strategies, and the validation of system performance under a variety of operating conditions. The results of simulations run on the power system simulator provide valuable data for optimizing the design and operation of MGs. They contribute to improving the MG systems’ dependability, stability, and resilience. The power system simulator will continue to play a crucial role in the development and deployment of efficient and sustainable MG systems as modeling techniques and simulation capabilities advance.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"148-157"},"PeriodicalIF":2.1,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165107","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}
Pub Date : 2024-08-14DOI: 10.1109/ICJECE.2024.3400048
G. Mariammal;A. Suruliandi;Z. Stamenkovic;S. P. Raja
Research in agriculture is a promising field, and crop prediction for particular land areas is especially critical to agriculture. Such prediction depends on the soil, minerals, and environment, the last of which has been short-changed by changing climatic conditions. Consequently, crop prediction for a particular zone presents difficulties for farmers. This is where machine learning (ML) steps in with techniques that are widely applied in agriculture. This work proposes a weighted stacked ensemble (WSE) method for the crop prediction process. It combines two base learners or classifiers to construct the WSE, which is a single predictive ensemble model, using weighted instances. The experimental outcomes show that the proposed WSE outperforms other classification and ensemble techniques in terms of improved crop prediction accuracy.
{"title":"A Novel Ensemble Machine Learning Algorithm for Predicting the Suitable Crop to Cultivate Based on Soil and Environment Characteristics","authors":"G. Mariammal;A. Suruliandi;Z. Stamenkovic;S. P. Raja","doi":"10.1109/ICJECE.2024.3400048","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3400048","url":null,"abstract":"Research in agriculture is a promising field, and crop prediction for particular land areas is especially critical to agriculture. Such prediction depends on the soil, minerals, and environment, the last of which has been short-changed by changing climatic conditions. Consequently, crop prediction for a particular zone presents difficulties for farmers. This is where machine learning (ML) steps in with techniques that are widely applied in agriculture. This work proposes a weighted stacked ensemble (WSE) method for the crop prediction process. It combines two base learners or classifiers to construct the WSE, which is a single predictive ensemble model, using weighted instances. The experimental outcomes show that the proposed WSE outperforms other classification and ensemble techniques in terms of improved crop prediction accuracy.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"127-135"},"PeriodicalIF":2.1,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013341","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}
This study presents a novel approach for solving the economic dispatch (ED) problem in groups of generating units communicating through a communication network. The suggested strategy is a consensus-based dynamic event-triggered (ET) distributed optimization method. Our methodology considers the sharing of the local information between generators and their convex cost functions to address the total cost function and offers a decentralized optimization solution over a network. The proposed distributed method addresses the ED problem by considering the criterion of optimal cost and by offering efficient communication. Generating units are grouped according to their generation operational limits, that is, total capacity and dynamic ET distributed protocols are developed to ensure the consensus of cost variables among generating units, operating under normal capacity conditions. The remaining generating agents work on their operating limits, which are segregated through the sharing of flag information through a switching mechanism. Consequently, in contrast to the existing methods, the recommended protocol allows nodes to function in groups, based on the power supply, for ED with geographical clustering and capacity restrictions, in addition to handling the system constraints. Furthermore, the proposed technique employs a dynamic triggering method to manage bandwidth and guarantee the elimination of Zeno behavior. The simulation results validate the efficacy of the proposed approach.
本研究提出了一种解决通过通信网络通信的发电机组经济调度（ED）问题的新方法。所建议的策略是一种基于共识的动态事件触发（ET）分布式优化方法。我们的方法考虑了发电机之间的局部信息共享及其凸成本函数，以解决总成本函数问题，并通过网络提供分散优化解决方案。建议的分布式方法通过考虑最优成本标准和提供高效通信来解决 ED 问题。根据发电运行限制（即总容量）对发电机组进行分组，并制定动态 ET 分布式协议，以确保在正常容量条件下运行的发电机组之间就成本变量达成共识。其余发电代理则根据其运行极限工作，通过切换机制共享标志信息将其隔离。因此，与现有方法不同的是，建议的协议允许节点根据电力供应情况分组运行，以应对 ED 的地理集群和容量限制，此外还能处理系统约束。此外，建议的技术还采用了动态触发方法来管理带宽，并保证消除 Zeno 行为。仿真结果验证了所提方法的有效性。
{"title":"Consensus and Clustering Approach for Dynamic Event-Triggered Distributed Optimization of Power System Networks With Saturation Constraint Approche de consensus et de regroupement pour","authors":"Ijaz Ahmed;Muhammad Rehan;Abdul Basit;Fahad Saleh Al-Ismail;Muhammad Khalid","doi":"10.1109/ICJECE.2024.3402961","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3402961","url":null,"abstract":"This study presents a novel approach for solving the economic dispatch (ED) problem in groups of generating units communicating through a communication network. The suggested strategy is a consensus-based dynamic event-triggered (ET) distributed optimization method. Our methodology considers the sharing of the local information between generators and their convex cost functions to address the total cost function and offers a decentralized optimization solution over a network. The proposed distributed method addresses the ED problem by considering the criterion of optimal cost and by offering efficient communication. Generating units are grouped according to their generation operational limits, that is, total capacity and dynamic ET distributed protocols are developed to ensure the consensus of cost variables among generating units, operating under normal capacity conditions. The remaining generating agents work on their operating limits, which are segregated through the sharing of flag information through a switching mechanism. Consequently, in contrast to the existing methods, the recommended protocol allows nodes to function in groups, based on the power supply, for ED with geographical clustering and capacity restrictions, in addition to handling the system constraints. Furthermore, the proposed technique employs a dynamic triggering method to manage bandwidth and guarantee the elimination of Zeno behavior. The simulation results validate the efficacy of the proposed approach.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"136-147"},"PeriodicalIF":2.1,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013420","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}
Pub Date : 2024-06-14DOI: 10.1109/ICJECE.2024.3379100
{"title":"IEEE Canadian Journal of Electrical and Computer Engineering","authors":"","doi":"10.1109/ICJECE.2024.3379100","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3379100","url":null,"abstract":"","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 2","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10557783","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141326286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12DOI: 10.1109/ICJECE.2024.3398653
Wu-Chih Hu;Liang-Bi Chen;Hong-Ming Lin
The fish industry is an important source of income for island countries. Fish is a main source of animal-based protein. Marine fishing is gradually being replaced by marine farming (or aquaculture) due to declining wild fish populations and water pollution. However, fish farming is costly job with high requirements for labor, electricity, water, and feed. The use of deep learning to perform intelligent surveillance in aquaculture fields, reducing the need for human resources and implementing real-time monitoring, has been proposed. In this article, we propose a novel deep residual network (ResNeXt $3 times 1 mathrm{D}$ ) for abnormal behavior recognition in aquaculture fields. The proposed ResNeXt $3 times 1 D$ convolutional network is mainly based on an $R(2+1) D$ convolutional network and modified to obtain better performance. Experimental results showed that the proposed ResNeXt $3 times 1 D$ exhibited good performance for abnormal behavior recognition in aquaculture fields. Specifically, the accuracy obtained using the proposed ResNeXt $3 times 1 mathrm{D}$ for abnormal behavior recognition in aquaculture fields was approximately $95.3 %$ .
渔业是岛屿国家的重要收入来源。鱼类是动物性蛋白质的主要来源。由于野生鱼类数量减少和水污染，海洋捕捞逐渐被海洋养殖（或水产养殖）所取代。然而，养鱼成本高昂，对劳动力、电力、水和饲料的要求很高。有人提出利用深度学习对水产养殖领域进行智能监控，以减少对人力资源的需求并实施实时监控。本文提出了一种新型深度残差网络（ResNeXt $3 times 1 mathrm{D}$ ），用于水产养殖领域的异常行为识别。所提出的 ResNeXt $3 times 1 D$ 卷积网络主要基于 $R(2+1) D$ 卷积网络，并对其进行了改进以获得更好的性能。实验结果表明，所提出的 ResNeXt 3 times 1 D$ 在水产养殖领域的异常行为识别中表现出了良好的性能。具体来说，使用所提出的 ResNeXt $3times 1 mathrm{D}$ 进行水产养殖领域异常行为识别的准确率约为 95.3 %$ 。
{"title":"A Method for Abnormal Behavior Recognition in Aquaculture Fields Using Deep Learning","authors":"Wu-Chih Hu;Liang-Bi Chen;Hong-Ming Lin","doi":"10.1109/ICJECE.2024.3398653","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3398653","url":null,"abstract":"The fish industry is an important source of income for island countries. Fish is a main source of animal-based protein. Marine fishing is gradually being replaced by marine farming (or aquaculture) due to declining wild fish populations and water pollution. However, fish farming is costly job with high requirements for labor, electricity, water, and feed. The use of deep learning to perform intelligent surveillance in aquaculture fields, reducing the need for human resources and implementing real-time monitoring, has been proposed. In this article, we propose a novel deep residual network (ResNeXt \u0000<inline-formula> <tex-math>$3 times 1 mathrm{D}$ </tex-math></inline-formula>\u0000) for abnormal behavior recognition in aquaculture fields. The proposed ResNeXt \u0000<inline-formula> <tex-math>$3 times 1 D$ </tex-math></inline-formula>\u0000 convolutional network is mainly based on an \u0000<inline-formula> <tex-math>$R(2+1) D$ </tex-math></inline-formula>\u0000 convolutional network and modified to obtain better performance. Experimental results showed that the proposed ResNeXt \u0000<inline-formula> <tex-math>$3 times 1 D$ </tex-math></inline-formula>\u0000 exhibited good performance for abnormal behavior recognition in aquaculture fields. Specifically, the accuracy obtained using the proposed ResNeXt \u0000<inline-formula> <tex-math>$3 times 1 mathrm{D}$ </tex-math></inline-formula>\u0000 for abnormal behavior recognition in aquaculture fields was approximately \u0000<inline-formula> <tex-math>$95.3 %$ </tex-math></inline-formula>\u0000.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 3","pages":"118-126"},"PeriodicalIF":2.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142013197","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}
The permanent magnet synchronous motor (PMSM) has a more efficiency, high torque density, and high power density, but it suffers from torque ripple. This article describes the electromagnetic (EM) behavior of M19 29Ga material assists PMSM for 310 V, 5 A, and 1500 r/min. In addition, various materials as Losil 34050, Arnon 5, 50M290, M19 USS Transformer 72–29 gauge, and TR80 USS Transformer 80–29 gauge incorporated PMSM and which material has superiority, and with the superiority kept constant, changed the various magnet materials. The EEC 26-T350, MQP-14–12 835995, N45M, Recoma 22, Samarium Cobalt 20/30, Vacodym 890TP, and Vacomax 240 incorporated PMSM also investigated for EM finite-element analysis. The results of this study of the variable as torque ripple forecast the highest torque ( $T_{mathrm {max}})$ , lowest power output ( $T_{mathrm {min}})$ , and overall torque ( $T_{mathrm {avg}})$ . The superior motor among various materials unified PMSM by its ripple and field characteristics. The outcomings of the modeled motor are validated with numerical equations.
{"title":"Impacts of Laminating Core Materials on Permanent Magnet Synchronous Motor by Newton–Raphson Methodc","authors":"Prabhu Sundaramoorthy;Arun Vijayakumar;Kuppapillai Rajkumar;Jamuna Ponnusamy;Gokul Chandrasekaran;Vijayakumar Madhaiyan","doi":"10.1109/ICJECE.2024.3370973","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3370973","url":null,"abstract":"The permanent magnet synchronous motor (PMSM) has a more efficiency, high torque density, and high power density, but it suffers from torque ripple. This article describes the electromagnetic (EM) behavior of M19 29Ga material assists PMSM for 310 V, 5 A, and 1500 r/min. In addition, various materials as Losil 34050, Arnon 5, 50M290, M19 USS Transformer 72–29 gauge, and TR80 USS Transformer 80–29 gauge incorporated PMSM and which material has superiority, and with the superiority kept constant, changed the various magnet materials. The EEC 26-T350, MQP-14–12 835995, N45M, Recoma 22, Samarium Cobalt 20/30, Vacodym 890TP, and Vacomax 240 incorporated PMSM also investigated for EM finite-element analysis. The results of this study of the variable as torque ripple forecast the highest torque (\u0000<inline-formula> <tex-math>$T_{mathrm {max}})$ </tex-math></inline-formula>\u0000, lowest power output (\u0000<inline-formula> <tex-math>$T_{mathrm {min}})$ </tex-math></inline-formula>\u0000, and overall torque (\u0000<inline-formula> <tex-math>$T_{mathrm {avg}})$ </tex-math></inline-formula>\u0000. The superior motor among various materials unified PMSM by its ripple and field characteristics. The outcomings of the modeled motor are validated with numerical equations.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 2","pages":"105-110"},"PeriodicalIF":0.0,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140948906","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}
Armored fighting vehicles (AFVs) of the future will be equipped with electrical drives and many electronic systems, such as computers, sensors, displays, actuators, and other sensitive electronics. Electric drive systems have the potential to substantially increase the efficiency of combat vehicles. The demand for electrical power in AFV has grown beyond the limits of that can be managed by the existing 28-V dc system. There is a necessity to switch from the single electrical bus configuration to a dual bus voltage configuration. This article describes the design procedure of a novel permanent magnet (PM) dual voltage generator for simultaneously providing power at two different voltages. Test results are presented and discussed.
未来的装甲战车（AFV）将配备电力驱动和许多电子系统，如计算机、传感器、显示器、执行器和其他敏感电子设备。电力驱动系统具有大幅提高战车效率的潜力。战车对电力需求的增长已经超出了现有 28 V 直流系统所能满足的极限。因此，有必要将单电气总线配置转换为双总线电压配置。本文介绍了一种新型永磁（PM）双电压发电机的设计过程，该发电机可同时提供两种不同电压的电力。文章还介绍并讨论了测试结果。
{"title":"Design of Novel Single-Frame Dual-Voltage (28-/270-V DC) Permanent Magnet Generator","authors":"Jaishankar Chinnachamy;Hosimin Thilagar Srinivasan","doi":"10.1109/ICJECE.2024.3370589","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3370589","url":null,"abstract":"Armored fighting vehicles (AFVs) of the future will be equipped with electrical drives and many electronic systems, such as computers, sensors, displays, actuators, and other sensitive electronics. Electric drive systems have the potential to substantially increase the efficiency of combat vehicles. The demand for electrical power in AFV has grown beyond the limits of that can be managed by the existing 28-V dc system. There is a necessity to switch from the single electrical bus configuration to a dual bus voltage configuration. This article describes the design procedure of a novel permanent magnet (PM) dual voltage generator for simultaneously providing power at two different voltages. Test results are presented and discussed.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 2","pages":"95-104"},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140948991","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}
Pub Date : 2024-04-19DOI: 10.1109/ICJECE.2024.3368454
Jiazheng Sheng;Siyi Guo;Hui Li;Shengnan Shen;Yikai Zhang;Yicang Huang;Bin Sun;Jian Wang
Convolutional neural networks (CNNs) have drawn huge interest in the field of surface defect classification. During the production of flexible printed circuit boards (FPCBs), only a limited number of images of surface defects can be obtained. FPCB surface defect datasets have small samples and severe imbalances, which can significantly affect defect classification accuracy. Hence, this article presented a lightweight visual geometry group (L-VGG), developed by modifying the classical VGG16 network structure. The L-VGG network was optimized using L2 regularization and sample weighting, which alleviated the over-fitting phenomenon caused by small samples and improved validation accuracy. In addition, the differences among the classification accuracies of different defect images caused by imbalanced datasets were significantly reduced. The training time of the proposed L-VGG network was equivalent to 83.84% and 91.94% compression of the traditional VGG16 and ResNet18 networks, respectively. The dataset augmentation with generated images further mitigates the overfitting phenomenon caused by the small sample problem to some extent, and finally achieves a validation accuracy of 94.20%.
{"title":"Visual Geometry Group Network for Flexible Printed Circuit Board Surface Defect Classification","authors":"Jiazheng Sheng;Siyi Guo;Hui Li;Shengnan Shen;Yikai Zhang;Yicang Huang;Bin Sun;Jian Wang","doi":"10.1109/ICJECE.2024.3368454","DOIUrl":"https://doi.org/10.1109/ICJECE.2024.3368454","url":null,"abstract":"Convolutional neural networks (CNNs) have drawn huge interest in the field of surface defect classification. During the production of flexible printed circuit boards (FPCBs), only a limited number of images of surface defects can be obtained. FPCB surface defect datasets have small samples and severe imbalances, which can significantly affect defect classification accuracy. Hence, this article presented a lightweight visual geometry group (L-VGG), developed by modifying the classical VGG16 network structure. The L-VGG network was optimized using L2 regularization and sample weighting, which alleviated the over-fitting phenomenon caused by small samples and improved validation accuracy. In addition, the differences among the classification accuracies of different defect images caused by imbalanced datasets were significantly reduced. The training time of the proposed L-VGG network was equivalent to 83.84% and 91.94% compression of the traditional VGG16 and ResNet18 networks, respectively. The dataset augmentation with generated images further mitigates the overfitting phenomenon caused by the small sample problem to some extent, and finally achieves a validation accuracy of 94.20%.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"47 2","pages":"70-77"},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140651108","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}
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