Development of methods, algorithms and software for optimal design of switched reluctance drives

The aim of this thesis is to estimate the perspectives of integrated switched reluctance drives (I-SRDs), i.e. reluctance machines integrated with converters. It is assumed that such drive series can be manufactured in the power range of 0.75...7.5 kW and speed ranges of 300...3000 rpm and 600...6000 rpm for applications like pumps, fans, conveyors, compressors, extruders and mixers. Based on the performed research and design work it is stated that the new drives have to be developed according to their applications, which determine objective functions and constraints, and that the best possible design should be found as a solution of a synthesis task. Sizing equations are not applied at all. The approach used in the thesis is based on the virtual prototyping concept, i.e. the new I-SRD series is designed in a virtual environment. Therefore, mathematical models and the ways to verify them have to be elaborated. The concepts of multidisciplinary and multilevel modeling are applied. The multidisciplinary model is a combination of interconnected electromagnetic, thermal and noise models. The multilevel concept is the approach when different elements of the drive are described using different languages, i.e. on different levels. Several original solutions are introduced, like the electromagnetic model comprising SIMULINK block-diagrams and MATLAB script, expressions for the correction of the flux linkage due to end-effects, an original equivalent circuit for thermal analysis, which allows using a very simple and fast method to solve the circuit, together with the concept of a multi-layer equivalent cylinder for modeling the motor winding. For verification of the multidisciplinary model a database of test results has been collected using both testing of several reluctance machines in the laboratory and analyzing of test results published by other researchers. After verification the model can be considered as a virtual prototype and can be used in the synthesis process. Several methods of solving the synthesis task were tested. The method, proved to be best suited for solving this task in the proposed form, is the genetic algorithm in the vector form with alphabetic encoding. The genetic algorithm should be coupled with the experimental design method or with the Monte-Carlo method

Performance Modelling, and Adaptive Control for Linked Sequential Systems

This thesis investigates the dynamics of linked sequential systems of machines in industrial laundries. Two aspects are considered: firstly the control of such systems and in particular the decision making point when a batch to be processed can be sent to one of many identical machines, and secondly the modelling of the whole system of linked machines. The decision making point in the control of these systems is frequently implemented in a sub-optimal manner, or a manner which becomes sub-optimal as conditions change. An adaptive system is preferable and an Evolutionary Artificial Neural Network approach (EANN) is proposed. The EANN is tested on simulations of real laundry systems and shown to be effective. Then it is applied to two abstract game playing problems in order to better understand its limitations. Limitations are found to include the fact that if learning does not appear to take place, it is not possible to determine if this is a failure of the Evolutionary approach or the Artificial Neural Network parameters. The dynamics and performance of Linked Sequential Systems in Industrial Laundries are not well understood or covered by theory in the literature. The theory of the performance of these systems is outlined, and an Agent Based Model (ABM) simulation presented. The ABM simulation is explained and then the simulation is compared to a real world system in an existing laundry. The performance of the existing system is measured and compared to the prediction of the ABM simulation. The ABM simulation is shown to offer a better understanding of the system than the previous static calculation. Finally the ABM is used in a design exercise to show how it could be used to specify a system more accurately than the static calculation at design stage

Европейский и национальный контексты в научных исследованиях - 2021 : Технология

В настоящем электронном сборнике «Европейский и национальный контексты в научных исследованиях. Технология» представлены работы молодых ученых по геодезии и картографии, химической технологии и машиностроению, информационным технологиям, строительству и радиотехнике. Предназначены для работников образования, науки и производства. Будут полезны студентам, магистрантам и аспирантам университетов.=In this Electronic collected materials “European and national dimension in research. Technology” works in the fields of geodesy, chemical technology, mechanical engineering, information technology, civil engineering, and radio-engineering are presented. It is intended for trainers, researchers and professionals. It can be useful for university graduate and post-graduate students

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective

The selection and evaluation of a sensory technology for interaction in a warehouse environment

In recent years, Human-Computer Interaction (HCI) has become a significant part of modern life as it has improved human performance in the completion of daily tasks in using computerised systems. The increase in the variety of bio-sensing and wearable technologies on the market has propelled designers towards designing more efficient, effective and fully natural User-Interfaces (UI), such as the Brain-Computer Interface (BCI) and the Muscle-Computer Interface (MCI). BCI and MCI have been used for various purposes, such as controlling wheelchairs, piloting drones, providing alphanumeric inputs into a system and improving sports performance. Various challenges are experienced by workers in a warehouse environment. Because they often have to carry objects (referred to as hands-full) it is difficult to interact with traditional devices. Noise undeniably exists in some industrial environments and it is known as a major factor that causes communication problems. This has reduced the popularity of using verbal interfaces with computer applications, such as Warehouse Management Systems. Another factor that effects the performance of workers are action slips caused by a lack of concentration during, for example, routine picking activities. This can have a negative impact on job performance and allow a worker to incorrectly execute a task in a warehouse environment. This research project investigated the current challenges workers experience in a warehouse environment and the technologies utilised in this environment. The latest automation and identification systems and technologies are identified and discussed, specifically the technologies which have addressed known problems. Sensory technologies were identified that enable interaction between a human and a computerised warehouse environment. Biological and natural behaviours of humans which are applicable in the interaction with a computerised environment were described and discussed. The interactive behaviours included the visionary, auditory, speech production and physiological movement where other natural human behaviours such paying attention, action slips and the action of counting items were investigated. A number of modern sensory technologies, devices and techniques for HCI were identified with the aim of selecting and evaluating an appropriate sensory technology for MCI. iii MCI technologies enable a computer system to recognise hand and other gestures of a user, creating means of direct interaction between a user and a computer as they are able to detect specific features extracted from a specific biological or physiological activity. Thereafter, Machine Learning (ML) is applied in order to train a computer system to detect these features and convert them to a computer interface. An application of biomedical signals (bio-signals) in HCI using a MYO Armband for MCI is presented. An MCI prototype (MCIp) was developed and implemented to allow a user to provide input to an HCI, in a hands-free and hands-full situation. The MCIp was designed and developed to recognise the hand-finger gestures of a person when both hands are free or when holding an object, such a cardboard box. The MCIp applies an Artificial Neural Network (ANN) to classify features extracted from the surface Electromyography signals acquired by the MYO Armband around the forearm muscle. The MCIp provided the results of data classification for gesture recognition to an accuracy level of 34.87% with a hands-free situation. This was done by employing the ANN. The MCIp, furthermore, enabled users to provide numeric inputs to the MCIp system hands-full with an accuracy of 59.7% after a training session for each gesture of only 10 seconds. The results were obtained using eight participants. Similar experimentation with the MYO Armband has not been found to be reported in any literature at submission of this document. Based on this novel experimentation, the main contribution of this research study is a suggestion that the application of a MYO Armband, as a commercially available muscle-sensing device on the market, has the potential as an MCI to recognise the finger gestures hands-free and hands-full. An accurate MCI can increase the efficiency and effectiveness of an HCI tool when it is applied to different applications in a warehouse where noise and hands-full activities pose a challenge. Future work to improve its accuracy is proposed

OPTIMIZATION OF THE CLEANING SYSTEM OF GRAPE HARVESTERS USING THE DISCRETE-ELEMENT METHOD

Grape harvesters are mechanized machines designed to remove grapes from vine trees, process them in a cleaning system, and then store them in onboard bins. These bins are later unloaded into a transport wagon and taken to a vinification facility. Cleaning systems can sometimes fail to completely remove the foreign materials (i.e. leaves, petioles, stems, etc.), which may compromise the vinification process. For this reason, the project focused on the cleaning system by minimizing the presence of foreign materials while maintaining an adequate harvesting throughput. The project main objective was to optimize the cleaning system in grape harvesters by using the Discrete-Element Method (DEM). Individual DEM simulations were validated and used to develop a main crop flow simulation for the optimization of the cleaning system. This optimization included reducing the presence of foreign materials (petioles and leaves) while increasing the crop throughput for the specific grape variety of Cabernet Sauvignon. The physical characteristics and properties of the biological materials (grapes, petioles, leaves) were measured during the 2014 grape harvesting season at three different locations (Aigues-Mortes, Saint-Gervais, and Pauillac) in France. Time constraints limited the number of measured properties at the locations. The results from each location were compared using an ANOVA and a Tukey HSD post-hoc test. Given the natural variability of the biological materials, the three populations were found to be significantly different in most cases. The physical characteristics and properties from the Aigues-Mortes and Pauillac locations were used for the validation process. This was done because these locations had the most complete data sets. During the summer of 2015, a second testing phase took place to validate both the DEM leaf deflection and cleaning system models. The additional experiments consisted of testing the leaf samples in controlled deflections and testing the efficiency of the cleaning system. These experiments used Cabernet Sauvignon leaves shipped from the Vineland Research and Innovation Centre (VRIC) in Ontario. The individual simulations included the inclined plane, rebound surface, leaf deflection, and grape trajectory tests on an inclined conveyor. The inclined plane and rebound simulations were adjusted until the results were within 5% of the experimental test results. The leaf deflection simulations used optimized crop material properties until the simulated leaf behavior matched the actual leaf. Some discrepancies in the DEM simulated leaf shape were identified due to the limitations of the particle creation method. The grape trajectory test results coincided with the DEM simulations at greater conveyor speeds. A moderate difference between the simulations and the experimental tests was present at lower conveyor speeds. A possible cause for this difference may have been the effect of gravity and belt friction on the generation and acceleration of the grapes on the conveyor. A main crop flow simulation that included a conveyor and aspirator was developed using the previously validated simulations. Nine conveyor configurations, which included three belt angles from horizontal (10°, 15°, and 20°) and three speeds (350 rev/min (1.4 m/s), 420 rev/min (1.7 m/s), and 500 rev/min (2.0 m/s)), were tested to optimize the cleaning system performance. Based on the DEM simulations, the 420 rev/min-20° configuration was recommended as the optimal crop conveyor setting. This particular configuration minimized product damage and had an increased aspiration success rate of 9.6% compared to the conventional conveyor settings (420 rev/min-15°)

Software framework for the development of context-aware reconfigurable systems

In this project we propose a new software framework for the development of context-aware and secure controlling software of distributed reconfigurable systems. Context-awareness is a key feature allowing the adaptation of systems behaviour according to the changing environment. We introduce a new definition of the term “context” for reconfigurable systems then we define a new context modelling and reasoning approach. Afterwards, we define a meta-model of context-aware reconfigurable applications that paves the way to the proposed framework. The proposed framework has a three-layer architecture: reconfiguration, context control, and services layer, where each layer has its well-defined role. We define also a new secure conversation protocol between distributed trustless parts based on the blockchain technology as well as the elliptic curve cryptography. To get better correctness and deployment guarantees of applications models in early development stages, we propose a new UML profile called GR-UML to add new semantics allowing the modelling of probabilistic scenarios running under memory and energy constraints, then we propose a methodology using transformations between the GR-UML, the GR-TNCES Petri nets formalism, and the IEC 61499 function blocks. A software tool implementing the methodology concepts is developed. To show the suitability of the mentioned contributions two case studies (baggage handling system and microgrids) are considered.In diesem Projekt schlagen wir ein Framework für die Entwicklung von kontextbewussten, sicheren Anwendungen von verteilten rekonfigurierbaren Systemen vor. Kontextbewusstheit ist eine Schlüsseleigenschaft, die die Anpassung des Systemverhaltens an die sich ändernde Umgebung ermöglicht. Wir führen eine Definition des Begriffs ``Kontext" für rekonfigurierbare Systeme ein und definieren dann einen Kontextmodellierungs- und Reasoning-Ansatz. Danach definieren wir ein Metamodell für kontextbewusste rekonfigurierbare Anwendungen, das den Weg zum vorgeschlagenen Framework ebnet. Das Framework hat eine dreischichtige Architektur: Rekonfigurations-, Kontextkontroll- und Dienste-Schicht, wobei jede Schicht ihre wohldefinierte Rolle hat. Wir definieren auch ein sicheres Konversationsprotokoll zwischen verteilten Teilen, das auf der Blockchain-Technologie sowie der elliptischen Kurven-Kryptographie basiert. Um bessere Korrektheits- und Einsatzgarantien für Anwendungsmodelle zu erhalten, schlagen wir ein UML-Profil namens GR-UML vor, um Semantik umzufassen, die die Modellierung probabilistischer Szenarien unter Speicher- und Energiebeschränkungen ermöglicht. Dann schlagen wir eine Methodik vor, die Transformationen zwischen GR-UML, dem GR-TNCES-Petrinetz-Formalismus und den IEC 61499-Funktionsblöcken verwendet. Es wird ein Software entwickelt, das die Konzepte der Methodik implementiert. Um die Eignung der genannten Beiträge zu zeigen, werden zwei Fallstudien betrachtet

Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus

This is an open access book. It gathers the first volume of the proceedings of the 31st edition of the International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, held on June 19 – 23, 2022, in Detroit, Michigan, USA. Covering four thematic areas including Manufacturing Processes, Machine Tools, Manufacturing Systems, and Enabling Technologies, it reports on advanced manufacturing processes, and innovative materials for 3D printing, applications of machine learning, artificial intelligence and mixed reality in various production sectors, as well as important issues in human-robot collaboration, including methods for improving safety. Contributions also cover strategies to improve quality control, supply chain management and training in the manufacturing industry, and methods supporting circular supply chain and sustainable manufacturing. All in all, this book provides academicians, engineers and professionals with extensive information on both scientific and industrial advances in the converging fields of manufacturing, production, and automation