Digital Twins for Condition and Fleet Monitoring of Aircraft: Toward More-Intelligent Electrified Aviation Systems

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 99806 - 99832

Published: Jan. 1, 2024

The convergence of Information Technology (IT), Operational (OT), and Educational (ET) has led to the emergence fourth industrial revolution. As a result, new concept emerged known as Digital Twins (DT), which is defined "a virtual representation various objects or systems that receive data from physical objects/systems make changes corrections". In aviation industry, numerous attempts have been made utilize DT in design, manufacturing, condition monitoring aircraft fleets. Among these research efforts, real-time, accurate, fast, predictive methods play crucial role ensuring safe efficient performance aircraft. Using for fleet not only enhances reliability safety but also reduces operational maintenance costs. this paper, conducted studies on applications units aerospace sector are discussed reviewed. aim review paper analyse current developments industry well explain remaining challenges systems. Then Finally, future trends along with presented. reviewed papers, most them used computational fluid dynamics, finite element methods, artificial intelligence techniques developing models At same time, analyses dedicated failure crack detection body engine fault detection. Life prediction another popular application using could help engineers predict required different parts marine, power systems, space programs lessons learned translated sector.

Language: Английский

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AI-Enabled Cognitive Predictive Maintenance of Urban Assets Using City Information Modeling—Systematic Review

Buildings, Journal Year: 2025, Volume and Issue: 15(5), P. 690 - 690

Published: Feb. 22, 2025

Predictive maintenance of built assets often relies on scheduled routine practices that are disconnected from real-time stress assessment, degradation and defects. However, while Digital Twin (DT) technology within building urban studies is maturing rapidly, its use in predictive limited. Traditional preventive reactive strategies more prevalent facility management not intuitive, resource efficient, cannot prevent failure either underserve the asset or surplus to requirements. City Information Modeling (CIM) refers a federation BIM models accordance with real-world geospatial references, it can be deployed as an Urban (UDT) at city level, like BIM’s deployment level. This study presents systematic review 105 Scopus-indexed papers establish current trends, gaps opportunities for cognitive framework architecture, engineering, construction operations (AECO) industry. A UDT consisting CIM section University Florida campus proposed bridge knowledge gap highlighted review. The illustrates potential CNN-IoT integration improve through advance notifications. It also eliminates centralized information archiving.

Language: Английский

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A collaborative network of digital twins for anomaly detection applications of complex systems. Snitch Digital Twin concept

Computers in Industry, Journal Year: 2022, Volume and Issue: 144, P. 103767 - 103767

Published: Sept. 13, 2022

This paper proposes a novel anomaly detection methodology for industrial systems based on Digital Twin (DT) ecosystems. In addition to DTs, conceived as digital representation of physical entity, this new concept DT focused modeling connections between behaviors. is called Snitch (SDT). The scope the SDT study variations behaviors and support anomalies them. behavior each entity characterized by three spatiotemporal features computed from collected measurement. Behavioral are identified quantified through modular patterns quantile regression behavioral indexes. Finally, robustness proposed assessed comparing it with other two commonly used algorithms Kernel Principal Component Analysis (KPCA) One-Class Support Vector Machines (OCSVM) in case application. diagnosis cooling system power-generator diesel engine. results obtained prove advantages goodness compared traditional algorithms.

Language: Английский

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Digital twin simulation for integration of blockchain and internet of things for optimal smart management of PV-based connected microgrids

Solar Energy, Journal Year: 2023, Volume and Issue: 251, P. 306 - 314

Published: Jan. 23, 2023

Language: Английский

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Designing High-Power-Density Electric Motors for Electric Vehicles with Advanced Magnetic Materials

World Electric Vehicle Journal, Journal Year: 2023, Volume and Issue: 14(4), P. 114 - 114

Published: April 18, 2023

As we face issues of fossil fuel depletion and environmental pollution, it is becoming increasingly important to transition towards clean renewable energies electric vehicles (EVs). However, designing motors with high power density for EVs can be challenging due space weight constraints, as well related loss temperature rise. In order overcome these challenges, a significant amount research has been conducted on high-power-density advanced materials, improved physical mathematical modeling materials the motor system, system-level multidisciplinary optimization entire drive system. These technologies aim achieve reliability optimal performance at system level. This paper provides an overview key performance, focus magnetic proper core losses under two-dimensional or three-dimensional vectorial magnetizations. will also discuss major challenges associated possible future directions in field.

Language: Английский

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Energy efficiency model-based Digital shadow for Induction motors: Towards the implementation of a Digital Twin

Engineering Science and Technology an International Journal, Journal Year: 2023, Volume and Issue: 44, P. 101469 - 101469

Published: June 25, 2023

The 4th industrial revolution requires the tracking and optimization of energy consumption using an intelligent management system (IEMS). Such a needs accurate real-time information to operate machines, where Induction Motors (IMs) represent 42.2% global consumption. This paper addresses problems data acquisition for motors in context Industry 4.0 (I4.0) precision, constraints, optimal operations play major role decision-making. A new vision Digital Shadow (DS) is proposed efficiency (EE) IMs. hybrid model consisting data-driven physics-based developed machine (RT). method based on two-stage procedure. Firstly, IM EE established by considering Stator joule losses, core rotor friction, windage addition stray losses create improved model. was double cage loss resistance added. Secondly, machine's are visualized 8 electrical circuit parameters (ECP) from rated speed test temperature. estimation RT incurred complexities required use Adaptive Neuro-Fuzzy Inference System (ANFIS)-based modeling. Fuzzy Logic Toolbox Designer app MATLAB training Sugeno systems. ANFIS models trained estimate each ECP standard inputs. testing dataset constituted experimental ECPs were calculated FSOLVE function solve nonlinear formed 60 manufacturers' such as voltage, number pole-pairs, output power, torque, current, starting maximum torque power factor. Finally, validated experimentally 1.5 KW, 400/230 V, 50 Hz squirrel induction motor (SCIM) linear control. EE, Torque, through MATLAB/SIMULINK. mean value RMSE eight estimated 7.57e-05, 5.73e-01 respectively while values MAE 2.06e-05, 3.79e-01 testing. errors w.r.t measured at condition, = 0.205, 0.1671. These results show that can be implemented industry monitor its losses.

Language: Английский

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Digital Twin Models: Functions, Challenges, and Industry Applications

IEEE Journal of Radio Frequency Identification, Journal Year: 2024, Volume and Issue: 8, P. 282 - 321

Published: Jan. 1, 2024

In the rapidly evolving landscape of Industry 4.0, digital twins have emerged as a transformative technology across various industrial sectors. This paper presents comprehensive, in-depth review twin models in terms concept and evolution, fundamental components frameworks, existing based on their functionalities. The also discusses how are used/adopted different industries highlights challenges potential solutions to address current issues. aims provide researchers industry professionals with clear insight into unique benefits applications models. will help comprehend significance for specific purposes foster advancement state-of-the-art techniques this field.

Language: Английский

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State-of-the-art review and synthesis: A requirement-based roadmap for standardized predictive maintenance automation using digital twin technologies

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 62, P. 102800 - 102800

Published: Sept. 10, 2024

Language: Английский

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Systematic review of predictive maintenance and digital twin technologies challenges, opportunities, and best practices

PeerJ Computer Science, Journal Year: 2024, Volume and Issue: 10, P. e1943 - e1943

Published: April 22, 2024

Background Maintaining machines effectively continues to be a challenge for industrial organisations, which frequently employ reactive or premeditated methods. Recent research has begun shift its attention towards the application of Predictive Maintenance (PdM) and Digital Twins (DT) principles in order improve maintenance processes. PdM technologies have capacity significantly profitability, safety, sustainability various industries. Significantly, precise equipment estimation, enabled by robust supervised learning techniques, is critical efficacy conjunction with DT development. This study underscores DT, exploring transformative potential across domains demanding real-time monitoring. Specifically, it delves into emerging fields healthcare, utilities (smart water management), agriculture farm), aligning latest frontiers these areas. Methodology Employing Preferred Reporting Items Systematic Review Meta-Analyses (PRISMA) criteria, this highlights diverse modeling techniques shaping asset lifetime evaluation within context from 34 scholarly articles. Results The revealed four important findings: modelling their approaches, predictive outcomes, implementation management. These findings align ongoing exploration applications farm). In addition, sheds light on functions emphasising extraordinary ability drive revolutionary change dynamic challenges. results highlight methodologies’ flexibility many industries, providing vital insights revolutionise management practice Conclusions Therefore, systematic review provides current essential resource academics, practitioners, policymakers refine strategies expand applicability sectors.

Language: Английский

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Predictive digital twin technologies for achieving net zero carbon emissions: a critical review and future research agenda

Smart and Sustainable Built Environment, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 2, 2024

Purpose Predictive digital twin technology, which amalgamates twins (DT), the internet of Things (IoT) and artificial intelligence (AI) for data collection, simulation predictive purposes, has demonstrated its effectiveness across a wide array industries. Nonetheless, there is conspicuous lack comprehensive research in built environment domain. This study endeavours to fill this void by exploring analysing capabilities individual technologies better understand develop successful integration use cases. Design/methodology/approach uses mixed literature review approach, involves using bibliometric techniques as well thematic critical assessments 137 relevant academic papers. Three separate lists were created Scopus database, covering AI IoT, DT, since IoT are crucial creating DT. Clear criteria applied create three lists, including limiting results only Q1 journals English publications from 2019 2023, order include most recent highest quality publications. The collected was analysed package R Studio. Findings reveal asymmetric attention various components twin’s system. There relatively greater body on representing 43 47%, respectively. In contrast, direct net-zero solutions constitutes 10%. Similarly, findings underscore necessity integrating these carbon emission prediction. Practical implications indicate that clear need more case studies investigating large-scale networks collect buildings construction sites. Furthermore, development advanced precise models imperative predicting production renewable energy sources demand housing. Originality/value paper makes significant contribution field providing strong theoretical foundation. It also serves catalyst future within For practitioners policymakers, offers reliable point reference.

Language: Английский

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