1,720,997 research outputs found
IEC 61499:llä toteutettu moniulotteisen aikasarjadatan hajautettu keräysjärjestelmä
No full textModern industrial systems create a vast amount of data that must be collected for analysis. This data is not necessarily easily accessible at once. Components of the system may expose their data in the network through communication protocols such as OPC UA. If the equipment hosting the OPC UA server lacks tools to actively push data to some permanent storage, such as a time series database, a data collector must be implemented to fetch the data from the endpoint and write it to the TSDB.
IEC 61499 can be leveraged in creating the collector. It allows an application developer to quickly assemble and configure the collector out of modular parts, contained in Function Blocks. Service Interface function blocks can also be used to implement an interface for the analysis software, allowing the same developer to distribute analysis tasks to devices in the network using IEC 61499's device model. This is especially useful since simple data ingestion from source to TSDB may impose a relatively light computation load, but analysis will often require a powerful PC with a GPU.
This work presents a data collection and analysis FB library for the 4DIAC Forte runtime environment. The FB library contains tools to route data from OPC UA servers to a TSDB, filter out unwanted data, and instantiate and configure Python based analysis algorithms and interface them via SIFBs.Nykyaikaiset automaatiojärjestelmät tuottavat suuria määriä dataa, jota voidaan kerätä talteen analyysia varten. Data tulee kuitenkin usein hajautetusti useista lähteistä, ja järjestelmän osat saattavat julkaista datansa käyttäen korkean luokan viestintäjärjestelmiä, kuten OPC UA:ta. Jos dataa julkaiseva laite ei kykene itse lähettämään viestejä varastoinnista vastaavalle laitteelle, kuten aikasarjatietokannalle, täytyy erillisen keräysjärjestelmän kerätä data.
IEC 61499:tä voidaan hyödyntää keräysjärjestelmän kehityksessä. Sen avulla ohjelmistokehittäjä voi nopeasti ja helposti koota keräysjärjestelmän valmiiksi kehitetyistä modulaarisista osista. Moninimutkaisiakin järjestelmiä, kuten analyysiohjelmaa, voidaan kuvata IEC 61499:n graafisella ohjelmointikielellä. Monimutkainen ohjelma voidaan piilottaa yksinkertaisen käyttöliittymän taakse. IEC 61499 mahdollistaa myös ohjelman osien hajauttamisen verkossa oleville laitteille. Keräilyn voi suorittaa verkon reunalaita, kun taas laskennallisesti raskaan analyysiohjelman voi ladata tehokkaalla näyttökortilla varustetulle tietokoneelle.
Tässä työssä esitellään datankeräystä ja analyysia varten kehitetty FB-kirjasto, joka sisältää työkaluja datankeruuseen OPC UA-palvelimilta, kiinnostavan ja turhan datan erotteluun, sekä Pythonilla kirjoitettujen analyysialgoritmien ajoon
IEC 61499 -standardia noudattavien ohjelmistojen tietojen siirrettävyys
No full textThis master’s thesis investigates the portability features of three different IEC 61499 standard compliant tools. Firstly, the thesis introduces the standard’s capabilities, then illustrates its use with a few example cases. The study continues by focusing on migrating the basic and composite function block types and system architecture with application networks and device configurations from one tool to another. A converter program is subsequently created using Python programming language to automate the required modification process, thus enabling the files to migrate between the compliant tools. The study takes into consideration NxtStudio, FBDK and 4DIAC software tools. In every tool, similar function blocks and system structures are created. The portability of these created elements is examined between the tools, resulting in a table that numerically evaluates the portability from one tool to another.Tässä diplomityössä tutkitaan kolmen erilaisen IEC 61499 -standardia noudattavan ohjelmiston tietojen siirrettävyyttä keskenään. Työssä käydään ensin läpi standardissa olevia ominaisuuksia, ja muutama esimerkkitoteutus oikeisiin sovelluksiin tuodaan esille. Tätä seuraa tutkimus, joka keskittyy standardin perus- ja komposiittifunktiolaatikoiden sekä järjestelmän arkkitehtuurin funktiolaatikkoverkon ja laitekonfiguraatioiden siirtämiseen yhden sovellustuottajan ohjelmasta toisen sovellustuottajan ohjelmaan. Tutkimuksen tuloksiin perustuen kehitetään Python-kielinen muunnosohjelma, joka suorittaa tarvittavat muutokset eri ohjelmistoissa tehtyihin tiedostoihin, jotta ne olisivat siirrettävissä toisesta ohjelmasta toiseen ohjelmaan. Tutkielma keskittyy NxtStudio, FBDK ja 4DIAC ohjelmistoihin. Jokaisessa ohjelmistossa luodaan samanlaiset funktiolaatikot ja järjestelmät, joiden siirrettävyydestä toiseen ohjelmaan tehdään numeerinen taulukko kertoen siirrettävyyden onnistumisesta
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Proposing mechanisms to increase the reliability between distributed devices in the IEC61499 Standard
Full text linkThe need for smarter and efficient production in the Industry 4.0 era is being achieved with the help of component-based architecture. Control applications designed using the IEC61499 standard and based on the component-based architecture can be distributed over various devices connected to one-another via the wired or the wireless medium. While the distribution of control application on different devices drastically increases the flexibility and modularity, the reliability across the control application can be affected due to the increased needs of communication between the devices. In this thesis, an advanced handshake message verification algorithm has been developed and tested, to ensure the reliability between devices communicating over a lossy wireless channel. The mechanism has been designed so as to be easily integrated in the existing control application and perform the reliability operations over the existing communication network
Comparative analysis of Life Cycle Assessment data sharing models for supply chains
No full textThe reliability of Life Cycle Assessment (LCA) is highly dependent on the quality of the data used. This thesis examines the current landscape of LCA data sharing within supply chains and collaborative consortia, with a particular focus on three critical aspects: interoperability, data provenance and scalability. The study evaluates three key data sharing architectures, Blockchain, International Data Spaces (IDS) and a Trusted Operator system, as well as three of the most prominent data formats, ILCD, EcoSpold and JSON-LD. Using a qualitative comparison, the analysis addresses criteria such as efficiency, data provenance, immutability, scalability, and security. The results reveal that IDS provides the best balance of scalability and flexibility, making it suitable for complex supply chain applications. While the choice of data format was found to be less critical, compatibility with regional databases and commonly used software remains essential.Elinkaariarvioinnin (Life Cycle Assessment, LCA) luotettavuus riippuu merkittävästi käytetyn datan laadusta. Tämä tutkielma tarkastelee LCA-datan jakamisen nykytilaa toimitusketjuissa ja yhteistyökonsortioissa keskittyen erityisesti kolmeen osa-alueeseen: yhteentoimivuuteen, datan jäljitettävyyteen ja skaalaavuuteen. Tutkimuksessa arvioidaan kolmea keskeistä datan jakamisen arkkitehtuuria: lohkoketjuja (Blockchain), data-avaruuksia (IDS) sekä luotettuun operaattoriin perustuvaa mallia. Lisäksi tarkastelun kohteena ovat kolme yleisesti käytettyä tiedostoformaattia: ILCD, EcoSpold ja JSON-LD. Kvalitati-visen vertailun avulla analyysi käsittelee kriteerejä, kuten tehokkuus, datan jäljitettävyys, muuttumattomuus, skaalaavuus ja tietoturva. Tulokset osoittavat, että IDS tarjoaa parhaan tasapainon skaalaavuuden ja joustavuuden välillä, mikä tekee siitä sopivan vaihtoehdon monimutkaisiin toimitusketjujen sovelluksiin. Tiedostoformaatin valinnan todettiin olevan vähemmän kriittinen, mutta yhteensopivuus alueellisten tietokantojen ja käytettävien ohjelmistojen kanssa on edelleen olennaist
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Applying machine learning in the Aalto Factory of the Future
Full text linkAwareness of machine errors in industrial manufacturing improves production efficiency and quality. Ignoring machine errors can increase maintenance costs and the risk of serious damages on machines and products. Furthermore, machine errors decrease overall efficiency due to production downtime. This thesis studies and presents approaches of the workflow necessary to implement a machine learning model as a tool to detect, classify and predict errors in industrial manufacturing and continuous process systems. Stream data is collected from two real demonstrators at the Aalto Factory of the Future: EnAS and a turbocharger. The data is used to experimentally validate the workflow and analyze possible alternatives to the methodology to create an ML model. The experimentation includes variations focused on using three classifiers from the scikit-learn machine learning Python library (logistic regression, support vector classifier, and decision tree), all trained using five different feature choices extracted from the data sets. The best results obtained from the data collected from EnAS came from a support vector classifier model which received a 91.4% recall score during testing, indicating that 91.4% of test errors were correctly classified. A decision tree classifier model performed the best on the turbocharger data set, resulting in recall scores of 99.9% and 81.3% using two different feature sets. Error detection and prediction for both EnAS and the turbocharger require high accuracy for correctly classifying errors. Incorrectly classifying error runs as normal runs may lead to catastrophic unrecoverable states in the machine, requiring a manual reboot of the whole control system
Safe Reinforcement Learning based Optimization of a Cruise Ship Energy Management System
No full textThe cruise ship industry is a large emitter of greenhouse gases. Multiple aspects must be tackled to help make the industry more sustainable and adhere to the net-zero emission goal set by the International Maritime Organization (IMO). One aspect is the optimization of the energy management of the ship, which can lead to large gains in energy savings. Traditional optimization approaches, such as linear optimization struggle to scale to large stochastic problem spaces such as that of a ship energy system. Modern approaches, such as reinforcement learning, are shown to be more effective at the task at hand. However, these approaches often lack a direct focus on safety, thus making them impractical for real-world applications.
This thesis presents work in the development of a safe reinforcement learning (RL) system for ship energy optimization. As part of the system, a ship's microgrid environment was developed alongside a reinforcement learning agent. The results showcase the potential of RL approaches for energy optimization as opposed to alternative approaches. The inclusion of safety-focused methods, such as utilizing a safety shield and a large language model-generated reward function, was shown to be effective at enhancing safety, reducing the number of safety violations by 87% when the agent was trained and tested in a surrogate model
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