Electrical and Computer Engineering Commons^™

Sliding Mode Control Of A Nonlinear Wave Energy Converter Model, Tania Demonte Gonzalez, Gordon Parker, Enrico Anderlini, Wayne Weaver

Michigan Tech Publications, Part 1

The most accurate wave energy converter models for heaving point absorbers include nonlinearities, which increase as resonance is achieved to maximize the energy capture. Over the power production spectrum and within the physical limits of the devices, the efficiency of wave energy converters can be enhanced by employing a control scheme that accounts for these nonlinearities. This paper proposes a sliding mode control for a heaving point absorber that includes the nonlinear effects of the dynamic and static Froude‐Krylov forces. The sliding mode controller tracks a reference velocity that matches the phase of the excitation force to ensure higher energy …

Characterization Of Anisotropic Materials Using Scattered Field Measurements, Hirsch M. Chizever

Theses and Dissertations

This research uses monostatic far-zone scattered field measurements to estimate the permittivity of biaxial materials at X-Band. Utilizing Radar Cross Section (RCS) measurement techniques, this effort examines the efficacy of whole-sample TEM illumination in the estimation of anisotropic permittivity, in contrast with traditional subsample illumination methods. The research examines the impact that dielectric supports have on measurement error and uncertainty in permittivity estimates. Following an incremental approach, the research first demonstrates successful estimation of permittivity for isotropic spheres followed by a Teflon isotropic cube. Finally, the method is applied to uniaxial and biaxial cubes whose anisotropic permittivity is validated through …

Evaluating Testing Procedures For Openflow Controller Network Re-Provisioning Time, Steven J. Jensen

Theses and Dissertations

Software-Defined Networking promises several advantages over traditional networking architectures, but has seen little adoption. Recently codified controller evaluation methodologies have seen little validation without strong statistical analysis of the results. The research developed an environment testing implementing a published Network Re-provisioning Time methodology to evaluate five OpenFlow controllers. The methodology is strong with required parameters but had issues with some edge cases. Further refinement and adding a convergence metric may close the gaps.

New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams

Theses and Dissertations

A commonality in the many applications and domains where signal processing (SP)is applied is the detection of events. Detection in SP requires the identification of the occurrence of an event, within a signal, and distinguishing the occurrence from no event. In a classical application of SP, seismologists seek to detect abnormalities in an electromagnetic (EM) signal to detect or not detect the occurrence of an earthquake, represented as an anomalous EM pulse. Since many signals are noisy, such as those produced by a seismograph, it can be challenging to distinguish a significant EM pulse from incident noise. In SP, smoothing …

Resistive Switching Properties Of Zro2 Film By Plasma-Enhanced Atomic Layer Deposition For Non-Volatile Memory Applications, Aleksey A. Sivkov, Yuan Xing, Zoe Minden, Zhigang Xiao, Kuan Yew Cheong, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

Resistive switching properties of nanoscale zirconium dioxide (ZrO₂) thin film deposited by plasma-enhanced atomic layer deposition (PE-ALD) have been investigated. A resistive memory device has been formed with a 10-nm-thick ZrO₂ film as an active switching layer sandwiched between an aluminum top electrode and a silver bottom electrode. Bipolar resistive switching characteristics were demonstrated by current–voltage measurements with a read memory window of 6.6 V, an ON/OFF current ratio of nearly 10⁵ , and a retention time of 10⁴ s. Current conduction at low resistance states follows Ohm's law while at a high-resistance state governed …

Comparative Study Of Hermitian And Non-Hermitian Topological Dielectric Photonic Crystals, Menglin L.N. Chen, Li (Lijun) Jun Jiang, Shuang Zhang, Ran Zhao, Zhihao Lan, Wei E.I. Sha

Electrical and Computer Engineering Faculty Research & Creative Works

The effects of gain and loss on the band structures of a bulk topological dielectric photonic crystal (PC) with C6v symmetry and the PC-air-PC interface are studied based on first-principal calculation. To illustrate the importance of parity-time (PT) symmetry, three systems are considered, namely the PT-symmetric, PT-asymmetric, and lossy systems. We find that the system with gain and loss distributed in a PT symmetric manner exhibits a phase transition from a PT exact phase to a PT broken phase as the strength of the gain and loss increases, while for the PT-asymmetric and lossy systems, no such phase transition occurs. …

Physical-Based Training Data Collection Approach For Data-Driven Lithium-Ion Battery State-Of-Charge Prediction, Jie Li, Will Ziehm, Jonathan W. Kimball, Robert Landers, Jonghyun Park

Electrical and Computer Engineering Faculty Research & Creative Works

Data-Driven approaches for State of Charge (SOC) prediction have been developed considerably in recent years. However, determining the appropriate training dataset is still a challenge for model development and validation due to the considerably varieties of lithium-ion batteries in terms of material, types of battery cells, and operation conditions. This work focuses on optimization of the training data set by using simple measurable data sets, which is important for the accuracy of predictions, reduction of training time, and application to online estimation. It is found that a randomly generated data set can be effectively used for the training data set, …

An Examination Of The Fuzzy Inference System On Probabilistic Roadmap Path Planning, Brandon Replogle

Master's Theses

In recent years, multi-robot systems have been widely used in many applications such as warehouse inventory tracking and automatic search and rescue operations. Probability roadmap (PRM) is a typical path planning algorithm that can determine an optimal trajectory once the robot start and goal positions are specified. However, when the number of robots in the system increases, it converges slowly and may even fail to find the solution.

In this thesis, a fuzzy inference system is proposed and combined with the probability roadmap algorithm for robot path planning. Computer simulation results in five different environments show this approach is very …

Progressive Poling Of Large Area, High R33 Electro-Optic Polymer Seo100c, Michael Maurer, Evan Gawron, Christopher Middlebrook

Michigan Tech Publications, Part 1

SEO100c, an EO-polymer, has been reported of having an r33 in excess of 100 pm/V. Experimental poling research was performed on rib waveguide modulator for device design and development. Reported is the determination of the impact that temperature and voltage have on the poling of a SEO100c waveguide device in order to maximize the r33 while avoiding damage to the device structure ensuring high yield in manufacture. The poling process is shown to have a nonlinear relationship between r33 and poling field aiding in the selection of achievable poling voltages for required r33 values. Device thermal stability is quantified and …

A Cdzntese Gamma Spectrometer Trained By Deep Convolutional Neural Network For Radioisotope Identification, Sandeep K. Chaudhuri, Joshua W. Kleppinger, Ritwik Nag, Kaushik Roy, Rojina Panta, Forest Agostinelli, Amit Sheth, Utpal N. Roy, Ralph B. James, Krishna C. Mandal

Publications

We report the implementation of a deep convolutional neural network to train a high-resolution room-temperature CdZnTeSe based gamma ray spectrometer for accurate and precise determination of gamma ray energies for radioisotope identification. The prototype learned spectrometer consists of a NI PCI 5122 fast digitizer connected to a pre-amplifier to recognize spectral features in a sequence of data. We used simulated preamplifier pulses that resemble actual data for various gamma photon energies to train a CNN on the equivalent of 90 seconds worth of data and validated it on 10 seconds worth of simulated data.

Simulation Modeling Of A Photovoltaic-Green Roof System For Energy Cost Reduction Of A Building: Texas Case Study, Sojung Kim, Burchan Aydin, Sumin Kim

Faculty Publications

This study aims at introducing a modeling and simulation approach for a green roof system which can reduce energy cost of a building exposed to high temperatures throughout the summer season. First, to understand thermal impact of a green roof system on a building surface, a field-based study has been conducted in Commerce, Texas, U.S., where the average maximum temperature in summer is 104 F (40 C). Two types of analyses were conducted: (1) comparison of temperature between different plant type via Analysis of variance (ANOVA) and (2) polynomial regression analysis to develop thermal impact estimation model based on air …

Collaborative All-Source Navigation With Integrity, Jonathon S. Gipson

Theses and Dissertations

The novel ARMAS-SOM framework fuses collaborative all-source sensor information in a resilient manner with fault detection, exclusion, and integrity solutions recognizable to a GNSS user. This framework uses a multi-filter residual monitoring approach for fault detection and exclusion and is augmented with an additional "observability" EKF sub-layer for resilience. We monitor the a posteriori state covariances in this sub-layer to provide intrinsic awareness when navigation state observability assumptions required for integrity are in danger. This is used to selectively augment the framework with offboard information to preserve resilience. By maintaining split parallel collaborative and proprioceptive estimation instances and employing a …

Wireless Power Receiver With Tripler Circuit, Boost Converter And Supercapacitor, Bradley Clayton

Symposium of Student Scholars

This presentation lays out the groundwork, advancements, and results of a three-stage wireless power receiver with the purpose of providing power to low-power electronic equipment that operate at 5V. The receiver incorporates an impedance matching network, a tripler circuit, a boost converter, and a super capacitor. The impedance matching network has been designed for 1GHz but through testing the receiver with a signal generator followed by an antenna, it has been found that the signal frequency of 996MHz yields optimal energy capture at the tested received power levels of 0dBm, 3dBm, and 6dBm. The signal is produced from a signal …

Novel Vehicle-To-Everything Rollover Antenna, Aya Alazzawi

Symposium of Student Scholars

Rollover Vehicle-to-Everything Antenna

Poster Presentation Undergraduate Student: Aya Alazzawi

Research Mentor(s): Dr. Billy Kihei

Soft robotics is a new field of engineering ready to be explored, because of its use of unconventional materials it can withstand copious amounts of stress which makes it ideal for applications involving vehicular accidents. In this groundbreaking work, we attempt to integrate soft robotics technologies with Vehicle-to-Everything (V2X) communications. Specifically, we introduce the preliminary planning stages for creating a novel V2X rollover antenna that can reduce road deaths and provide more reliable accident data. An up-right roof-mounted antenna could be damaged during a roll-over accident …

Pulmon-C: A Real-Time Monitoring Framework Of Pulmonary Function, Md Saiful Islam, Maria Valero, Shahriar Hossain

Symposium of Student Scholars

This project will develop PulMon-C, a real-time monitoring framework of pulmonary function to diagnose COVID-19 patients who are being self-quarantined at home. The tool will identify anomalies in breathe rate and predict pulmonary deterioration to raise alert for immediate actions. The uniqueness of the tool is using non-invasive sensors placed under-mattress that are able to communicate data about the respiratory signal. The customer segment of PulMon-C will be the diagnosed COVID-19 patients and healthcare providers. PulMon-C will assist with the remote monitoring of COVID-19 patients as an urgent need in the USA and will bring larger impact in delivering …

Oral Minimal Model For Gestational Diabetes, Sarah Peters

Symposium of Student Scholars

Gestational diabetes is one of the most common issues that a pregnant woman encounters that could result in harm to both the woman and child. Due to this issue, the woman’s glucose and insulin levels should be carefully monitored throughout her pregnancy to assess the need for prescribed diabetic medication to help regulate those levels. In this research, the objectives is to develop a MATLAB computer program of the Oral Minimal Model, which is a model that can be used to estimate a person’s insulin sensitivity from an oral glucose tolerance test (OGTT) where plasma glucose and insulin levels are …

Source Localization Of Electroencephalogram (Eeg) Waves With Convolutional Neural Network, Terence Onyewuenyi

Symposium of Student Scholars

This paper investigates the use of deep learning as a means for quantification and source localization of prioritizing electroencephalogram (EEG) waves for the purpose of detecting different eye states of human subjects. The Convolutional Deep Learning tool is trained to recognize EEG reading corresponding to a set of different eye movements as generated by watching different action scenes. The results also predict whether the subjects' eyes are open or closed. Source localization is performed next on the EEG data to focus on the different EEG components which primarily contribute to the activity. This was done by using a convolutional neural …

Colloidal Quantum Dot (Cqd) Based Mid-Wavelength Infrared Optoelectronics, Shihab Bin Hafiz

Dissertations

Colloidal quantum dot (CQD) photodetectors are a rapidly emerging technology with a potential to significantly impact today’s infrared sensing and imaging technologies. To date, CQD photodetector research is primarily focused on lead-chalcogenide semiconductor CQDs which have spectral response fundamentally limited by the bulk bandgap of the constituent material, confining their applications to near-infrared (NIR, 0.7-1.0 um) and short-wavelength infrared (SWIR, 1-2.5 um) spectral regions. The overall goal of this dissertation is to investigate a new generation of CQD materials and devices that advances the current CQD photodetector research toward the technologically important thermal infrared region of 3-5 ?m, known as …

Learning Of Radar System For Target Detection, Wei Jiang

Dissertations

In this dissertation, the problem of data-driven joint design of transmitted waveform and detector in a radar system is addressed. Two novel learning-based approaches to waveform and detector design are proposed based on end-to-end training of the radar system. The first approach consists of alternating supervised training of the detector for a fixed waveform and reinforcement learning of the transmitter for a fixed detector. In the second approach, the transmitter and detector are trained simultaneously. Various operational waveform constraints, such as peak-to-average-power ratio (PAR) and spectral compatibility, are incorporated into the design. Unlike traditional radar design methods that rely on …

Application Of Artificial Neural Networks To Power System State Estimation, James P. Carmichael, Yuan Liao

Electrical and Computer Engineering Presentations

State estimation function is essential for effective and timely execution of power system automation and control systems, especially in modern active distribution systems where more intermittent renewable energy systems are integrated into the grid. Distribution system state estimation faces a lot of challenges including lack of monitoring devices and possible incorrect topology information. Developing efficient state estimation for distribution systems is thus of great interest. This paper presents results on utilizing artificial neural networks for this purpose.

Artificial neural networks have been used in power distribution system state estimation. However, there is a lack of systematic analysis and study of …

Role Of Protective Relaying In The Smart Grid, J. Anderson, Alex Apostolov, R. Fowler, J. Gers, R. Kazimier, S. Klecker, Yuan Liao, M. Majidi, P. Myrda, T. Raffield

Electrical and Computer Engineering Presentations

This paper discusses the role of protective relaying in a Smart Grid. It outlines the definition, attributes, and benefits of a Smart Grid. The role that protective relays can play in implementing Smart Grid functionality and the impact that a Smart Grid design may have on modern protective relays is discussed. Specific examples of Smart Grid applications that may be implemented using modern protective relays and other intelligent electronic devices are provided.

Geomagnetic Disturbances (Gmd) Impacts On Protection Systems, Qun Qiu, V. Madani, Tapan Manna, T. Raffield, S. Klecker, Yuan Liao, S. Meliopoulos, D. Fontana

Electrical and Computer Engineering Presentations

This paper provides background and historical events of Geomagnetic Disturbances (GMD), and reviews GMD impacts on power systems equipment, and associated protection and control systems, mitigating measures, and Geomagnetic Induced Current (GIC) monitoring methods. This paper is a summary of the IEEE PES-TR72 report, titled, GMD Impacts on Protection Systems, prepared by the K17 Working Group of the IEEE Power System Relaying and Control committee.

Zip Load Modeling For Single And Aggregate Loads And Cvr Factor Estimation, Yiqi Zhang, Yuan Liao, Evan S. Jones, Nicholas Jewell, Dan M. Ionel

Electrical and Computer Engineering Presentations

ZIP load modeling has been used in various power system applications. The aggregate load modeling is common practice in utility companies. However, little research has been done on the theoretical formulation of the aggregate load. This paper formulates the aggregate ZIP load model using the single ZIP load model. The factors that may affect aggregate ZIP load estimation are studied. Common ZIP parameter estimation methods including least squares method, optimization method and neural network method have been used in this paper to estimate ZIP parameters. The case studies are based on the IEEE 13-bus and 34-bus system built in OpenDSS. …

An Integrated Model Of Optofluidic Biosensor Function And Performance, Joel Greig Wright, Jr.

Theses and Dissertations

Optofluidic flow-through biosensor devices have been in development for fast bio-target detection. Utilizing the fabrication processes developed by the microelectronics industry, these biosensors can be fabricated into lab-on-a-chip devices with a degree of platform portability. This biosensor technology can be used to detect a variety of targets, and is particularly useful for the detection single molecules and nucleic acid strands. Microfabrication also offers the possibility of production at scale, and this will offer a fast detection method for a range of applications with promising economic viability. The development of this technology has advanced to now warrant a descriptive model that …

Electrical Property Of Polypropylene Films Subjected To Different Temperatures And Dc Electric Fields, Huseyin R. Hiziroglu, Chuyan Zhang, Weichen Shi, Qiao Wang, Mingguang Diao

Electrical & Computer Engineering Publications

A polypropylene (PP) film is usually used as a dielectric material in capacitors as well as cables. However, PP films may degrade because of the combined effect of temperature and electric field. In an earlier study, plain PP films and PP films loaded with nano-metric natural clay were studied under sinusoidal (AC) electric fields at power frequency and temperatures above the ambient. To better understand the electrical characteristics of PP film under various conditions, the objective of this study is to determine the time-to-breakdown of the plain PP and PP filled with 2% (wt) natural nano-clay when subjected to time-invariant …

Maintenance Automation Architecture And Electrical Equipment Fault Prediction Method In Tanzania Secondary Distribution Networks, Hadija Mbembati, Kwame Ibwe, Baraka Maiseli

Tanzania Journal of Science

Distribution networks remain the most maintenance-intensive parts of power systems. The implementation of maintenance automation and prediction of equipment fault can enhance system reliability while reducing the overall costs. In Tanzania, however, maintenance automation has not been deployed in secondary distribution networks (SDNs). Instead, traditional methods are used for condition prediction and fault identification of power assets (transformers and power lines). These (manual) methods are costly and time-consuming, and may introduce human-related errors. Motivated by these challenges, this work introduces maintenance automation into the network architecture by implementing effective maintenance and fault identification methods. The proposed method adopts machine learning …

Analysis And Performance Evaluation Of Entropic Thresholding Image Processing Techniques For Electrical Capacitance Tomography Measurement System, Josiah Nombo, Alfred Mwambela, Michael Kisangiri

Tanzania Journal of Science

To improve image quality generated from the electrical capacitance tomography measurement system, the use of entropic thresholding techniques is investigated in this article. Based on the analysis of the principle of Electrical Capacitance Tomography (ECT) image reconstruction and entropic thresholding, various algorithms have been proposed for easy extraction of quantitative information from tomograms generated from the ECT system. Experiments indicate that proposed algorithms can provide high-quality images at no or minimum computational cost. It is easier to implement and integrate with classical algorithms such as Linear Back Projection, Singular value decomposition, Tikhonov regularization, and Landweber. Entropic thresholding techniques present a …

Multi-Operator Cell Tower Locations Prediction From Crowdsourced Data, Mostafizur Rahman, Mohammad Arif Hossain, Murat Yuksel

Electrical and Computer Engineering Faculty Publications

Cell tower locations are not publicly available due to business interests of wireless providers. Very often wireless providers provide exaggerated coverage maps that may mislead the public. In addition to providing a neutral check on the coverage maps, prediction of cell tower locations hosting multiple operators’ access nodes could also be helpful in disaster communications and public safety in general. The localization of the disaster-affected towers can be very conducive to respond and reach to the victims. Further, victims’ devices could utilize this knowledge to initiate device-to-device (D2D) or unmanned aerial vehicular (UAV) communications as alternatives to the damaged cellular …

A Compact 1200 V, 700 A, Igbt-Based Pulse Generator For Repetitive Transcranial Magnetic Stimulation In Vivo Laboratory Experiments On Small Animals, Daniel Senda, Haley Strong, Dustin Hines, Rochelle Hines, R. Jacob Baker

Psychology Faculty Research

An insulated-gate bipolar transistor (IGBT) pulse generator for repetitive transcranial magnetic stimulation used for in vivo laboratory experiments on small animals, such as mice, is reported. The pulse generator is based upon an IGBT that can switch 700 A of current for 1 ms and that has a DC breakdown voltage of 1200 V. The duration of the design’s output pulse is controlled by, and follows, an input trigger pulse. The voltage amplitude of the output pulses is determined by an external high-voltage power supply and the energy stored in a 330 µF capacitor bank. The approach enables the amplitude …

Designing A Computer-Vision Application: A Case Study For Hand-Hygiene Assessment In An Open-Room Environment, Chengzang Zhong, Amy R. Reibman, Hansel A. Mina, Amanda J. Deering

Department of Food Science Faculty Publications

Hand-hygiene is a critical component for safe food handling. In this paper, we apply an iterative engineering process to design a hand-hygiene action detection system to improve food- handling safety. We demonstrate the feasibility of a baseline RGB-only convolutional neural network (CNN) in the restricted case of a single scenario; however, since this baseline system performs poorly across scenarios, we also demonstrate the application of two methods to explore potential reasons for its poor performance. This leads to the development of our hierarchical system that incorporates a variety of modalities (RGB, optical flow, hand masks, and human skeleton joints) for …