| 1. |
- Aziz, Abdullah, 1992-
(författare)
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Virtualizing Operational Technology by Distributed Digital Twins
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Industrial digitalization, stemming from the convergence of Information Technology (IT) and Operational Technology (OT), is a transformative force in modern industries. The Industrial Internet of Things (IIoT) and Industrial Cyber-Physical Systems (ICPS) empower industries with enhanced production processes, data-driven insights, and advanced automation. Accompanying these trends, digital twins bridge the gap between the physical and digital realms, promising dynamic representations of entities. This convergence holds great promise for fostering efficient and agile industrial ecosystems.However, amidst the promise, a series of challenges loom large across a multitude of domains. These challenges span a multitude of domains. The convergence of IT and OT engenders a spectrum of complexities, including interoperability issues, data integration dilemmas, and the imperative need to tackle the historical hardware-centricity of industrial systems. This includes enhancing energy efficiency and security in the digital realm and addressing fundamental issues within the fabric of modern industries.The scope of our research addresses these multifaceted challenges by encompassing three overarching research questions. The first explores the integration of IIoT architectures and data integration models, striving to augment interoperability and data exchange for industries, offering practical benefits. The second delves into the realm of ICPS and industrial automation, investigating how Digital Twins can optimize energy efficiency, security, and service availability. The third widens the horizon by examining the potential of distributed digital twins as proxies to foster composability and adaptability, bridge the physical-virtual gap, and meet the evolving needs of industrial IoT and cyber-physical systems.Our thesis unfolds with five key contributions, each addressing fundamental challenges in industrial digitalization. First, we present a synthesized IIoT architecture tailored for the mining industry, aligning seamlessly with IoT and Industry 4.0 standards and frameworks. Second, we explore data integration through service-based and event-driven communication models across industries. We provide a qualitative analysis of these models to present guidelines for designing data integration solutions according to needs.In the third contribution, we focus on digital twins for Industrial Cyber-Physical Systems (ICPS) and introduce the concept of a digital twin as proxy. This concept enables the virtualization of tangible devices and assets from the OT domain to the IT domain. This contribution addresses energy efficiency, security, and service availability challenges. Building on this, our fourth contribution implements and integrates the concept of the digital twin as a proxy with the Eclipse Arrowhead Framework, extending its applicability to industrial automation and reinforcing our response to the second research question.Our fifth contribution further envisions the virtualization of the OT within IT. Grounded in service-oriented and microservice architectural principles, we propose the concept of purpose-oriented composable digital twins by utilizing distributed digital twins as proxies. This concept offers a forward-looking solution to address evolving needs. Together with the third and fourth contributions, our work ensures a comprehensive and forward-looking impact on the discourse of industrial digitalization.
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| 2. |
- Bicaku, Ani, DI, 1988-
(författare)
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Security Standard Compliance in System of Systems
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The world we live in is becoming digitalized by transforming our society and economyin an unpredicted way. Digital technologies are transforming products, manufacturingassets, and entire supply chains. These technologies revolutionize how organisations en-gage with customers, other partners, and society depending on the ability to connectpeople, technology, and processes. Distributed services through different platforms, or-ganisations, and even regions are becoming very common with the digital transformationof industrial processes. More and more systems are being constructed by interconnectingexisting and new independent systems. The transformation from traditional and isolatedsystems to connected components in a System of Systems (SoS), provides many advan-tages such as flexibility, efficiency, interoperability, and competitiveness. While it is clearthat digital technology will transform most industries, there are a number of challengesto be addressed, especially in terms of standards and security.In the past, providing a secure environment meant isolation from external access andproviding physical protection, usually based on proprietary standards. Nowadays, withthe development of state-of-the-art technologies, these systems have to meet and provideproof of fulfilling several requirements and involving many stakeholders. Thus, to assurethat organisations can move towards this multi-stakeholder cooperation, security is one ofthe challenges that need to be addressed. With the increasing number of devices, systems,and services in these complex systems and the number of standards and regulationsthey should fulfill, the need for automated standard compliance verification is of utmostimportance. Such verification will ensure that the components included in their businessprocesses comply with the imposed standards, laws and regulations.The research presented in this thesis targets the automated and continuous standardcompliance verification in SoS. Standard compliance verification provides evidence thatprocesses and their components satisfy the requirements defined by national and interna-tional standards. The thesis proposes an automated and continuous standard complianceverification framework that provides evidence if SoS components fulfill security standards’requirements based on extracted measurable indicator points. Since these systems evolveover time, the standard compliance is verified in design time and continuously monitoredand verified during run time after the SoS has been deployed.
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| 3. |
- Borngrund, Carl, 1992-
(författare)
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Towards Deep-learning-based Autonomous Navigation in the Short-loading Cycle
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Earth-moving machines, such as wheel loaders, are a type of heavy-duty machinery used within the construction industry to perform vital tasks, such as digging, transporting, and mining applications. One of these tasks is the short-loading cycle, where an operator manoeuvres the wheel loader to move material from a pile to the tipping body of a dump truck, through navigation, scooping, and dumping. The short-loading cycle is a repetitive task performed in high quantities, often as part of a larger refinement process, making it interesting for automation.The main objective of this thesis work is to investigate challenges facing the automation of the short-loading cycle, focusing in particular on subtasks that can be efficiently addressed with deep learning methods. A secondary objective is to examine how alternative development paths, such as scale models, or simulations, can be used to enable data-driven automation of the short-loading cycle, as directly experimenting on real vehicles has a high associated cost when large numbers of timesteps are needed to gather enough data.To investigate the two objectives, the literature is systematically reviewed to identify research gaps, challenges, and the usage of deep learning techniques. Secondly, a set of deep learning techniques is investigated to address perception and actuation problems identified as challenging and important for the automation of the short-loading cycle.The investigation of deep learning techniques involves training and validating a realtime object detector neural network to identify key components (wheels, tipping body, and cab) on a scale model dump truck while testing on a real vehicle. This resulted in a localisation and classification degradation of only 14% between the scale model and the real dump truck, with no additional training. In addition, an examination to minimize the annotation workload of humans found that it is possible to decrease the workload by 95% while still retaining similar detection performance by leveraging linear interpolation.Lastly, this thesis presents an investigation regarding the usage of reinforcement learning for navigation during the short-loading cycle. The results indicate that training the agent in simulation is currently required as the agent obtains the maximum reward after timesteps in the order of millions before being capable of performing the task. The results suggest that the trained agent is capable of bridging the gap between simulation and reality to complete a simplified version of the navigation task during the short-loading cycle.The experiments presented in this thesis provide proof of concept that indicates deep learning techniques can aid in the realisation of an autonomous solution. Moreover, the results show that development paths allowing for experiments providing large numbers of timesteps can facilitate the practical use of such techniques.
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| 4. |
- Carlsson, Oscar
(författare)
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Engineering of IoT Automation Systems
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Major societal challenges such as environmental sustainability, availability of energy and raw materials, and globalisation are creating new requirements for many actors in society. These new requirements relate to efficiency, flexibility, sustainability, and competitiveness. While these aspects have all been around for some time, and many systems have been locally optimised with regards to one or a few of these requirements, recent advances in communication and processing capabilities promise increased possibilities for connecting different parts of society, allowing optimal operation on a much larger scale.While industrial production systems have been controlled electronically for decades, the digitisation of market channels and consumer systems, together with the possibility to interconnect different production facilities, now allow for automated interaction along the whole supply chain from raw materials to end users.Simultaneously, increased demand for efficiency forces increased specialisation among actors, which with increased possibilities of interconnectivity, creates large enterprises of cooperating, specialised stakeholders.One of the major remaining obstacles for a widespread adaptation of more intelligent, more connected systems, able to deliver these envisioned results, is a coherent approach to the engineering and management of Systems-of-Systems involving very large numbers of devices and operating across several automation domains.For traditional automation systems there are established engineering procedures and numerous standards for engineering data, although most are focused on the static processes that have traditionally been the norm. For full integration with a digital society many of the existing automation systems will need significant modifications and as many automation systems are ageing and in need of replacement, a suitable solution to this may be a large scale migration to new automation solutions.The work presented in this thesis includes some new approaches and methodologies to utilise the existing engineering procedures and standards, while introducing some of the flexibility proposed by the emerging technologies. The major technical solutions presented consist of a structure way to organise connected systems and how they are related, regardless of engineering standards used to design their interactions, and an approach to allow configuration of heterogeneous systems through service interactions.Further contributions include an approach for migrating certain categories of existing industrial control systems to a service oriented architecture, as a basic outline for adaption of the next generation of automation systems in industry.Certain remaining challenges have been identified, which have to be addressed for a successful launch of widespread interconnected automation systems based on Internet of Things and associated technologies.
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| 5. |
- Chiquito, Alex, 1994-
(författare)
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Attribute-based Approaches for Secure Data Sharing in the Industry
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In the Industry 4.0 era, secure and efficient data sharing is vital for innovation and operational enhancement. Industry 4.0 envisions a highly connected ecosystem where machines, devices, and stakeholders collaborate in real time to optimize processes, enhance productivity, and create new value propositions. However, this surge in data-driven collaboration brings forth a critical challenge, ensuring the secure and controlled sharing of sensitive information. As organizations embrace the potential of Industry 4.0, the need for robust mechanisms to achieve key data security properties of data integrity, confidentiality, and availability, while enabling efficient data exchange becomes paramount. However, while the promise of Industry 4.0 presents promising opportunities, it also introduces a set of challenges intrinsic to data security solutions. These solutions, while promising in providing fine-grained data security, introduce complexities such as administrative overhead and substantial management efforts for the users. Striking a balance between robust security and operational ease is critical for enabling seamless data exchange within the evolving landscape of Industry 4.0.This thesis explores the realm of Attribute-based approaches to achieve the desired secure data sharing, pivotal in the digitized Industry 4.0 environment. An overarching objective is to achieve compatibility of these data-securing mechanisms with the Industry 4.0 paradigms through the usage of attribute-based approaches. This includes the exploration of the existing solutions within the state-of-the-art and its analysis in the context of usability and practicality for industrial adoption. Access control entails the establishment of policies and mechanisms to regulate who can access specific resources or information, under what conditions, and to what extent. The study will delve into various access control models and their applicability, with a particular emphasis on Attribute-Based Access Control. Moreover, through the creation of proofs-of-concepts implementations, we explore the usability of Attribute-based Access Control (ABAC) models and policy languages, applied to different aspects of the data-sharing process. Manageability, user-friendliness, and fine-granularity of the access control were identified as key properties for the usability of data securing technologies in industry. Hence, discovering and addressing challenges for such properties is of special focus for this thesis. In addition, this thesis explores attribute-based encryption techniques, seeking to augment data security while minimizing additional operational complexities. Moreover, this thesis also explores the implications of third-party cloud services, popular in Industry 4.0 environments, as well as third-party stakeholder data sharing to motivate the need to ensure both in-transit and at-rest data security.This thesis makes significant contributions in the domain of secure data sharing in Industry 4.0. First, it contextualizes access control within the broader data security landscape and explores state-of-the-art Attribute-Based Access Control policy languages. The research designs, evaluates, and automates ABAC models to address fine-granularity and manageability gaps, with a focus on user-friendliness for industrial adoption. Furthermore, it proposes and implements an automated management solution for integrating new data sources in Service-Oriented Architecture (SOA) industrial data-sharing applications, within the Eclipse Arrowhead Framework. This includes the innovative proposal of contractual automation of access control policies to enhance efficiency and security. Moreover, the research delves into the realm of attribute-based encryption approaches, conducting a state-of-the-art exploration and gap analysis, with a special focus on uncovering the adoption barriers associated with this technology. Lastly, the thesis designs, implements, and evaluates an ABAC-Enabled ABE solution architecture, covering the discovered gaps, and offering an expressive and user-friendly approach to secure data sharing. These contributions collectively advance the field of data security and access control in the context of Industry 4.0 and similar evolving industrial landscapesThe research indicated that Attribute-based approaches hold promise for practical data protection at rest through access control mechanisms, especially within fine-grained policies. The study explores ABAC in a graph-based policy language, Next-generation Access Control (NGAC), showcasing its potential for reducing administrative workload related to policy management. Simplified policy creation and expression enhance the ease of model implementation. These insights extend to ABE, highlighting the value of delegating attribute management for reduced administrative complexity and improved expressiveness within ABE schemes. This approach allows for automation techniques developed for ABAC policy management to be translated into ABE schemes.
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| 6. |
- Chiquito, Eric
(författare)
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Decentralized Negotiations and Data Storage for the Circular Economy
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The shift from traditional modes of operation characterized by manual or analog processes to digitalization represents a fundamental transformation in the way business manage their processes and interact with their customers. Digitalization brings refinement of existing workflows, improved efficiency, enhanced customer experience, and better collaboration within ecosystems. This benefits circularity and reusability, reduces the environmental impact and helps streamlining the supply chain process.The collaboration between diverse organizations with varying data requirements highlights the importance of both political and architectural decentralization as interacting parties may be cautious about sharing sensitive data or entrusting a third party with its processing. Political decentralization eliminates the need for a governing authority to establish trust among collaborating organizations. Architectural decentralization distributes data storage across various actors and defines and enforces access rights and ownership while simultaneously improving security by eliminating a single point of failure. Lately, blockchain systems using Smart Contracts have emerged as a popular approach for achieving decentralization. However, while these implementations offer decentralization, they may not always be the most efficient solution for decentralized systems.This doctoral thesis delves into the digitalization of existing systems, with a focus on decentralized negotiation mechanisms, data storage, and circularity. The work investigates how decentralized systems can effectively represent highly interconnected data to facilitate bidirectional traversal of relationships and proposes a proof-of-concept (PoC) implementation using Interplanetary File System. This work is extended to the realm of sustainability by examining digital product passports, showcasing their role in ensuring traceability and accountability throughout product lifecycles. An analysis of the state-of-the-art blockchain approaches for transitioning electronic auctions toward decentralized systems is presented. Based on this, a system design for a decentralized auction system based on blockchain and a PoC implementation using Hyperledger Fabric are proposed. Finally, the digitalization of agreements for the automatic representation of rights and obligations in price-only and multi-attribute electronic auctions and data sharing is analyzed.The main contributions of this thesis are (1) The use of state-of-the-art decentralized technologies for the bidirectional traceability of highly interconnected data in the context of sustainability. 2) The analysis and implementation of decentralized open-cry auction systems using blockchain technologies. (3) The use of Ricardian contracts for the representation of rights and obligations in electronic auctions and data sharing.
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| 7. |
- Dadhich, Siddharth, 1987-
(författare)
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Automation of Wheel-Loaders
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Automation and tele-remote operation of mobile earth moving machines is desired for safety and productivity reasons. With tele-operation and automation, operators can avoid harsh ergonomic conditions and hazardous environments with poor air quality, and the productivity can in principle be improved by saving the time required to commute to and from work areas. Tele-remote operation of a wheel-loader is investigated and compared with manual operation, and it is found that the constrained perception of the machine is a challenging problem with remote operations. Real-time video transmission over wireless is difficult, but presents a way towards improving the remote operator’s quality of experience. To avoid glitches in the real-time video, arising from variable wireless conditions, the use of SCReAM (Self-Clocked Rate Adaptation for Multimedia) protocol is proposed. Experiments with a small scale robot over LTE show the usefulness of SCReAM for time-critical remote control applications. Automation of the bucket-filling step in the loading cycle of a wheel-loader has been an open problem, despite three decades of research. To address the bucket-filling problem, imitation learning has been applied using expert operator data, experiments are performed with a 20-tonne Volvo L180H wheel-loader and an automatic bucket-filling solution is proposed, developed and demonstrated in field-tests. The conducted experiments are in the realm of small data (100 bucket-filling examples), shallow time-delayed neural-network (TDNN), and a wheel-loader interacting with a non-stationary pile-environment. The total delay length of the TDNN model is found to be an important hyperparameter, and the trained and tuned model comes close to the performance of an expert operator with slightly longer bucket-filling time. The proposed imitation learning trained on medium coarse gravel succeeds in filling buckets in a gravel cobble pile. However, a general solution for automatic bucket-filling needs to be adaptive to possible changes in operating conditions. To adapt an initial imitation model for unseen operating conditions, a reinforcement learning approach is proposed and evaluated. A deterministic actor-critic algorithm is used to update actor (control policy) and critic (policy evaluation) networks. The experiments show that by use of a carefully chosen reward signal the models learns to improve and maximizes bucket weights in a gravel-cobble pile with only 40 bucket-filling trials. This shows that an imitation learning based bucket-filling solution equipped with a reinforcement learning agent is well suited for the continually changing operating conditions found in the construction industry. The results presented in this thesis are a demonstration of the use of artificial intelligence and machine learning methods for the operation of construction equipment. Wheel-loader OEMs can use these results to develop an autonomous bucket-filling function that can be used in manual, tele-remote or fully autonomous operations.
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| 8. |
- Derhamy, Hasan
(författare)
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Architectural Design Principles For Industrial Internet of Things
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- As society has progressed through periods of evolution and revolution, technology hasplayed a key role as an enabler. In the same manner that mechanical machines of the1800’s drove the industrial revolution, now digitalized machines are driving another one.With this recognition of a fourth industrial revolution, the Industry 4.0 initiative wasfounded. One of the drivers of Industry 4.0 is the Industrial Internet of Things (IIoT).The IIoT is a consequence of widely present computing ubiquity and interconnected-ness. Software has become a crucial tool of almost all industries from bakeries and arts to manufacturing facilities and banking. Programming is now a required competenceand used by a variety of professions. It is not only about algorithm development, it has become more about engineering and integrating existing designs and tools. This impacts the way software is architected and drives a large body of research in the area.Software solutions are becoming more distributed, not only over multiple processes, but over heterogeneous hardware and business domains. Computing platforms could bemobile or geographically separated over large distances, exposing the solutions to network disturbances, performance degradation and security vulnerabilities.Hence, IIoT introduces complexity on a scale previously unseen in the software in-dustry. Software architecture must accommodate these heterogeneous domains and com-petencies and handle the increasing levels of complexity.This thesis proposes an architectural style for designing IIoT software architectures.The popular Service Oriented Architecture (SOA) style is not sufficient to define a com-plete architecture for IIoT applications. SOA fundamental principles are defined as loose coupling, lookup and late binding. The proposed architecture style extends these SOA principles with autonomy, specialization, data at its source and first person perspective. It preserves the benefits of SOA that models functionalities as reusable services with standardized interfaces. Thus, the proposed style helps to capture the heterogeneity of IIoT (e.g. systems, capabilities, domains, competencies etc.), while handling challenges imposed by it. The style also captures resource constraints of IIoT platforms; distri-bution of application logic across IIoT; dependence between services within IIoT; and presentation of the solution in various stakeholder perspectives.The IIoT generates large amounts of data that is subsequently stored, analysed, archived and eventually fed back into the product life cycle. Centralization of data has well known challenges. This thesis proposes a method of information extraction based on the principle of data at its source. Such data preserves implicit context, reducing the burden of semantic data within the system. Desired information is expressed through dynamic (runtime) queries. Using the queries, a path is created to retrieve the requested data. It alleviates the need for data to be stored in intermediary nodes; data remains atthe source. Thus, IIoT applications extract information and present it to requesting sys-tems without redundant source related context. This helps with issues of data ownership, access control and stale data.Another IIoT challenge tackled in this work is decentralization of Manufacturing Execution System (MES). It is motivated by a need to mitigate the impact of vulnerable shared networks on the factory floor; and by business requirements to reduce dependence on local factory infrastructure. This thesis explores a solution where functions of MES are distributed to the workstations that enables them to operate autonomously. Such autonomous workstations utilize the proposed Intelligent Product, Workflow Managerand Workflow Executor systems. Thus, MES can be decentralized to edge nodes as envisioned by Industry 4.0.
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| 9. |
- Hartman, Andreas
(författare)
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Electromagnetic Modeling with Complex Dielectrics : A Partial Element Equivalent Circuit Approach
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Wireless communication systems have become an integral part of many complex systems in diverse areas of society, for the exchange of data in business and industrial settings. With the advent of Internet of Things (IoT) and wireless sensor network architectures, the tighter demands on interoperability between different devices are putting heavy requirements their ability to exchange data wirelessly among them reliably. However, many environments pose a challenging setting for a wireless communication system to operate within. Consequently, electromagnetic modeling could be used as a crucial part of the analysis and design of a wireless communication system in these environments.In this thesis, means for the electromagnetic modeling of complex materials are considered. Specifically, the incorporation of dielectrics that exhibit loss, dispersion, and anisotropic properties into electromagnetic codes is addressed. The work has been executed within the partial element equivalent circuit (PEEC) method framework.First, a PEEC implementation that incorporates dispersive and lossy dielectrics, represented by equivalent circuit models explicitly included in the PEEC equations, is developed. This provides a descriptor system form of the PEEC model that includes dielectrics with permittivities that can be represented as finite sums of Debye and Lorentz permittivity models and can be integrated by any time integration scheme of choice. Additionally, the description admits the application of model-order reduction techniques, reducing the model complexity of a large-scale PEEC model that consists of frequency-dispersive dielectrics.Next, the incorporation of anisotropic dielectrics in PEEC simulations is considered. A PEEC cell for anisotropic dielectrics, with a general permittivity tensor, is derived. It turns out to be an extension of the standard dielectric PEEC cell for an isotropic dielectric by adding a voltage-dependent current source in parallel with the excess capacitance of the dielectric cell. A cross-coupling excess capacitance concept that defines the dependent current source for the anisotropic PEEC cell is defined and given for orthogonal PEEC meshes. As a result, the PEEC cell for an anisotropic dielectric is possible to extend to handle lossy and dispersive anisotropic dielectrics straightforwardly. The developed PEEC model has been applied to model a patch antenna mounted on an anisotropic substrate. The simulation results are in agreement with other simulation technique results. Consequently, the anisotropic model permits electromagnetic modeling of structures and devices that consist of a broader class of materials.The modeling of dielectrics in different ambient temperature conditions is also considered for the PEEC analysis of its impact on antennas. Dielectrics with temperature dependent permittivity have been modeled with PEEC by standard approaches found in the literature. This has proved useful for frequency-domain simulations in PEEC. The utility has been demonstrated by investigating the impact due to temperature-dependent dielectrics on printed antennas. These types of investigations could provide valuable in-formation in the design of printed antennas in harsh environments.Finally, the problem of designing magneto-dielectric materials that intrinsically provide distortionless propagation for TEM mode signals is investigated. The frequency dependent permittivity and permeability of a slab are related to the per-unit length (p.u.l.) parameters of a two-conductor transmission line. The p.u.l. parameters are specified to approximate the Heaviside condition in a specified and finite frequency interval, while simultaneously enforcing that the corresponding permittivity and permeability represent a passive material. Consequently, the passivity condition ensures the designed material is possible to realize in practice while the Heaviside condition secures that the material is distortionless. The design method has been employed to design a passive material that approximates the Heaviside condition in a narrow frequency interval. Verification in both time and frequency domains indicates that the designed material closely resembles a distortionless material in the specified frequency interval. These results indicate that an approximation of the Heaviside condition could be a potential aid in the design of distortionless materials for bandlimited applications. Further investigations on design method improvements, limitations on the approximation in terms of both accuracy and bandwidth, and the construction of such materials in practice could lead to new distortionless cable or material designs.
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| 10. |
- Häggström, Fredrik, 1984-
(författare)
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Robust energy management for IoT machine elements
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Advancements in semiconductor technology have reached the point at which ambient energy in the surrounding environment can power sensors and microprocessors. This capability enables new strategies for energy management, which are necessary to continue the sensorization of our environment. With the vast amount of interconnected devices and the rate at which the number of such devices is increasing, there is a need to power resource-constrained devices through means other than disposable batteries. Harvesting ambient energy from the surroundings of the device is one solution to this challenge. It has been estimated that the global demand for bearings will reach 104.5 billion dollars in 2018 with an annual increase of 7.3%. Bearings are mechanical parts that are essential for rotating machinery and that have the potential to measure and monitor vital parts of a machine. A scenario in which bearings contain embedded electronics to monitor process and health parameters that can be analyzed on site and collected from remote locations is a crucial motivator for this thesis. The investigated technologies should be applicable in dirty and encapsulated industrial environments; therefore, vibrational and rotational kinetic energies are considered in this thesis. For each energy source, both the physics and the associated electronics are modeled and to some extent experimentally verified. Vibration harvesters are investigated and modeled in SPICE to verify performance gains using a novel circuit for nonlinear power extraction for piezoelectric materials. The simulations revealed that a weak coupling from the electrical system to the mechanical system would greatly benefit nonlinear extraction techniques. Such a weakly coupled system can be created in a bearing. Mechanical load and rotation generate cyclic strain in the bearing's raceway; the cyclic strain can be utilized by applying piezoelectric patches to the raceway to power embedded systems, and sensory information from the piezoelectric patch can also be used to monitor the bearing. Finally, trends and limits for the energy costs of computing, communication and data acquisition are investigated to determine suitable energy storage technologies to combine with the advancements in energy harvesting for machine elements such as rolling element bearings. The results indicate that high integration between the mechanical and electrical parts is desired, which, in combination with capacitive energy storage, appears to be the long-term direction for real-world implementations.
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