The Optimization of Data Acquisition, Fuel Flow, and Spark Timing Control for a Synthesis Gas-Engine-Generator System

As climate change drives the exploration into new and alternative fuels, biodiesel has emerged as a promising alternative to traditional diesel fuel. To further increase the viability of biodiesel, a unique system at the University of Kansas utilizes glycerin, the primary byproduct of biodiesel production, for power generation. This system converts glycerin into a hydrogen-rich gas (syngas) that is sent to an engine-generator system in one continuous flow process. This thesis details the implementation and troubleshooting of recent upgrades to the system, the experimental optimization of propane fuel and spark control for the engine, and directions for future research involving this setup. Chapter Two describes recent changes in the Syngas Rig including the renovation and replacement of various components to enhance the efficiency of the system and to resolve encountered issues. For instance, a recently installed water pump (Berkeley Model S39533) in the cooling system replaced the stock mechanical pump to eliminate an engine overheating issue. Moreover, additional safety measures were implemented in the fuel system in order to prevent any unintentional activation of fuel flow. All of the rig’s operating paths now require the activation of both mechanical and electric switches by wiring in a series instead of through parallel circuits. This chapter also includes troubleshooting guidelines to aid future students in utilizing the system. The third chapter discusses upgrades in pure propane operation that help by preheating the engine prior to syngas operation and establishing the baseline energy requirement for fueling the system. In addition, an upgrade to the fuel system incorporates an electric fuel valve (EFV) as a replacement for a gaseous propane carburetor, providing the ability for air-to-fuel ratio (AFR) adjustment of the engine at different generator loads. Moreover, spark timing optimization accompanies the new fuel control in order to enhance engine performance and maximize fuel economy. Additionally, in-cylinder pressure traces and associated performance parameters are reviewed and discussed in order to analyze the operation of the new EFV-based system. Finally, the fourth chapter provides a thorough discussion of the thesis efforts along with suggested directions for future research

Electricity Sector Reform: Sourcing and Cost Management of Electricity for Steel Manufacturing in Nigeria

In 2014, Lazard levelized cost of energy analysis model priced diesel powered systems at $0.225 –$0.404/KWh and a range of $0.165 –$0.242/KWh for gas-powered systems. The model gave a range of $0.28 –$0.33/kWh for diesel and a range of $0.14/kWh –$0.16/kW for gas fired. Nigeria has an abundance of gas reserves, but heavy gas flaring by oil companies perpetuates power failure across Nigeria. What has resulted is an unreliable electricity infrastructure and a high cost of alternative energy. The Electricity Power Sector Reform Act of 2005 started the reform process. Guided by decision theory, the purpose of this multiple case study was to understand the perceptions of business leaders at the steel manufacturing businesses on how the use of multiple supply sources of electricity might lead to survival, growth, and profitability. The study’s population consisted of 10 steel manufacturing companies in the Southwest region of Nigeria. The data were collected via semistructured interviews with the leaders who source energy, a review of archival records, and observations of company officials placing orders from multiple sources. The van Kaam method of data analysis generated 5 themes: cost of generating electricity and the investment in alternative sources of energy, erratic power supply and its impact on the steel production industry, quality of power supply relative to the capacity and its impact on profits, electricity factor in the steel production process, and use of multiple sources. These findings may contribute to social change by increasing employment opportunities for members of the local community, who will have an enhanced understanding about steel and seize entrepreneurial opportunities

Entwicklung von Objekterkennungssystemen für SoC-FPGA Plattformen

Object detection is a crucial and challenging task in the field of embedded vision and robotics. Over the last 15 years, various object detection algorithms/systems (e.g., face detection, traffic sign detection) are proposed by different researchers and companies. Most of these research are either focused on improving the detection performance or devoted to boosting the detection speed, which reveals two typically employed criteria while evaluating an object detection algorithm/system: detection accuracy and execution speed. Considering these two factors and the application of object detection to the domains such as service robots and Advanced Driving Assistance System (ADAS), FPGA is a promising platform to achieve accurate object detection in real-time. Therefore, FPGA-based robust object detection systems are designed in this work. The main work of this thesis can be divided into two parts: promising algorithm obtaining and hardware design on SoC-FPGA. Firstly, representative object detection algorithms are selected, implemented, and evaluated. Thereafter, a generalized object detection framework is created. With this framework, pedestrian detection, traffic sign detection, and head detection algorithms are realized and tested. The experiments verify that promising detection results can be obtained by employing the generalized object detection framework. For the work of hardware design on FPGA, the platform of the object detection system, which consists of stereo OV7670 cameras, Xilinx Zedboard, and a monitor that can visualize the detection results, is created. After that, IP cores that correspond to each block of the framework are designed. Configurable parameters are provided by each IP core so that the IPs, especially feature calculation IP and feature scaler IP, can be correctly instanced according to the fast feature pyramid theory. Finally, by employing the designed IP cores, pedestrian detection system, traffic sign detection system, and head detection system are designed and evaluated. The on-board testing results show that real-time object (e.g., pedestrian, traffic sign, head) detection with promising accuracy can all be achieved. In addition, with the generalized object detection framework and the designed IP-toolbox, the object detection system that targets any instance of objects can be designed and implemented rapidly.Objekterkennung ist eine essenzielle und herausfordernde Aufgabe in den Forschungsgebieten der Embedded Vision und der Robotik. In den letzten 15 Jahren wurden verschiedene Objekterkennungsalgorithmen und Systeme (z.B. Gesichtserkennung) aus der Forschung sowie der Industrie präsentiert. Der Forschungsschwerpunkt liegt dabei typischerweise entweder bei der Verbesserung der Erkennungsqualität oder bei der Beschleunigung der Erkennungsgeschwindigkeit. Hieraus leiten sich direkt die Kriterien für den Einsatz von Objekterkennungsalgorithmen und Systemen ab: Erkennungsgenauigkeit und die Erkennungslatenz. Unter Berücksichtigung dieser Kriterien und dem konkreten Einsatzgebiet der Objekterkennung für Serviceroboter und ADAS haben sich FPGA Plattformen als vielversprechende Kandidaten für die Implementierung von hoch genauen Objekterkennungsalgorithmen mit strikten Echtzeitanforderungen herausgestellt. Auf Bases dessen wurden im Rahmen dieser Arbeit eine robuste Objekterkennung entwickelt. Der Fokus dieser Arbeit ist geteilt in zwei Aspekte: Identifikation und Analyse geeigneter Objekterkennungsalgorithmen und deren Implementierung in einer FPGA basierten SoC-Plattform. Zu Beginn wurden eine Reihe von repräsentativen Algorithmen ausgewählt, in einer Testumgebung implementiert und evaluiert. Darauf aufbauend wurde ein Entwicklungs-Frameworks für die Erkennung von Passanten, Verkehrszeichen sowie Kopfdetektion entwickelt und analysiert. Für die Entwicklung einer FPGA basierten Plattform wurde ein Objekterkennungssystem erstellt. Eine Sammlung aus IP-Cores, die das Entwicklungs-Framework bilden, wurden für die FPGA Plattform implementiert. Die IP-Cores bieten eine Reihe von Konfigurationsparametern für den flexiblen Einsatz von neuen Komponenten, im Besonderen IP-Cores für die Berechnung und Skalierung von Erkennungseigenschaften, basierend auf der Fast Feature Pyramid Theorie. Abschliessend wurden die entwickelten IP-Cores zur Erkennung von Passanten, Verkehrszeichen sowie die Kopfdetektion integriert und gemeinsam evaluiert. Die gesammelten Ergebnisse aus verschiedenen Testscenarios der entwickelten FPGA-Plattform zeigen, dass die Objekterkennung in Echtzeit mit vielversprechender Genauigkeit erreichbar ist. Darüber hinaus können mit dem generalisierten Objekterkennungsrahmen und der entwickelten IP-Toolbox schnell und flexibel belibige Objekterkennungssysteme entwickelt und implementiert werden

A review of modelling and analysis of morphing wings

Morphing wings have a large potential to improve the overall aircraft performances, in a way like natural flyers do. By adapting or optimising dynamically the shape to various flight conditions, there are yet many unexplored opportunities beyond current proof-of-concept demonstrations. This review discusses the most prominent examples of morphing concepts with applications to two and three-dimensional wing models. Methods and tools commonly deployed for the design and analysis of these concepts are discussed, ranging from structural to aerodynamic analyses, and from control to optimisation aspects. Throughout the review process, it became apparent that the adoption of morphing concepts for routine use on aerial vehicles is still scarce, and some reasons holding back their integration for industrial use are given. Finally, promising concepts for future use are identified

Interactive exploration of historic information via gesture recognition

Developers of interactive exhibits often struggle to �nd appropriate input devices that enable intuitive control, permitting the visitors to engage e�ectively with the content. Recently motion sensing input devices like the Microsoft Kinect or Panasonic D-Imager have become available enabling gesture based control of computer systems. These devices present an attractive input device for exhibits since the user can interact with their hands and they are not required to physically touch any part of the system. In this thesis we investigate techniques to enable the raw data coming from these types of devices to be used to control an interactive exhibit. Object recognition and tracking techniques are used to analyse the user's hand where movement and clicks are processed. To show the e�ectiveness of the techniques the gesture system is used to control an interactive system designed to inform the public about iconic buildings in the centre of Norwich, UK. We evaluate two methods of making selections in the test environment. At the time of experimentation the technologies were relatively new to the image processing environment. As a result of the research presented in this thesis, the techniques and methods used have been detailed and published [3] at the VSMM (Virtual Systems and Multimedia 2012) conference with the intention of further forwarding the area

Automatic self-calibration from self-observation and self-touch on a dual arm industrial manipulator

Přesná kalibrace je klíčový faktor určující chování robotu. Tradiční kalibrační procedury zahrnují různé formy přídavných měřicích zařízení a stávají se nepraktickými, pokud se robot nebo prostředí ve kterém je nasazen často mění. Současným trendem v automatizaci je posun od velkosériové k malosériové výrobě. Zároveň se díky pokroku v měřicí technologii stávají dostupnými pokročilé senzory, jako například kamery, RGB-D a silové senzory. Díky tomu je možné provádět automatizovanou sebekalibraci na základě redundantní informace poskytované těmito senzory. V této práci jsme využili dva prumyslové manipulátory upevněné na společné základně se silovými senzory na koncovém článku a vybavili je: (i) dvěma externími fotoaparáty upevněnými na společné základně manipulátorů, (ii) speciálními koncovými články s referenčními značkami. Po uvedení robotu do kontaktních ("sebedotykových") pozic pomocí silové zpetné vazby jsme sbírali data z obou fotoaparátů a kloubových enkodérů robotu. Použitím metod nelineární optimalizace nejmenších čtverců jsme kvantitativně porovnali výkony kinematické kalibrace pri využití různých kombinací protínajících se kinematických retězců - sebepozorování (pomocí fotoaparátu) nebo sebedotyk, kde je využito omezení dané fyzickým kontaktem.Accurate calibration is key for the performance of every robot. Traditional calibration procedures involve some form of external measuring apparatus and become impractical if the robot itself or the site where it is deployed change frequently - current trend in automation with shift from mass to small batch production. At the same time, advances in sensor technology make affordable but increasingly accurate devices such as cameras, RGB-D, and force/tactile sensors available, making it possible to perform automated selfcontained calibration relying on redundant information in these sensory streams. In this work, we employ two industrial manipulators mounted on a common base, with Force/Torque sensors at the tool and additionally equip them with: (i) two external cameras mounted on the robot base, (ii) special end-effectors with fiducial markers. Driving the robot to contact ("self-touch") configurations relying on force feedback, we collect images from the cameras as well as encoder readings. Using non-linear least squares optimization, this dataset is then used to quantitatively compare the performance of kinematic calibration by employing different combinations of intersecting kinematic chains - either through self-observation (using the cameras) or self-touch, where the physical contact constraint is exploited

Sequentially Modified Gravitational Search Algorithm for Image Enhancement

Gravitational Search Algorithm (GSA) is based on the acceleration trend feature of objects with a mass towards each other and includes many interdependent parameters. The gravitational constant among these parameters influences the speeds and positions of the agents, meaning that the search capability depends on the largescale gravitational constant. The proposed new algorithm, which was obtained with the use of two operators at different times of the call and sequentially doing works, was named as Sequentially Modified ‎ Gravitational Search Algorithm (SMGSA). SMGSA is applied to 10 basic and 6 composite benchmark functions. Each function is run 30 times and the best, mean and median values are obtained. The achieved results are compared with the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and GSA among the heuristic optimization algorithms. Between GSA and the operator for each function convergence speed, standard deviation and graphical comparisons are included. Beside this, by using the Wilcoxon signed rank test, the comparison of the averages of the data as two dependent groups of GSA and the new operators is performed. It is seen that the obtained results provided better results than the other methods. Additionally, in this study, SMGSA was applied to the transformation function among image enhancement techniques which are engineering applications. The success of this method has been increased by optimizing the parameters of the transformation function used. Effective improvement has been achieved in terms of both visual and information quality

Matching methods for semantic interoperability in Product Lifecycle Management.

Product lifecycle management (PLM) is a business strategy that enables seamless information flow in today's collaborative, but distributed product development environment. In such environment, geographically and functionally distributed teams are involved in the development process, and the teams use different software systems with different ways of representing product data. As the product development process gets bigger and complicated, product semantics also needs to be translated in addition to the syntactic information, but ISO 10303, the current industry standard, cannot successfully translate the semantics; this has led to a new approach toward semantics-based product data integration. Semantics-based integration first requires participating domains to use semantic representation of product data. Given the semantic representations, it further requires techniques to determine semantic maps across product representations that will enable semantically correct interoperability of product data, and we propose the enabling techniques in this research. In order to determine semantic maps, we propose a method - Instance-Based Concept Matching (IBCM) that detects 1-to-n maps by exploiting implicit semantics captured in the instances of product models. The use of implicit semantics adds a new dimension in the area of product development, where most of the previous research has focused on using schema or data definition that are explicitly defined. Any single matching method is not enough to determine the semantic maps across the different systems, since each method presents only one view. We propose a method - FEedback Matching Framework with Implicit Training (FEMFIT) to combine the different matching approaches using ranking Support Vector Machine. The method overcomes the need to explicitly train the algorithm before it is used, and minimizes the decision-making load on the domain expert. Finally, we propose a framework to automatically determine the translation rules to enable translation of concepts from one system to another. Even after the semantic maps are obtained, the syntax in the sending system should properly transform to the syntax in the receiving system. We use a graph search method that obtains the overall translation rule as a combination of multiple basic functions. Using such rules, data from one system can be easily translated to another system.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64796/1/yeoil_1.pd