1,804 research outputs found

    Machine Learning Methods for Product Quality Monitoring in Electric Resistance Welding

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    Elektrisches Widerstandsschweißen (Englisch: Electric Resistance Welding, ERW) ist eine Gruppe von vollautomatisierten Fertigungsprozessen, bei denen metallische Werkstoffe durch WĂ€rme verbunden werden, die von elektrischem Strom und Widerstand erzeugt wird. Eine genaue QualitĂ€tsüberwachung von ERW kann oft nur teilweise mit destruktiven Methoden durchgeführt werden. Es besteht ein großes industrielles und wirtschaftliches Potenzial, datengetriebene AnsĂ€tze für die QualitĂ€tsüberwachung in ERW zu entwickeln, um die Wartungskosten zu senken und die QualitĂ€tskontrolle zu verbessern. Datengetriebene AnsĂ€tze wie maschinelles Lernen (ML) haben aufgrund der enormen Menge verfügbarer Daten, die von Technologien der Industrie 4.0 bereitgestellt werden, viel Aufmerksamkeit auf sich gezogen. Datengetriebene AnsĂ€tze ermöglichen eine zerstörungsfreie, umfassende und prĂ€zise QualitĂ€tsüberwachung, wenn eine bestimmte Menge prĂ€ziser Daten verfügbar ist. Dies kann eine umfassende Online-QualitĂ€tsüberwachung ermöglichen, die ansonsten mit herkömmlichen empirischen Methoden Ă€ußerst schwierig ist. Es gibt jedoch noch viele Herausforderungen bei der Adoption solcher AnsĂ€tze in der Fertigungsindustrie. Zu diesen Herausforderungen gehören: effiziente Datensammlung, die dasWissen von erforderlichen Datenmengen und relevanten Sensoren für erfolgreiches maschinelles Lernen verlangt; das anspruchsvolle Verstehen von komplexen Prozessen und facettenreichen Daten; eine geschickte Selektion geeigneter ML-Methoden und die Integration von DomĂ€nenwissen für die prĂ€diktive QualitĂ€tsüberwachung mit inhomogenen Datenstrukturen, usw. Bestehende ML-Lösungen für ERW liefern keine systematische Vorgehensweise für die Methodenauswahl. Jeder Prozess der ML-Entwicklung erfordert ein umfassendes Prozess- und DatenverstĂ€ndnis und ist auf ein bestimmtes Szenario zugeschnitten, das schwer zu verallgemeinern ist. Es existieren semantische Lösungen für das Prozess- und DatenverstĂ€ndnis und Datenmanagement. Diese betrachten die Datenanalyse als eine isolierte Phase. Sie liefern keine Systemlösungen für das Prozess- und DatenverstĂ€ndnis, die Datenaufbereitung und die ML-Verbesserung, die konfigurierbare und verallgemeinerbare Lösungen für maschinelles Lernen ermöglichen. Diese Arbeit versucht, die obengenannten Herausforderungen zu adressieren, indem ein Framework fĂŒr maschinelles Lernen für ERW vorgeschlagen wird, und demonstriert fünf industrielle AnwendungsfĂ€lle, die das Framework anwenden und validieren. Das Framework ĂŒberprĂŒft die Fragen und DatenspezifitĂ€ten, schlĂ€gt eine simulationsunterstützte Datenerfassung vor und erörtert Methoden des maschinellen Lernens, die in zwei Gruppen unterteilt sind: Feature Engineering und Feature Learning. Das Framework basiert auf semantischen Technologien, die eine standardisierte Prozess- und Datenbeschreibung, eine Ontologie-bewusste Datenaufbereitung sowie halbautomatisierte und Nutzer-konfigurierbare ML-Lösungen ermöglichen. Diese Arbeit demonstriert außerdem die Übertragbarkeit des Frameworks auf einen hochprĂ€zisen Laserprozess. Diese Arbeit ist ein Beginn des Wegs zur intelligenten Fertigung von ERW, der mit dem Trend der vierten industriellen Revolution korrespondiert

    A Corrosion Control Manual for Rail Rapid Transit

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    This manual addresses corrosion problems in the design, contruction, and maintenance of rapid transit systems. Design and maintenance solutions are provided for each problem covered. The scope encompasses all facilities of urban rapid transit systems: structures and tracks, platforms and stations, power and signals, and cars. The types of corrosion and their causes as well as rapid transit properties are described. Corrosion control committees, and NASA, DOD, and ASTM specifications and design criteria to which reference is made in the manual are listed. A bibliography of papers and excerpts of reports is provided and a glossary of frequently used terms is included

    An investigation into the prognosis of electromagnetic relays.

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    Electrical contacts provide a well-proven solution to switching various loads in a wide variety of applications, such as power distribution, control applications, automotive and telecommunications. However, electrical contacts are known for limited reliability due to degradation effects upon the switching contacts due to arcing and fretting. Essentially, the life of the device may be determined by the limited life of the contacts. Failure to trip, spurious tripping and contact welding can, in critical applications such as control systems for avionics and nuclear power application, cause significant costs due to downtime, as well as safety implications. Prognostics provides a way to assess the remaining useful life (RUL) of a component based on its current state of health and its anticipated future usage and operating conditions. In this thesis, the effects of contact wear on a set of electromagnetic relays used in an avionic power controller is examined, and how contact resistance combined with a prognostic approach, can be used to ascertain the RUL of the device. Two methodologies are presented, firstly a Physics based Model (PbM) of the degradation using the predicted material loss due to arc damage. Secondly a computationally efficient technique using posterior degradation data to form a state space model in real time via a Sliding Window Recursive Least Squares (SWRLS) algorithm. Health monitoring using the presented techniques can provide knowledge of impending failure in high reliability applications where the risks associated with loss-of-functionality are too high to endure. The future states of the systems has been estimated based on a Particle and Kalman-filter projection of the models via a Bayesian framework. Performance of the prognostication health management algorithm during the contacts life has been quantified using performance evaluation metrics. Model predictions have been correlated with experimental data. Prognostic metrics including Prognostic Horizon (PH), alpha-Lamda (α-λ), and Relative Accuracy have been used to assess the performance of the damage proxies and a comparison of the two models made

    Feasibility of remotely manipulated welding in space. A step in the development of novel joining technologies

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    In order to establish permanent human presence in space technologies of constructing and repairing space stations and other space structures must be developed. Most construction jobs are performed on earth and the fabricated modules will then be delivered to space by the Space Shuttle. Only limited final assembly jobs, which are primarily mechanical fastening, will be performed on site in space. Such fabrication plans, however, limit the designs of these structures, because each module must fit inside the transport vehicle and must withstand launching stresses which are considerably high. Large-scale utilization of space necessitates more extensive construction work on site. Furthermore, continuous operations of space stations and other structures require maintenance and repairs of structural components as well as of tools and equipment on these space structures. Metal joining technologies, and especially high-quality welding, in space need developing

    The materials processing research base of the Materials Processing Center

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    The goals and activities of the center are discussed. The center activities encompass all engineering materials including metals, ceramics, polymers, electronic materials, composites, superconductors, and thin films. Processes include crystallization, solidification, nucleation, and polymer synthesis

    Engineering Principles

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    Over the last decade, there has been substantial development of welding technologies for joining advanced alloys and composites demanded by the evolving global manufacturing sector. The evolution of these welding technologies has been substantial and finds numerous applications in engineering industries. It is driven by our desire to reverse the impact of climate change and fuel consumption in several vital sectors. This book reviews the most recent developments in welding. It is organized into three sections: “Principles of Welding and Joining Technology,” “Microstructural Evolution and Residual Stress,” and “Applications of Welding and Joining.” Chapters address such topics as stresses in welding, tribology, thin-film metallurgical manufacturing processes, and mechanical manufacturing processes, as well as recent advances in welding and novel applications of these technologies for joining different materials such as titanium, aluminum, and magnesium alloys, ceramics, and plastics

    FATIGUE ASSESSMENT OF COMPLEX STRUCTURAL COMPONENTS OF STEEL BRIDGES INTEGRATING FINITE ELEMENT MODELS AND FIELD-COLLECTED DATA

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    Fatigue damage in welded structural steel components has a complex presentation, which is influenced by the geometric configuration of the component and load path in a structural system. The classic fatigue assessment methods, using nominal stresses and S-N curves, may not capture nor predict the complicated performance of the component with respect to fatigue. Recent novel complex steel structural connections that experience multi-axial behavior or do not fit any conventional fatigue categories are not explicitly addressed in the existing fatigue design codes. An ideal fatigue estimation for the complex structural components is dependent on a thorough understanding of structural performance of the component within the global structural system and application of an appropriate fatigue assessment method. This dissertation presents a fatigue assessment protocol for complex structural components of steel bridges, using numerical methods and field-collected structural response data. Multiple fatigue assessment methods are implemented, including the nominal stress method, hotspot stress method, and linear elastic fracture mechanics method to estimate fatigue performance of a complex welded structural component. Accordingly, for each method, a set of computationally efficient finite element models of a large-scale bridge are created. Each model corresponds to the requirements of a specific fatigue assessment method and provides the required stress responses, under simulated dynamic traffic loads. A major contribution of this research is the development of a novel a multi-scale modeling method to accommodate multiple dimensions of elements and multiple axes loading configurations. The multi-scale models are created for a case study, the Memorial Bridge in Portsmouth, NH, which is a vertical lift steel truss bridge and includes a novel gusset-less connection. The gusset-less connection includes a complex web geometry and curved fillet welds connecting the web to the flange. The bridge is also equipped with a long-term structural health monitoring program, with arrays of installed sensors. Field data are collected from the sensors to report the health status of the bridge. Additionally, field-collected data are utilized to validate the finite element models created for this study. Due to the limited sensor location available, finite element models are used to predict structural responses that will supplement the field-collected data to appropriately provide stress- concentrated responses at the welded components of the bridge. The multi-scale model results illustrate that the geometric shape of the weld impacts the variability of the generated hotspot stresses along the weld toe. The changes in the stress state and estimated fatigue life are investigated during the crack propagation procedure, using a multi-scale model with a simulated crack

    Nonterrestrial utilization of materials: Automated space manufacturing facility

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    Four areas related to the nonterrestrial use of materials are included: (1) material resources needed for feedstock in an orbital manufacturing facility, (2) required initial components of a nonterrestrial manufacturing facility, (3) growth and productive capability of such a facility, and (4) automation and robotics requirements of the facility
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