Browsing by Author "Negash Medhin, Committee Member"

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Active Incipient Fault Detection With Multiple Simultaneous Faults.
(2010-10-20) Fair, Martene; Stephen Campbell, Committee Chair; Ernest Stitzinger, Committee Member; Negash Medhin, Committee Member; Robert White, Committee Member
Acute Inflammatory Response to Endotoxin Challenge: Model Development, Parameter Estimation, and Treatment Control.
(2010-08-03) Frank, Dennis; Hien Tran, Committee Chair; Stephen Campbell, Committee Member; Negash Medhin, Committee Member; John Franke, Committee Member
Auxiliary Signal Design for Fault Detection for Nonlinear Systems: Direct Approach
(2008-05-06) Andjelkovic, Ivan V.; Negash Medhin, Committee Member; Pierre A. Gremaud, Committee Member; Stephen L. Campbell, Committee Chair; Ralph Smith, Committee Member
The main task of active fault detection is to design an auxiliary signal which acting on the system will reveal to the observer a potential fault of the system. There are numerous results that implement techniques of optimal control to calculate an auxiliary signal. However, the techniques and methods are almost exclusively designed for linear systems, while nonlinear systems are treated through linearization. In this thesis, we are providing a novel way of directly approaching nonlinear systems. We will start with a brief overview of the areas of the fault detection, optimal control, basic terminology and principles of active fault detection and previous research. Then we will present the novel p-norm approach enabling us to solve nonlinear problems directly using optimization. We will develop a direct optimization formulation for active fault detection for linear and nonlinear systems with additive uncertainty. We will present some test examples and point out the advantages and disadvantages of our new p-norm approach. Several illustrative examples will be presented and analyzed for a deeper understanding of underlying problems involved with nonlinear systems. We are hoping that this thesis will give guidelines for future users and researchers of how to approach active fault detection on nonlinear systems. Linear systems with model uncertainty have already been analyzed using the Riccati equations. Here we will develop a direct optimization formulation. After some test examples, we will solve several types of problems that cannot be solved using the Riccati approach, namely problems that contain additional constraints (soft or hard) on states of the system or on auxiliary signals. The quality of an auxiliary signal is usually measured by some cost function. We will examine the influence of several cost functions on our auxiliary signal design.
Auxiliary Signal Design for Fault Detection in Nonlinear Systems
(2008-04-03) Sweetingham, Kelly Ann; Stephen L. Campbell, Committee Chair; Negash Medhin, Committee Member; Ralph Smith, Committee Member; Hien Tran, Committee Member
Recently, research has developed in the area of active fault detection and model identification algorithms for linear systems. These algorithms compute an auxiliary input signal which guarantees fault detection, assuming a bounded noise. This dissertation addresses the question of when the previous linear theory can be applied to nonlinear systems. Several case studies are presented to verify that linearizations can in fact produce results in the nonlinear case. Two results are proven about the use of linearizations. The first result gives a parameter which scales the entire problem. Using this parameter, the scaled auxiliary signal, along with a scaled noise bound, will guarantee fault detection in the nonlinear problem. The second result shows how to compute the acceptable noise bound for the nonlinear problem using the exact auxiliary signal from the linearized problem. Also presented is a computational study to verify these two results. Two secondary projects are also presented in this dissertation. The first is a comparison of two different linear algorithms used to compute the optimal auxiliary signal. The second is a port of one of the existing pieces of fault detection software into Matlab. This new software is included, as well as a discuss of the complications of the port.
Digital Signal Design for Fault Detection in Linear Continuous Dynamical Systems
(2007-04-11) Choe, Dongkyoung; Yahya Fathi, Committee Member; Negash Medhin, Committee Member; Stephen L. Campbell, Committee Chair; Robert Buche, Committee Member
A systematic approach to detect underlying undesirable states of a physical system is to compare its observed behaviors to several competing models and to identify the model that best describes the observation. This model selection process can be enhanced by applying a specially designed auxiliary input signal to the system. This dissertation applies the auxiliary-signal-based model selection approach for recognizing faulty behaviors of systems whose dynamic behaviors can be described by linear differential equations. Using an existing analog--signal--based algorithm, the effect of the modeling error on this particular type of detection approach is examined and a geometrical explanation is provided. We also present a variation of the analog--signal--based algorithm which produces signals that are more practical for certain types of applications. In addition, an alternative auxiliary signal design algorithm is developed, producing digital signals that minimally disturb regular system operation and guarantee fault detection for a given amount of the gap between physical system and the corresponding model. The algorithm implements the analytical solution steps derived mostly by the optimal control problem solution technique while converting a nested optimization problem into an equivalent eigenvalue problem. The algorithm provides an option to optimize the duration of each digital piece to yield even more Steel material is widely used in fabricating automotive seat frames. Unfortunately, these materials are not renewable and take a somewhat longer time to degrade in a landfill than natural based biodegradable materials. Unprecedented growth of bio-based textile composites has drawn interest from various industries, such as automotive and transportation. Bio-based composite materials offer products that are biodegradable, easily recycled and can exceed the physical performance of metallic materials that are commercially available. Additional performance characteristics that composite materials can offer include weight reduction and strength improvement. The purpose of this research is to investigate the physical and mechanical properties of bio-based composite materials incorporating different linear densities of the flax sliver and blend ratios of Epoxy-soybean oil resin. Sliver is defined as a "continuous bundle of loosely untwisted fibers" [46]. The proposed fabrication concept is the impregnation of soybean-Epoxy resin into flax sliver. After resin impregnation of the flax sliver and curing it with the curing agent, the flax sliver — resin mixtures become rigid and support an increase in fiber loading. The resin consolidation method with sliver form is also called Sliver Polymer Matrix Composite (SPMC). One of the potential applications for the particular bio-based composite is automotive seat frames. The properties provided by SPMC, strength, weight reduction and biodegradability, are important to this final product. Three different bundle sizes of flax sliver were used, namely 8, 9 and 10 ply flax sliver. Each of the flax slivers has individual linear density of 253.41 grains⁄yard. Thus plied sliver bundles had linear densities of 2027.3, 2280.7 and 2534 grains⁄yard respectively. Moreover, three blend ratios of Epoxy and Acrylated Epoxidized Soybean Oil (AESO) are also taken into consideration as another variable, namely 100% Epoxy resin, 30% AESO ⁄ 70% Epoxy resin, and 50% AESO ⁄ 50% Epoxy resin. This research analyzes the mechanical and physical properties of the rigid bio-based composite materials employing flax fibers. Physical testing was performed to determine the flexural rigidity (three-point bend), impact strength and biodegradability at varying sliver linear densities and Epoxy-soybean resin blend ratios. Flexural rigidity test utilized 9" x 1" (Length x diameter) samples, impact strength test utilized 3" x 1" (Length x diameter). The highest impact test value was achieved with samples of 10 ply flax sliver and 50% Epoxy ⁄ 50% AESO resin mixture. The impact test value for this particular sample was 57 ft-lb. The highest flexural rigidity test value was also achieved with samples of 10 ply of flax sliver with 50% ⁄ 50% Epoxy-AESO resin mixtures. The average flexural rigidity of this sample was 612.74 lbs. (278.5 kg). The algorithm provides an option to optimize the duration of each digital piece to yield even more "plant-friendly" auxiliary detection signals at the cost of a moderate increase in computational time.
Financial Risk Management: Portfolio Optimization.
(2011-02-18) Yang, Song; Tao Pang, Committee Chair; Negash Medhin, Committee Member; Peter Bloomfield, Committee Member; Min Kang, Committee Member
Modeling Shear Wave Propagation in Biotissue: An Internal Variable Approach to Dissipation
(2006-08-07) Luke, Nicholas Stephen; H.T. Banks, Committee Chair; Negash Medhin, Committee Member; Hien Tran, Committee Member; Mansoor Haider, Committee Member
The ability to reliably detech artery disease based on the acoustic noises produced by a stenosis can provide a simple, non-invasive technique for diagnosis. Current research exploits the shear wave fields in body tissue to detect and analyze coronary stenoses. A mathematical model of this system, utilizing an internal strain variable approximation to the quasi-linear viscoelastic constitutive equation proposed by Fung, was previously presented. The methods an ideas outlined in that presentation are expanded upon in this work. As an initial investigation, a homogeneous two-dimensional viscoelastic geometry is considered. Being uniform in theta, this geometry behaves as a one dimensional model, and the results generated from it are compared to the one dimensional results. Several variations of the model are considered, to allow for different assumptions about the elastic response. A statistical significance test is employed to determine if the extra parameters needed for certain variations of the model are necessary in modeling efforts. After validating the model with the comparison to previous findings, more complicated geometries are developed. Simulations involving a heterogeneous geometry with a uniform ring running through the originam medium, a theta dependent model which considers a rigid occlusion formed along the inner radius of the geometry, and a model which combines the ring and occlusion are presented. In an attempt to move towards the ultimate goal of detecting the location of a stenosis from the data gathered at the chestwall, an inverse problem methodology is introduced and results from the inverse problem are shown.
Time Optimal and Minimum Effort Control of Time-invariant Systems.
(2010-10-29) Grover, Amandeep; Kazufumi Ito, Committee Chair; Zhilin Li, Committee Member; Negash Medhin, Committee Member