Measurements, Models, Systems and Design

531 s.

Economic and environmental impact assessment through system dynamics of technology-enhanced maintenance services

This work presents an economic and environmental impact assessment of maintenance services in order to evaluate how they contribute to sustainable value creation through field service delivery supported by advanced technologies. To this end, systems dynamics is used to assist the prediction of economic and environmental impacts of maintenance services supported by the use of an e-maintenance platform implementing prognosis and health management. A special concern is given to the energy use and related carbon footprint as environmental impacts

Entwicklung und Analyse eines Zug-zentrischen Entfernungsmesssystems mittels Colored Petri Nets

Based on the technology trends, the train control system should weaken the proportion of ground facilities, and give trains more individual initiative than in the past. As a result, the safety and flexibility of the train control system can be further improved. In this thesis, an enhanced movement authority system is proposed, which combines advantages of the train-centric communication with current movement authority mechanisms. To obtain the necessary train distance interval data, the onboard equipment and a new train-to-train distance measurement system (TTDMS) are applied as normal and backup strategies, respectively. While different location technologies have been used to collect data for trains, the development and validation of new systems remain challenges. In this thesis, formal approaches are presented for developing and verifying TTDMS. To assist the system development, the Colored Petri nets (CPNs) are used to formalize and evaluate the system structure and its behavior. Based on the CPN model, the system structure is validated. Additionally, a procedure is proposed to generate a Code Architecture from the formal model. The system performance is assessed in detection range and accuracy. Therefore both mathematical simulation and practical measurements validation are implemented. The results indicate that the system is feasible to carry out distance measurements both in metropolitan and railway lines, and the formal approaches are reusable to develop and verify other systems. As the target object, TTDMS is based on a spread-spectrum technology to accomplish distance measurement. The measurement is carried out by applying Time of Arrival (TOA) to calculate the distance between two trains, and requires no synchronized time source of transmission. It can calculate the time difference by using the autocorrelation of Pseudo Random Noise (PRN) code. Different from existing systems in air and maritime transport, this system does not require any other localization unit, except for communication architecture. To guarantee a system can operate as designed, it needs to be validated before its application. Only when system behaviors have been validated other relative performances' evaluations make sense. Based on the unambiguous definition of formal methods, TTDMS can be described much clearer by using formal methods instead of executable codes.Basierend auf technologischen Trends sollte das Zugbeeinflussungssystem den Anteil der Bodenanlagen reduzieren und den Zügen mehr Eigeninitiative geben als in der Vergangenheit, da so die funktionale Sicherheit und die Flexibilität des Zugbeeinflussungssystems erhöht werden können. In dieser Arbeit wird ein verbessertes System vorgeschlagen, das die Vorteile der zugbezogenen Kommunikation mit den aktuellen Fahrbefehlsmechanismen kombiniert. Um die notwendigen Daten des Zugabstandsintervalls zu erhalten, werden die Bordausrüstung und ein neues Zug-zu-Zug-Entfernungsmesssystem (TTDMS) als normale bzw. Backup-Strategien angewendet. Während verschiedene Ortungstechnolgien zur Zugdatenerfassung genutzt wurden, bleibt die Entwicklung und Validierung neuer Systeme eine Herausforderung. In dieser Arbeit werden formale Ansätze zur Entwicklung und Verifikation von TTDMS vorgestellt. Zur Unterstützung der Systementwicklung werden CPNs zur Formalisierung und Bewertung der Systemstruktur und ihres Verhaltens eingesetzt. Basierend auf dem CPN-Modell wird die Systemstruktur validiert. Zusätzlich wird eine Methode vorgeschlagen, mit der eine Code-Architektur aus dem formalen Modell generiert werden kann. Die Systemleistung wird im Erfassungsbereich und in der Genauigkeit beurteilt. Daher werden sowohl eine mathematische Simulation als auch eine praktische Validierung der Messungen implementiert. Die Ergebnisse zeigen, dass das System in der Lage ist, Entfernungsmessungen in Metro- und Eisenbahnlinien durchzuführen. Zudem sind die formalen Ansätze bei der Entwicklung und Verifikation anderer Systeme wiederverwendbar. Die Abstandsmessung mit TTDMS basiert auf einem Frequenzspreizungsverfahren. Die Messung wird durchgeführt, indem die Ankunftszeit angewendet wird, um den Abstand zwischen zwei Zügen zu berechnen. Dieses Verfahren erfordert keine Synchronisierung der Zeitquellen der Übertragung. Der Zeitunterschied kann damit berechnet werden, indem die Autokorrelation des Pseudo-Random-Noise-Codes verwendet wird. Im Unterschied zu Systemen im Luft- und Seeverkehr benötigt dieses System keine andere Lokalisierungseinheit als die Kommunikationsarchitektur. Um zu gewährleisten, dass ein System wie vorgesehen funktioniert, muss es validiert werden. Nur wenn das Systemverhalten validiert wurde, sind Bewertungen anderer relativer Leistungen sinnvoll. Aufgrund ihrer eindeutigen Definition kann das TTDMS mit formalen Methoden klarer beschrieben werden als mit ausführbaren Codes

Industrial Applications: New Solutions for the New Era

This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section

FAULT DETECTION AND ISOLATION FOR WIND TURBINE DYNAMIC SYSTEMS

This work presents two fault detection and isolation (FDI) approaches for wind turbine systems (WTS). Firstly, a non-linear mathematical model for wind turbine (WT) dynamics is developed. Based on the developed WTS mathematical model, a robust fault detection observer is designed to estimate system faults, so as to generate residuals. The observer is designed to be robust to system disturbance and sensitive to system faults. A WT blade pitch system fault, a drive-train system gearbox fault and three sensor faults are simulated to the nominal system model, and the designed observer is then to detect these faults when the system is subjected to disturbance. The simulation results showed that the simulated faults are successfully detected. In addition, a neural network (NN) method is proposed for WTS fault detection and isolation. Two radial basis function (RBF) networks are employed in this method. The first NN is used to generate the residual from system input/output data. A second NN is used as a classifier to isolate the faults. The classifier is trained to achieve the following target: the output are all “0”s for no fault case; while the output is “1” if the corresponding fault occurs. The performance of the developed neural network FDI method was evaluated using the simulated three sensor faults. The simulation results demonstrated these faults are successfully detected and isolated by the NN classifier

Intelligent distributed process monitoring and management system

Monitoring systems represent an important tool to support efforts aimed at improving productivity and quality, reducing waste and enhancing safety in manufacturing. Modern technologies including electronic devices, communication technology, the Internet, database systems and modern computer technology represent resources that can provide flexible and cost accessible attractive and efficient solutions for the implementation of distributed and intelligent monitoring systems. A new generation of microcontrollers offer a high level of integrated devices and operate at low power, making them the ideal choice for many embedded industrial applications. However, the development of application software for microcontroller- based implementations has normally been a restrictive factor. Before this work this has resulted in most process and condition monitoring systems being PC based. This research presents an intelligent and distributed monitoring system based on microcontroller technology, specifically the PIC18C452. The system uses a flexible architecture that can be adapted to the necessities of different monitoring applications. "Monitoring Modules" that can be deployed according to the application requirements were developed. Industrial networks and Internet technologies are employed to enhance communication, therefore allowing monitoring records to be made available in a remote database. The Petri-net concept is used to represent the monitoring task in such a way as to provide independence from the system's hardware and software. Extensions to the original Petri-net theory and new modelling elements, including the acquisition of analogue signals, required to support the use of this method in a microcontroller-based environment, are presented. These enhancements represent a major contribution of this research. Finally, the benefits of the system are considered by means of three application examples a simple Press Rig to illustrate the general features and use of the system, a more complicated Assembly Process Rig to show the flexibility of the modelling approach, and finally a CNC Milling Machine tool changer is used to demonstrate the system in a real manufacturing application