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Tessellated Surface MachiningLu, Jiewu 14 February 2007 (has links) (PDF)
Sculptured surface machining (SSM) is the end milling of sculptured surfaces with multi-axis machine tools. SSM consists of the tessellated model machining (TMM) and the parametric model machining (PMM). The former is gaining more and more attention over the past decade because it offers many advantages over the latter. New methods for various machining stages of TMM are proposed in this dissertation. First, in the 5-axis finish machining stage, a 3-dimension Configuration-space (3D C-space) machining method is presented. Next, in clean-up machining stage, an effective and creative approach is introduced. Finally, a complete TMM system is developed. The TMM system is developed with C++ on Windows platform. Benchmarks are used to test the methods proposed in this dissertation. The results show that methods are accurate and efficient.
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Vom CAD-Modell über die Simulation zum 3D-Druck und zurück : Simulationsansätze in einer, durch den 3D-Druck entfesselten, neuen GestaltungsfreiheitPrinz, Ralf 22 July 2016 (has links) (PDF)
War bisher die Gestalt von Bauteilen und Baugruppen in Konstruktionen sehr stark durch ihre Fertigungsverfahren beeinflusst, so ändern sich diese Vorgaben durch die Verwendung von 3D- Druck auf beinahe revolutionäre Art und Weise. Und somit werden Ansätze salonfähig, die bisher doch eher selten in Anwendung waren, wie z.B. Gitterstrukturen oder Topologieoptimierung. Diese finden nun wieder häufiger ihren Weg in die Bauteil- und Baugruppenstrukturen. Die Verwendung birgt aber auch damit einhergehende Herausforderungen, da sich z.B. die Bauteilgrößen nach einer Topologieoptimierung drastisch vergrößern und z.B. auch die Glättung der Teile für den Druck, sowie die Rückführung in die CAD-Systeme, häufig noch eine ungelöste Aufgabe darstellen. Diese Ansätze müssen bezogen auf den PLM Gedanken, prozesstechnisch durchdacht und entsprechend implementiert werden. Der Vortrag beschäftigt sich mit der dafür notwendigen Prozesskette vom CAD-Model über die Simulationsverfahren wie Topologieoptimierung oder Gitterstrukturen, Glättung von Strukturen u.v.m. sowie deren Rückführung ins CAD/PLM.
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Anomaly Detection on Embedded Sensor Processing PlatformCao, Yichen January 2021 (has links)
Embedded platforms are often used as a sensor data processing node to collect data and transmit the data to the remote server. Due to the poor performance and power limitation, data processing was often left to the remote server. With the improvement of the computation ability, it is becoming possible to do some partial data processing on the embedded platforms, which would reduce the power and time consumption on the data transmission. Moreover, processing the data locally on the embedded platforms could reduce the dependence on the network. The platform could even do some tasks offline. This project aims to explore effective data analysis methods, especially for anomaly detection, which could be implemented on the embedded platform to be analyzed and detected locally. In this project, we select four methods: Seasonal and Trend Decomposition Using Loess (STL), Autoregressive Integrated Moving Average Model (ARIMA), Vector Autoregression (VAR), Long ShortTerm Memory (LSTM), to implement on the embedded platform ESP32. To test which methods could better fit the platform, we evaluate and compare the result from two aspects: the time overhead and the accuracy. The results show that the STL has the highest detection accuracy, but its time overhead is significantly higher than all other methods. ARIMA has the smallest time overhead and higher accuracy than LSTM and VAR. For LSTM, the method performs better with univariable input than multivariable input. Finally, we discuss the factors that may influence the result and future works. / Inbäddade plattformar används ofta som en sensor databehandlingsnod för att samla in och sedan överföra data till fjärrservern. Databehandling lämnades ofta till fjärrservern på grund av den dåliga prestandan och effektbegränsningen. Med förbättrad beräkningsförmåga blir det framkomligt att göra en del databehandling på de inbäddade plattformarna, vilket skulle minska ström och tidsförbrukningen för dataöverföringen. För övrigt kan lokal behandling av data på de inbäddade plattformarna minska beroendet av nätverket. Plattformen kan till och med utföra vissa uppgifter I nedkopplat läge. Detta projekt avser att utforska effektiva dataanalysmetoder särskilt för avvikelsedetektering, som kan verkställas på den inbäddade plattformen för att analyseras och upptäckas lokalt. I det här projektet väljer vi fyra metoder för att införa på den inbäddade plattformen ESP32: Seasonal and Trend Decomposition Using Loess (STL), Autoregressive Integrated Moving Average Model (ARIMA), Vector Autoregression (VAR), Long Short-Term Memory (LSTM). För att testa vilka metoder som bättre passar plattformen utvärderar och jämför vi resultatet med hänsyn till två aspekter: tidsomkostnaderna och noggrannheten. Resultaten visar att STL har den högsta detektionsnoggrannheten, men dess tidsomkostning är betydligt högre än alla andra metoder. ARIMA har den minsta tidsomkostningen och högre noggrannhet än LSTM och VAR. För LSTM fungerar metoden bättre med univariable input än multivariable input. Slutligen diskuterar vi faktorerna som möjligtvis påverkar resultatet och framtida arbeten.
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"Man måste plocka russinen ur kakan" : En intervjustudie om lärares uppfattningar och erfarenheter av arbete med Skriva sig till lärande.Jakobsson, Hilda, Jonsson, Anders January 2023 (has links)
No description available.
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A Level Set Approach for Denoising and Adaptively Smoothing Complex Geometry Stereolithography FilesJanuary 2014 (has links)
abstract: Stereolithography files (STL) are widely used in diverse fields as a means of describing complex geometries through surface triangulations. The resulting stereolithography output is a result of either experimental measurements, or computer-aided design. Often times stereolithography outputs from experimental means are prone to noise, surface irregularities and holes in an otherwise closed surface.
A general method for denoising and adaptively smoothing these dirty stereolithography files is proposed. Unlike existing means, this approach aims to smoothen the dirty surface representation by utilizing the well established levelset method. The level of smoothing and denoising can be set depending on a per-requirement basis by means of input parameters. Once the surface representation is smoothened as desired, it can be extracted as a standard levelset scalar isosurface.
The approach presented in this thesis is also coupled to a fully unstructured Cartesian mesh generation library with built-in localized adaptive mesh refinement (AMR) capabilities, thereby ensuring lower computational cost while also providing sufficient resolution. Future work will focus on implementing tetrahedral cuts to the base hexahedral mesh structure in order to extract a fully unstructured hexahedra-dominant mesh describing the STL geometry, which can be used for fluid flow simulations. / Dissertation/Thesis / Masters Thesis Aerospace Engineering 2014
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Aplikace řídicího systému Simatic pro řízení balícího stroje / Application of the Simatic control system for the packaging machine controlUrbánek, Tomáš January 2014 (has links)
Masters thesis deals with the SIMATIC, which is the process control system from Siemens. Simatic belongs to the group of so-called programmable logic controllers (English Programmable Logic Controller). It is a microcomputer that processes the instructions in real time. I have designed a control algorithm and HMI visualization in my Masterś thesis. Moreover,my attention is focused on PLC S7 - 300. The S7-313C is used for implementations. The proposed solution has been tested and operated in real conditions
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Manufacturing Feature Recognition by 3D Solid Model Slicing and Contour Based Geometric ReasoningPullat, Rajendran January 2010 (has links)
No description available.
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Effects of MIFID II on Stock Trade Volumes of Nasdaq Stockholm / MIFID II- Effekter på Nasdaq Stockholms Handlade AktievolymerElling, Eva January 2019 (has links)
Introducing new financial legislation to financial markets require caution to achieve the intended outcome. This thesis aims to investigate whether or not the newly installed revised Markets in Financial Instruments Directive- the MIFID II regulation - temporally influenced the trading stock volume levels of Nasdaq Stockholm during its introduction to the Swedish stock market. A first approach of a generalized Negative Binomial model is carried out on aggregated data, followed by an individual Fixed Effects model in an attempt to eliminate omitted variable bias caused by missing unobserved variables for the individual stocks. The aggregated data is attained by taking the equally weighted average of the trading volume and adjusting for seasonality through Seasonal and Trend decomposition using Loess in combination with a regression model with ARIMA errors to mitigate calendar effects. Due to robustness of the aggregated data, the Negative Binomial model manage to capture significant effects of the regulation on the Small Cap. segment, even though clusters of the data show signs of divergent reactions to MIFID II. Since the Fixed Effects model operate on non-aggregated TSCS data and because of the varying effects on each stock the Fixed Effect model fails in its attempt to do the same. / Implementation av nya finansiella regelverk på finansmarknaden kräver aktsamhet för att uppnå de tilltänka målen. Det här arbetet undersöker huruvida MIFID II regleringen orsakade en temporär medelvärdesskiftning av de handlade aktievolymerna på Nasdaq Stockholm under regelverkets introduktion på den svenska marknaden. Först testas en generaliserad Negative Binomial regression applicerat på aggregerad data, därefter en individuell Fixed Effects modell för att försöka eliminera fel på grund av saknade, okända variabler. Det aggrigerade datasettet erhålls genom att ta genomsnittet av handelsvolymerna och justera dessa för sässongsmässiga mönster med metoden STL i kombination med regression med ARIMA residualer för att även ta hänsyn till kalender relaterade effekter. Eftersom den aggrigerade datan är robust lyckas the Negative Binomial regressionen fånga signifikanta effekter av regleringen för Small Cap. segmentet trots att datat uppvisar tecken på att subgrupper inom segmentet reagerat väldigt olika på den nya regleringen. Eftersom Fixed Effects modellen är applicerad på icke-aggrigerad TSCS data och pågrund av den varierande effekten på de individuella aktierna lyckas inte denna modell med detta.
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Stereolithography (STL) File Modification by Vertex Translation Algorithm (VTA) for Precision Layered ManufacturingNavangul, Gaurav D. 20 September 2011 (has links)
No description available.
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Synthesis and Reactivity of Rare Earth Metals Complexes with a Nitrogen Donor Ligand. Compounds in Formal Low Oxidation States / Synthese un Reaktivität von Seltenerden Metallkomplexe mit einem Stickstoff-Donor Ligand. Verbindungen in den formalen niedrigen OxidationstufenNeculai, Ana-Mirela 08 May 2003 (has links)
No description available.
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