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- <p>Locks (Hydraulic engineering) -- Maintenance and repair.</p> <p>Locks (Hydraulic engineering) -- Electric equipment.</p> <p>Engineering<strong> -- </strong>Management.</p> (1)
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Articles 1 - 7 of 7
Full-Text Articles in Electrical and Electronics
Advanced Analytics In Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms And Parallel Machine Scheduling Using A Genetic Algorithm, Meiling He
Theses and Dissertations
Industry 4.0 offers great opportunities to utilize advanced data processing tools by generating Big Data from a more connected and efficient data collection system. Making good use of data processing technologies, such as machine learning and optimization algorithms, will significantly contribute to better quality control, automation, and job scheduling in Smart Manufacturing. This research aims to develop a new machine learning algorithm for solving highly imbalanced data processing problems, implement both supervised and unsupervised machine learning auto-selection frameworks for detecting anomalies in smart manufacturing, and develop a genetic algorithm for optimizing job schedules on unrelated parallel machines. This research also …
Development Of Metaheuristic Algorithms For The Efficient Allocation Of Power Flow Control Devices, Eduardo Jose Castillo Fatule
Development Of Metaheuristic Algorithms For The Efficient Allocation Of Power Flow Control Devices, Eduardo Jose Castillo Fatule
Open Access Theses & Dissertations
Modern energy grids have become extremely complex systems, requiring more variable and active flow control. As a remedy to this, Distributed Flexible AC Transmission Systems (D-FACTS) are cost-efficient devices used to mitigate power flow congestion and integrate renewable energies. The objective of this research is then to propose an efficient multiple objective evolutionary algorithm to solve a stochastic model for D-FACTS allocation, which aims to optimize various objectives related to cost, grid health, and environmental impacts. The model was implemented on a modified RTS-96 test system, and the results show that optimally allocating D-FACTS modules using the proposed model can …
Algebraic, Computational, And Data-Driven Methods For Control-Theoretic Analysis And Learning Of Ensemble Systems, Wei Miao
McKelvey School of Engineering Theses & Dissertations
In this thesis, we study a class of problems involving a population of dynamical systems under a common control signal, namely, ensemble systems, through both control-theoretic and data-driven perspectives. These problems are stemmed from the growing need to understand and manipulate large collections of dynamical systems in emerging scientific areas such as quantum control, neuroscience, and magnetic resonance imaging. We examine fundamental control-theoretic properties such as ensemble controllability of ensemble systems and ensemble reachability of ensemble states, and propose ensemble control design approaches to devise control signals that steer ensemble systems to desired profiles. We show that these control-theoretic properties …
Elucidating And Leveraging Dynamics-Function Relationships In Neural Circuits Through Modeling And Optimal Control, Sruti Mallik
Elucidating And Leveraging Dynamics-Function Relationships In Neural Circuits Through Modeling And Optimal Control, Sruti Mallik
McKelvey School of Engineering Theses & Dissertations
A fundamental research question in neuroscience pertains to understanding how neural networks through their activity encode and decode information. In this research, we build on methods from theoretical domains such as control theory, dynamical systems analysis and reinforcement learning to investigate such questions. Our objective is two-fold: first, to use methods from engineering to identify specific objectives that neural circuits might be optimizing through their spatiotemporal activity patterns, and second, to draw motivation from neuroscience to formulate new engineering principles such as synthesis of dynamical networks for decentralized control applications. We specifically take a top-down, optimization driven approach in our …
Efficiently Estimating Survival Signature And Two-Terminal Reliability Of Heterogeneous Networks Through Multi-Objective Optimization, Daniel Bruno Lopes Da Silva
Efficiently Estimating Survival Signature And Two-Terminal Reliability Of Heterogeneous Networks Through Multi-Objective Optimization, Daniel Bruno Lopes Da Silva
Graduate Theses and Dissertations
The two-terminal reliability problem is a classical reliability problem with applications in wired and wireless communication networks, electronic circuit design, computer networks, and electrical power distribution, among other systems. However, the two-terminal reliability problem is among the hardest combinatorial problems and is intractable for large, complex networks. Several exact methods to solve the two-terminal reliability problem have been proposed since the 1960s, but they have exponential time complexity in general. Hence, practical studies involving large network-type systems resort to approximation methods to estimate the system's reliability. One attractive approach for quantifying the reliability of complex systems is to use signatures, …
Asset Management Framework For The United States Army Corps Of Engineers Lock And Dam Electrical Equipment, Megan Elizabeth Bates
Asset Management Framework For The United States Army Corps Of Engineers Lock And Dam Electrical Equipment, Megan Elizabeth Bates
Theses, Dissertations and Capstones
The focus of this thesis is to design an efficient and effective preventative maintenance program for the electrical equipment that the United States Army Corps of Engineers (USACE) operates at the locks and dams. This thesis presents the concept of asset management and designs a framework to manage the electrical assets at USACE. The methodology was tested, and the results validated the framework proposed in this thesis. The framework was tested on two separate projects and the results were the same optimized strategies, which shows that the framework is robust and can be implemented into each project and can give …
Quality Assurance Of Lightweight Structures Via Phase-Based Motion Estimation, Ikenna E. Ifekaonwu
Quality Assurance Of Lightweight Structures Via Phase-Based Motion Estimation, Ikenna E. Ifekaonwu
Electronic Theses and Dissertations
In recent years, lightweight structures have become mature and adopted in various applications. The importance of quality assurance cannot be overemphasized hence extensive research has been conducted to assess the quality of lightweight structures. This study investigates a novel process that exploits motion magnification to investigate the damage characteristics of lightweight mission-critical parts. The goal is to assure the structural integrity of 3D printed structures and composite structures by determining the inherent defects present in the part by exploiting their vibration characteristics. The minuscule vibration of the structure was recorded with the aid of a high-speed digital camera, and the …