IEEE Open Journal of the Industrial Electronics Society最新文献

{"title":"Hybrid Modeling of an Induction Machine to Support Bearing Diagnostics","authors":"Praneet Amitabh;Dimitar Bozalakov;Frederik De Belie","doi":"10.1109/OJIES.2024.3461949","DOIUrl":"https://doi.org/10.1109/OJIES.2024.3461949","url":null,"abstract":"In this article, a novel hybrid model of an induction machine is proposed that can emulate the response of a machine with a faulty bearing. The idea behind developing such a topology is to have the response quite close to that from a real asset while keeping it computationally efficient. The aim is to develop an accurate and efficient model, akin to digital twins, which have the potential for real-time operation. Therefore, the model is divided into two parts. One is a physics-based model that takes fundamental equations and motor construction parameters to yield an intermediate response. All the major parameters are taken into account such that the fundamental component comes quite close to that of the real asset and the bearing fault signature comes in the same order. These signatures are quite small and some small parasitic effects or the assumptions taken while simplifying the model might not impact the fundamental component that much but they alter the signature's amplitude quite significantly. One way is to model all the parasitic effects, which might increase the computation effort significantly. Another way is to take all the parasitic effects altogether and bridge the difference using a statistical approach which is developed using experimental data. Therefore, the current measurements were taken for several bearings with different fault severity. These measurements are processed and quantified such that the net outcome can express the evolution of the signature with increasing fault severity. The same is done for the data generated using the physics-based model. Finally, the difference in the responses is reduced using the neural network such that it can mimic real-world machine behavior closely. The analytical model followed by statistical adjustment overall is considered a hybrid model. The ultimate goal of this methodology is to generate extensive datasets encompassing diverse operating conditions that can be used further to estimate the health of the bearing and possibly be used for training predictive algorithms to estimate bearing RUL in motors. The proposed methodology is developed for the machine operating at 1000 and 1500 RPM and is validated for three different operating speeds.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"1140-1157"},"PeriodicalIF":5.2,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681032","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452675","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}

{"title":"Model-Free Predictive Current Controller for Common Mode Voltage Stabilization by Finite odd Virtual Vector set","authors":"Majid Akbari;S. Alireza Davari;Reza Ghandehari;Freddy Flores-Bahamonde;Jose Rodriguez","doi":"10.1109/OJIES.2024.3457835","DOIUrl":"10.1109/OJIES.2024.3457835","url":null,"abstract":"Reducing the common mode voltage (CMV) fluctuations is crucial in transformer-less (T-less) converters. The modulation modification-based methods inherently increase the steady-state error of the compared currents due to the reduced number of voltage vectors. This error can significantly raise the total harmonic distortion (THD) output current of the inverter. This research presents a strategy of odd virtual vectors based on model-free predictive control using the extended state observer (ESO) to fix the CMV fluctuations and a significant decrease in the THD of the output current. This means the number of CMV stabilizing vectors increases with the linear combination of odd voltage vectors. The proposed method has two advantages over CMV fluctuation reduction schemes that are modulation modification-based: simultaneous control of CMV stabilization and THD reduction in T-less converters, and independence of the controller from system variables and parameters, making it a robust predictive control method. The practical results show that the proposed method, in addition to the complete CMV stabilization and the reduction of the current THD, is completely robust to the changes in the parameters of the ultralocal model and ESO compared to the model-based solutions.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"1042-1057"},"PeriodicalIF":5.2,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10675355","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175875","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}

{"title":"Unsupervised and Semisupervised Machine Learning Frameworks for Multiclass Tool Wear Recognition","authors":"Maryam Assafo;Peter Langendoerfer","doi":"10.1109/OJIES.2024.3455264","DOIUrl":"10.1109/OJIES.2024.3455264","url":null,"abstract":"Tool condition monitoring (TCM) is crucial to ensure good quality products and avoid downtime. Machine learning has proven to be vital for TCM. However, existing works are predominately based on supervised learning, which hinders their applicability in real-world manufacturing settings, where data labeling is cumbersome and costly with in-service machines. Additionally, the existing unsupervised solutions mostly handle binary decision-based TCM which is unable to fully reflect the dynamics of tool wear progression. To address these issues, we propose different unsupervised and semisupervised five-class tool wear recognition frameworks to handle fully unlabeled and partially labeled data, respectively. The underlying methods include Laplacian score, sparse autoencoder (SAE), stacked SAE (SSAE), self-organizing map, Softmax, support vector machine, and random forest. For the semisupervised frameworks, we considered designs where labeled data influence only feature learning, classifier building, or both. We also investigated different training configurations of SSAE regarding the supervision level. We applied the frameworks on two run-to-failure datasets of milling tools, recorded using a microphone and an accelerometer. Single sensor and multisensor data under different percentages of labeled training data were considered in the evaluation. The results showed which of the frameworks led to the best predictive performance under which data settings, and highlighted the significance of sensor fusion and discriminative feature representations in combating the unavailability and scarcity of labels, among other findings. The highest macro-F1 achieved for the two datasets with fully unlabeled data reached 87.52% and 75.80%, respectively, and over 90% when only 25% of the training observations were labeled.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"993-1010"},"PeriodicalIF":5.2,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10668405","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175872","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}

{"title":"Battery Energy Storage Systems in Microgrids: A Review of SoC Balancing and Perspectives","authors":"Thales Augusto Fagundes;Guilherme Henrique Favaro Fuzato;Lucas Jonys Ribeiro Silva;Augusto Matheus dos Santos Alonso;Juan C. Vasquez;Josep M. Guerrero;Ricardo Quadros Machado","doi":"10.1109/OJIES.2024.3455239","DOIUrl":"10.1109/OJIES.2024.3455239","url":null,"abstract":"Microgrids (MGs) often integrate various energy sources to enhance system reliability, including intermittent methods, such as solar panels and wind turbines. Consequently, this integration contributes to a more resilient power distribution system. In addition, battery energy storage system (BESS) units are connected to MGs to offer grid-supporting services, such as peak shaving, load compensation, power factor quality, and operation during source failures. In this context, an energy management system (EMS) is necessary to incorporate BESS in MGs. Consequently, state-of-charge (SoC) equalization is a common approach to address EMS requirements and balance the internal load among BESS units in MG operation. In this article, we present a comprehensive review of EMS strategies for balancing SoC among BESS units, including centralized and decentralized control, multiagent systems, and other concepts, such as designing nonlinear strategies, optimal algorithms, and categorizing agents into clusters. Moreover, in this article, we discuss alternatives to improve EMS and strategies regarding the topology of power converters, including redundancy-based topology, modular multilevel converter, cascaded-based converter, and hybrid-type systems. In addition, this article explores optimization processes aimed at reducing operational costs while considering SoC equalization. Finally, second-life BESS units are explored as an emerging topic, focusing on their operation within specific power converters topologies to achieve SoC balance.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"961-992"},"PeriodicalIF":5.2,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10666276","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175873","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}

{"title":"Real-Time Cyber-Physical Digital Twin for Low Earth Orbit Satellite Constellation Network Enhanced Wide-Area Power Grid","authors":"Tianshi Cheng;Tong Duan;Venkata Dinavahi","doi":"10.1109/OJIES.2024.3454010","DOIUrl":"10.1109/OJIES.2024.3454010","url":null,"abstract":"Low Earth orbit (LEO) satellite networks, such as SpaceX's Starlink, offer enhanced communication potential for contemporary power grid measurement and control. Yet, the dynamic nature of these networks complicates their modeling and simulation. This study introduces a modular, data-oriented digital twin framework for real-time simulation of wide-area ac–dc grids with LEO satellite networks. The framework integrates RustSat for satellite tracking, SatSDN with MiniNet for SDN simulations, and entity-component-system (ECS)-Grid for real-time power system simulation. It features a data-centric design using an ECS framework with a structure-of-arrays memory layout, optimizing cache efficiency and computational performance, and offers high extensibility for interdisciplinary simulations. This marks the initial effort to develop a digital twin for real-time co-simulation of large-scale power systems and LEO satellite constellation networks. Evaluations on a wide-area synthetic ac–dc system with multiple satellite network types confirm the efficiency and precision of our approach, underscoring its potential in bridging LEO satellite networks with power system applications.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"1029-1041"},"PeriodicalIF":5.2,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10663871","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175876","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}

{"title":"A Design of a Redundancy-Based Cascaded Bidirectional DC–DC Converter for Improved Reliability in Energy Storage Devices","authors":"Thales Augusto Fagundes;Guilherme Henrique Favaro Fuzato;Rafael Fernando Quirino Magossi;Ana Laís Rui Oliveira;Ricardo Quadros Machado","doi":"10.1109/OJIES.2024.3446911","DOIUrl":"10.1109/OJIES.2024.3446911","url":null,"abstract":"This article proposes a redundancy-based cascaded bidirectional dc/dc converter designed to interface battery energy storage system (BESS) units. With the employment of this topology, its reliability is increased due to redundancy in power conversion, which differs from conventional structures formed by dc/dc converters that cannot process power flow when a fault occurs. Thus, the topology is provided merging the cascaded bidirectional Boost converter and cascaded bidirectional Cuk converter. Subsequently, the coupled mathematical model of the proposed topology can be readily calculated, considering all feasible (different) subcircuits according to the switching pattern. Therefore, small-signal analysis is applied to design the PI controllers, followed by a closed-loop performance evaluation using an infinity norm and stability analysis to assess the operation of the dc/dc converter in closed loop for different values of load and current references. Finally, a lab-scale prototype and a hardware-in-the-loop setup prove the effectiveness of the dc/dc converter working in various scenarios and also operating with the traditional SoC-based droop for balancing the BESS units.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"898-915"},"PeriodicalIF":5.2,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643290","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175881","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}

{"title":"Toward Semantic Event-Handling for Building Explainable Cyber-Physical Systems","authors":"Gernot Steindl;Tobias Schwarzinger;Katrin Schreiberhuber;Fajar J. Ekaputra","doi":"10.1109/OJIES.2024.3447001","DOIUrl":"10.1109/OJIES.2024.3447001","url":null,"abstract":"In the context of cyber-physical systems (CPS), understanding system behaviors is crucial for ensuring reliability, efficiency, and trust. However, due to the increasing complexity of the modern CPS, gaining such understanding is becoming more challenging. In this article we provide a foundation for explaining system behavior through detected system events. To this end, the article proposes a technology-agnostic, semantic event-handling module to address the challenge of enhancing explainability within CPS. This module is designed to be part of the common architecture for Explainable CPS and, therefore, can be integrated seamlessly into existing CPS frameworks by providing different interfaces to access detected events. Two case studies in the smart building and smart grid domain are carried out to demonstrate the feasibility and efficacy of the approach, utilizing an open-source software stack for the prototypical implementation. A qualitative evaluation of the proposed approach, based on the ISO/IEC 25010:2023, was used to analyze the software design. Our evaluation result shows that the semantic event-handling module is appropriate as a generic approach to handling events within a CPS. The module becomes a foundation for incorporating explainability into the system, which is needed as a foundation to ensure human trust and enable informed decision-making.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"928-945"},"PeriodicalIF":5.2,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643286","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175880","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}

{"title":"Explainable Model Prediction of Memristor","authors":"Sruthi Pallathuvalappil;Rahul Kottappuzhackal;Alex James","doi":"10.1109/OJIES.2024.3440578","DOIUrl":"10.1109/OJIES.2024.3440578","url":null,"abstract":"System level simulation of neuro-memristive circuits under variability are complex and follow a black-box neural network approach. In realistic hardware, they are often difficult to cross-check for accuracy and reproducible results. The accurate memristor model prediction becomes critical to decipher the overall circuit function in a wide range of nonideal and practical conditions. In most neuro-memristive systems, crossbar configuration is essential for implementing multiply and accumulate calculations, that form the primary unit for neural network implementations. Predicting the specific memristor model that best fits the crossbar simulations to make it explainable is an open challenge that is solved in this article. As the size of the crossbar increases the cross-validation becomes even more challenging. This article proposes predicting the memristor device under test by automatically evaluating the \u0000<italic>I–V</i>\u0000 behavior using random forest and extreme gradient boosting algorithms. Starting with a single memristor model, the prediction approach is extended to memristor crossbar-based circuits explainable. The performance of both algorithms is analyzed based on precision, recall, f1-score, and support. The accuracy, macro average, and weighted average of both algorithms at different operational frequencies are explored.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"836-846"},"PeriodicalIF":5.2,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10631696","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940425","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}

{"title":"AutomationML Meets Bayesian Networks: A Comprehensive Safety-Security Risk Assessment in Industrial Control Systems","authors":"Pushparaj Bhosale;Wolfgang Kastner;Thilo Sauter","doi":"10.1109/OJIES.2024.3439388","DOIUrl":"10.1109/OJIES.2024.3439388","url":null,"abstract":"Industrial control systems (ICSs) play a crucial role in the smooth operation of critical infrastructures, and their increasing complexity and interconnectedness necessitate integrating safety and security measures. Thus, an integrated risk assessment approach is essential to identify and address potential hazards and vulnerabilities. However, conducting such risk assessments becomes complex and challenging due to the difficulty in data availability. Acquiring data from various sources poses a significant hurdle. To address these challenges, automation markup language (AML) provides a standardized framework that facilitates the seamless exchange of engineering information. This article uses AML libraries and connection setup techniques to generate a valuable model of a single source of data for an integrated safety and security risk assessment. The automated risk assessment employs the AML model as a data source and the Bayesian belief network (BBN) as the risk assessment method. The value of risk associated with the system is calculated using the BBN models as the product of the probability of occurrence and severity. An evaluation of the proposed risk assessment method is also provided based on ISO 31000. AML's effectiveness as a valuable information model in meeting the growing need for comprehensive safety and security risk assessment in ICSs is demonstrated.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"823-835"},"PeriodicalIF":5.2,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10623880","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940426","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}

{"title":"TALESS: TSN With Legacy End-Stations Synchronization","authors":"Daniel Bujosa Mateu;Julian Proenza;Alessandro V. Papadopoulos;Thomas Nolte;Mohammad Ashjaei","doi":"10.1109/OJIES.2024.3436590","DOIUrl":"10.1109/OJIES.2024.3436590","url":null,"abstract":"In order to facilitate the adoption of Time Sensitive Networking (TSN) by the industry, it is necessary to develop tools to integrate legacy systems with TSN. In this article, we propose a solution for the coexistence of different time domains from different legacy systems, each with its corresponding synchronization protocol, in a single TSN network. To this end, we experimentally identified the effects of replacing the communications subsystem of a legacy Ethernet-based network with TSN in terms of synchronization. Based on the results, we propose a solution called TALESS (TSN with Legacy End-Stations Synchronization). TALESS can identify the drift between the TSN communications subsystem and the integrated legacy devices (end-stations) and then modify the TSN schedule to adapt to the different time domains to avoid the effects of the lack of synchronization between them. We validate TALESS through both simulations and experiments on a prototype. We demonstrate that thanks to TALESS, legacy systems can synchronize through TSN and even improve features such as their reception jitter or their integrability with other legacy systems.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"807-822"},"PeriodicalIF":5.2,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10620612","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141880628","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}