Digital Commons Network^™

Detecting Electrical Submersible Pump (Esp) Failures And Estimating Run Life Using Artificial Neural Networks, Mostafa Ahmed Sobhy

Theses and Dissertations

Electric Submersible Pumps (ESPs) are one of the important artificial lift methods for sustaining production in mature and high-water-cut wells; but may suffer frequent failures due to mechanical, electrical, hydraulic, chemical, and operational failures. These failures can yield substantial deferred production and intervention costs. Plenty of ESP installations are fitted with downhole sensors. Yet, it is observed that the current industry practice underutilizes the wealth of available sensor and operational data and lacks standardized, explainable failure-type identification and classification.

In this thesis, a comprehensive Machine Learning (ML) and Deep Learning (DL) framework was introduced for ESPs that simultaneously estimates remaining …

Application Of Neural Networks For Intelligent Processing Of Sensor Signals In The Control Of Technological Process Parameters, N.R. Yusupbekov, Yu.Sh. Avazov, G.Kh. Rashidov

Chemical Technology, Control and Management

This scientific article investigates the problem of analyzing technological process parameters in the fields of chemistry, energy, and metallurgy based on sensor data and applying intelligent signal processing methods. The main objective is to evaluate the effectiveness of artificial intelligence and deep learning models for intelligent analysis, forecasting, and anomaly detection of data obtained from sensors. Time-series data collected from industrial sensors were analyzed using LSTM (Long Short-Term Memory) and Autoencoder neural networks, as well as the Kalman filter. At the first stage of the study, sensor signals were denoised and their true state was estimated using the Kalman filter. …

Algorithms For The Synthesis Of Adaptive Control Systems Based On The Speed-Gradient Method, Oxunjon Boborayimov

Chemical Technology, Control and Management

This paper discusses the synthesis algorithms for adaptive control systems based on the speed-gradient method. Adaptive control systems with implicit reference and adjustable models are synthesized using speed-gradient techniques, which reduce the requirements for the main control loop structure and the completeness of measurement data. Stable adaptive decentralized control algorithms are developed for a class of interconnected systems with nonlinear local dynamics and uncertainties, ensuring the stability of individual subsystems and the overall system while accounting for their interactions. To incorporate inter-subsystem interactions into the overall control law, an adaptation algorithm based on the speed-gradient method is introduced. A synthesis …

Finding The Shortest And Optimal Path With Metaheuristic And Madm Methods, Narmin Ibrahim Hasanli

Chemical Technology, Control and Management

The article had described a method for finding the shortest and most optimal path among cities. The data had been taken from the TSPLIB library, which had provided standard examples for the Traveling Salesman Problem. This approach had integrated the advantages of the meta-heuristic technique and the Multi Attribute Decision Making method to solve the problem effectively. In the first stage, the population based meta-heuristic method ACO (Ant Colony Optimization) had found optimal solutions in large search spaces. The use of pheromone trails, heuristic information and an iterative search process had given the opportunity to find the best or near-best …

Modeling Of Urea Drying And Granulation Process In Fluidized Bed, Jalolitdin Pakhritdinovich Mukhitdinov, Aleksey Viktorovich Schulz

Chemical Technology, Control and Management

This article is devoted to the mathematical modeling of urea drying and granulation processes in a fluidized bed. A brief description is provided for the functional blocks included in the mathematical model, along with the required parameters that form an integrated representation of the technological process. The SR-POLAR model is used to describe a phase equilibrium between the components involved. The interconnections between functional blocks are shown in the process flow diagram. Block diagrams for modeling a multi-chamber granulation unit and the cooling system for the resulting granules are presented. Granule growth in the fluidized bed is described using a …

Research And Development Of Intelligent Measurement Systems, Odil Abdujalilovich Jumaev, Mahmudov Giyosjon Baqoyevich

Chemical Technology, Control and Management

The article discusses modern methods for developing intelligent measuring systems. Intelligent measuring systems are systems based on intelligent technologies that not only accurately measure physical or chemical quantities, but also have the ability to self-analyze, diagnose and make management decisions. The article comprehensively examines the architecture, components of such systems, the organization of their software and hardware, the relationship of sensors and artificial intelligence algorithms. It also analyzes the practical application and prospects of intelligent measuring systems in such areas as industry, medicine, energy, ecology, transport.

Synthesis Of A Control System For Thermal Energy Facilities Using The Quantum Photon Spin Method, Isomiddin Siddikov, N.S Yakubova

Chemical Technology, Control and Management

Increasing energy efficiency and reducing fuel consumption in the process of generating electricity and heat at thermal power plants is one of the urgent tasks. Such systems operate under conditions of random changes in external and internal influences, as well as measurement uncertainties, which reduce the quality of control. In order to overcome this problem, it was proposed to develop an intelligent control system using the quantum photon-spin method to control technological units of thermal power plants. In the proposed approach, a multi-dimensional heating boiler device was taken as a control object, and the simulation modeling of the control system …

Clinic Vs. Daily Life Gait Characteristics In Patients With Spinocerebellar Ataxia, Vrutangkumar V. Shah, Daniel Muzyka, Adam Jagodinsky, Hannah Casey, James Mcnames, Mahmoud El-Gohary, Kristen Sowalsky, Delaram Safarpour, Patricia Carlson-Kuhta, Fay B. Horak, Christopher M. Gomez

Electrical and Computer Engineering Faculty Publications and Presentations

Background:

Recent findings suggest that a single gait assessment in a clinic may not reflect everyday mobility.ObjectiveWe compared gait measures that best differentiated individuals with spinocerebellar ataxia (SCA) from age-matched healthy controls (HC) during a supervised gait test in the clinic vs. a week of unsupervised gait during daily life.

Methods: Twenty-six individuals with SCA types 1, 2, 3, and 6, and 13 (HC) wore three Opal inertial sensors (on both feet and lower back) during a 2-minute walk in the clinic and for seven days in daily life. Seventeen gait measures were analyzed to investigate the group differences using …

A Pilot Study On Tissue Deformation Using An Integrated Sensor–Actuator Blood Collection Setup In Aquaculture (Salmo Salar), Ishrak Siddiquee, Md Ebne Al Ashad, Ahmed Hasnain Jalal

Electrical and Computer Engineering Faculty Publications

This pilot study presents a sensor–actuator setup designed to evaluate tissue deformation in Atlantic Salmon (Salmo salar) during needle insertion. The system integrates three types of low-cost, commercially available force sensors to capture force profiles and identify biomechanical events associated with tissue layer transitions. Controlled insertions were performed on a deceased specimen, and the resulting force data were analyzed to quantify insertion dynamics and estimate tissue deformation. A simulation model based on the recorded force values was developed to calculate stress distribution and deformation, which ranged from 0.001 µm to 8.4 µm and from 0.3 N/m2 to 4.9 N/m2, respectively. …

Optimizing Object Detection For Remote Monitoring With Owl Ducklink Radios, Colin Ren-Jin Babian

Electrical Engineering

This project develops an AI powered object detection system integrated with OWL DuckLink radios to enable real time remote monitoring. The system benchmarks multiple AI accelerators using a Raspberry Pi 5 to determine their efficiency in low power, long range communication environments. By evaluating the Raspberry Pi 5 CPU (7.62W, 14.5 camera FPS, 3.8 inference FPS), Raspberry Pi AI Camera with Sony IMX500 (6.45W, 30 camera FPS, 9.2 inference FPS), and Raspberry Pi AI Hat with Hailo-8L chipset (7.80W, 30 camera FPS, >30 inference FPS), this project identifies the most effective combination of hardware and software for edge AI applications. …

Restoration Of 6-Axis Industrial-Grade Robotic Arms, Bryce Andrew Paulson, Warren Douglas Howard

Electrical Engineering

The Staubli TX60 and TX60CR are industrial-grade, six-axis robotic arms originally designed to perform complex automation tasks in manufacturing environments. Following their retirement from active industrial use, both units were restored to full operational status. As part of this project, they were reprogrammed to execute a pick-and-place routine using kids shape-sorting toys that mirrors typical workflows found in factory settings. The six degrees of freedom afforded by each robot enable a wide range of motion, making them well-suited for tasks such as material handling, product sorting, and repetitive operations typically carried out by human workers. Each model is equipped with …

Shared Power, Shared Future: Navigating Technology, Ownership, And Equity In Community Battery Storage, Bassam Al-Hanahi, Nishadi Mudiyanselage, Asma Aziz

Research outputs 2022 to 2026

Community Battery Storage Systems (CBS) are gaining traction as a shared energy solution to support the growing integration of rooftop solar and electric vehicles. Operating at the neighborhood scale, CBS offers benefits such as grid flexibility, enhanced self-consumption, and cost optimization. This review provides a multidimensional synthesis of CBS developments, examining technical design, ownership structures, regulatory conditions, and community engagement. By analyzing pilot projects and demonstration trials, the paper identifies recurring challenges – including inconsistent tariff structures, limited financial viability, and unclear market roles – that constrain scalability. It also highlights emerging strategies such as Local Use of Service (LUoS) …

Multi-Modal Depth Estimation Using Camera And Mmwave Sensors, Alston D. Devero-Belfon

Student Theses

For accurately estimating the depth of environments with varying lighting conditions, reliable methods are limited. By utilizing wireless sensor technology in conjunction with cameras, a wide range of environments can be visualized, and objects within these environments can be tracked and monitored. Such methods offer cost-effective alternatives and provide a more secure, data-at-rest option for individuals with low vision, while also enhancing machine perception. In this work, we develop such a prototype that utilizes wireless sensors and cameras, which act in sync, enabling us to estimate the depth of objects within varying lighting environments to a level that is recognizable …

Single-Molecule Orientation And Localization Microscopy, Sophie Brasselet, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Single-molecule localization microscopy (SMLM) offers enhanced spatial resolution in optical microscopy, providing detailed insights into the spatial organization of proteins in cells at the nanoscale. Over the past decade, SMLM has progressively incorporated the capability to retrieve the orientations of single molecules using their polarized dipolar emission pattern. Here we explore recent advancements in single-molecule orientation and localization microscopy (SMOLM), which yields super-resolved images of molecular three-dimensional (3D) orientations, wobble and 3D positions. This advancement opens possibilities to explore the nanoscale organization and conformation of biological molecules as well as to monitor and design local 3D optical fields in nanophotonics. …

Electrical Characterization Of Germanium Tin Alloys And Devices For Space Reliability, Kevin K. Choe

Theses and Dissertations

GeSn (germanium tin) alloys are potentially well suited for near-mid infrared space optoelectronic applications. Alloys of GeSn have similar properties to group III-V and mercury-cadmium-telluride semiconductors and are compatible with cost-effective complementary metal oxide semiconductor (CMOS) manufacturing technology. Recent progress in non-equilibrium remote plasma-enhanced chemical vapor deposition (RPECVD) has enabled the crystalline growth of GeSn with Sn concentrations of up to 10% without Sn surface segregation. Several experimental studies in previous literature report CVD- or molecular beam epitaxy (MBE)-grown GeSn alloys achieving a direct bandgap with 6%-9% Sn content. This novel growth technique opens opportunities for a cost-effective, next-generation optical …

Validation And Proposed Expansion Of The Data-Driven D Region Model, Kevin M. Watson

Theses and Dissertations

Predicting ionosphere effects on radio wave propagation is critical for communications and over-the-horizon radar systems. The D region is challenging to model for several reasons, one of which is chemical complexity. Ion density changes during sunrise/sunset introduce substantial uncertainty in electron density profiles (EDPs). The Data Driven D Region (D3R) model solves electron densities through an ion chemistry model and assimilates relevant space weather inputs. This study evaluates D3R against the Faraday International Reference Ionosphere (FIRI) and measurements using Very Low Frequency (VLF) propagation paths. Space weather event impacts on D3R EDPs are evaluated during the disturbed period from 8-12 …

Switching Performance Optimization Of Sic Mosfets With Digital Active Gate Drivers, Liyang Du

Graduate Theses and Dissertations

Silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFETs) have extensive applications in high-power density devices, but they exhibit quick switching transients that are problematic, including electromagnetic interference (EMI), voltage overshoot, and current imbalance between paralleled devices. The purpose of this dissertation is to maximize the switching performance of SiC MOSFETs using digital active gate drivers (AGDs). A three-level gate driving approach is presented to improve current sharing in paralleled SiC MOSFETs through turn-on voltage and gate signal delay adjustment. Closed-loop control with real-time feedback ensures high-reliability operation. For better practicability, a compact AGD structure of a single-path Class-B amplifier-based topology is …

Large Lithium-Ion Battery Model For Secure Shared E-Bike Battery In Smart Cities, Donghui Ding, Zhao Li, Linhao Luo, Ming Jin, Bin Zhu, Yichen Zhong, Junhao Hu, Peng Cai, Huiqi Hu

Research Collection School Of Computing and Information Systems

Electric bikes powered by lithium-ion batteries are increasingly used in smart cities to promote sustainable mobility and efficient delivery services. However, limited battery range and slow plug-in charging remain key challenges. Shared electric bike battery systems, facilitated by battery swapping stations, offer a promising solution by enabling quick and efficient battery replacements. However, their success hinges on accurate anomaly detection, battery health estimation and remain range prediction. These tasks remain challenging due to data scarcity, battery diversity and environmental variability. Here we show that a large-scale lithium-ion battery model trained on over ten million battery time series data enables robust …

Comparative Analysis Of Different Magnetic Anomaly Datasets Using Navigation Performance With Flight Test Data, Aaron P. Nielsen, Brandon M. Blakely, Patrick Duff

Faculty Publications

Magnetic Anomaly Navigation (MagNav) is a map-based method of navigation which relies on accurately obtaining the anomaly field to a high level of precision to achieve good navigation results. This requires utilizing high quality sensors, accurately modeling disturbance fields from the aircraft & other sources, and creating high-fidelity maps. Aeromagnetic survey data or marine track survey data must be processed into a product that can be used as a reference for a magnetic navigator and a variety of techniques can be utilized for this processing. The data collection for different survey types reflects choices typically made to study the underlying …

Renewable-Based Isolated Power Systems: A Review Of Scalability, Reliability, And Uncertainty Modeling, Mehrdad Ghahramani, Daryoush Habibi, Seyyedmorteza Ghamari, Hamid Soleimani, Asma Aziz

Research outputs 2022 to 2026

Electric power systems are increasingly becoming more decentralized. Many communities depend on isolated power systems that operate independently of the main grid. Remote, islanded, and isolated systems face challenges due to the intermittency and unpredictability of renewable energy sources. This paper reviews the current status of renewable integration and control in stand-alone power systems. It examines techniques to enhance system reliability through energy storage, hybrid systems, and advanced predictive models. Additionally, the issues related to connecting stand-alone systems, focusing on reliability and renewable penetration, are discussed. The scalability of stand-alone power systems is analyzed based on classifications of small-, medium-, …

Optimizing Hip And Knee Assistance For Walking And Sit-To-Stand Transitions: An Intrinsic Muscle Mechanics Based Predictive Approach, Neethan Ratnakumar

Dissertations

As the global population ages, the demand for wearable assistive technologies continues to rise, driven by their potential to enhance mobility and independence in older adults. Effectively designed controllers for lower-limb exoskeletons to assist sit-to-stand (STS) and walking are crucial for delivering efficient, safe, and comfortable assistance during daily activities. Traditionally, controller optimization involves biomechanical modeling and user-specific customization. Musculoskeletal simulations play a central role in this process by providing insights into human-exoskeleton interaction dynamics, thereby informing and refining control strategies.

This work presents a simulation-driven approach for developing exoskeleton controllers for walking and STS using two distinct methods: optimal …

An Audio Data-Driven Roadway Digital Twin And Its Underlying Framework For A Digitized Transportation Construction Environment, Anisha Deria, Pedro J. Chacon Dominguez, Yong-Cheol Lee, Jin W. Choi

Michigan Tech Publications

The increasing need to build and maintain transportation systems has led project managers to manage multiple projects simultaneously. Roadway projects often entail several miles of job site, making it difficult to keep track of progress and maintenance activities. To improve the situation, this study proposes an audio data-driven roadway digital twin framework for real-time and remote monitoring of construction projects. The latent characteristics of a digital twin required for establishing a digitized work environment were investigated. As a primary method of seamlessly linking virtual and physical environments, audio data classified and analyzed by deep neural network (DNN) has been employed …

Superhydrophilic Porous Coooh Nano-Architecture With Abundant Oxygen Vacancies For Enhanced Urea Electrooxidation At Ampere-Level Current Densities, Wen-Jing Lv, Xiao-Man Tang, Xue-Tong Wang, Wen-Cai Liu, Jian-Wen Zhu, Guo-Jing Wang, Yuan-Zhi Zhu

Journal of Electrochemistry

The conversion of urea-containing wastewater into clean hydrogen energy has gained increasing attention. However, challenges remain, particularly with sluggish catalytic kinetics and limited long-term stability of urea oxidation reaction (UOR). Herein, we report the loosely porous CoOOH nano-architecture (CoOOH LPNAs) with hydrophilic surface and abundant oxygen vacancies (O_v) on carbon fiber paper (CFP) by electrochemical reconstruction of the CoP nanoneedles precursor. The resulting three-dimensional electrode exhibited an impressively low potential of 1.38 V at 1000 mA·cm⁻² and excellent durability for UOR. Furthermore, when tested in an anion exchange membrane (AEM) electrolyzer, it required only 1.53 V at …

Structure Regulation Engineering For Biomass-Derived Carbon Anodes Enabling High-Rate Dual-Ion Batteries, Rui Zhou, Rui Liu, Yun-Nuo Li, Si-Jie Jiang, Tian-Tian Jing, Yan-Song Xu, Fei-Fei Cao

Journal of Electrochemistry

Dual-ion batteries (DIBs) usually use carbon-based materials as electrodes, showing advantages in high operating voltage, potential low cost, and environmental friendliness. Different from conventional “rocking chair” type secondary batteries, DIBs perform a unique working mechanism, which employ both cation and anion taking part in capacity contribution at an anode and a cathode, respectively, during electrochemical reactions. Graphite has been identified as a suitable cathode material for anion intercalation at high voltages (> 4.8 V) with fast reaction kinetics. However, the development of DIBs is being hindered by dynamic mismatch between a cathode and an anode due to sluggish Li^{+ …}

Design And Optimization Of Anode Catalysts For Direct Ethanol Fuel Cells: Advances And Challenges In C-C Bond Activation And Selective Modulation Of The C1 Pathway, Kai-Chi Qin, Meng-Tian Huo, Yu Liang, Si-Yuan Zhu, Zi-Hao Xing, Jin-Fa Chang

Journal of Electrochemistry

Direct ethanol fuel cells (DEFCs) are a promising alternative to conventional energy sources, offering high energy density, environmental sustainability, and operational safety. Compared to methanol fuel cells, DEFCs exhibit lower toxicity and a more mature preparation process. Unlike hydrogen fuel cells, DEFCs provide superior storage and transport feasibility, as well as cost-effectiveness, significantly enhancing their commercial viability. However, the stable C–C bond in ethanol creates a high activation energy barrier, often resulting in incomplete electrooxidation. Current commercial platinum (Pt)- and palladium (Pd)-based catalysts demonstrate low C–C bond cleavage efficiency (

Assessing Solar Radiation Patterns In Sarawak Using Measured Data And The Hargreaves-Samani Model For Photovoltaic Systems Application, Chun Yong Soo, Xian Hwa Chan, Wan Mohamad Husni Wan Mokhtar, Ahmad Rujhan Mohd Rais

Makara Journal of Technology

This study evaluates the Hargreaves-Samani model for estimating solar radiation in five locations in Sarawak: Bintulu, Kapit, Sri Aman, Kuching, and Miri (Subis), using minimum and maximum temperatures as key inputs. Analysis reveals stable minimum temperatures (19.7 °C to 28.8 °C), supporting consistent solar radiation patterns favorable for Photovoltaic (PV) performance. Miri (Subis) recorded the highest daily maximum temperature of 44.8 °C, while Kuching had the lowest at 24.7 °C, highlighting significant regional climatic variability. Analysis also indicates strong solar potential in Bintulu, Kapit, Sri Aman, Kuching, and Miri, with radiation peaking at 7.5 kWh/m², though seasonal variations impact PV …

Direct Control Strategy Using Polynomial Fuzzy-Based Adaptive Fractional Order Pid Controller, Ali Rospawan, Clara Lavita Angelina, Faisal Samsuri, Muhammad Yeza Baihaqi, Edmun Halawa, Muhammad Munajat, Vincent Vincent, Surawan Setiyadi, Irwan Purnama, Joni Welman Simatupang

Makara Journal of Technology

This paper presents a novel direct control strategy using a polynomial fuzzy neural network-based adaptive fractional order proportional integral derivative (PFNN-AFOPID) controller for nonlinear and time-varying systems. The proposed approach integrates the enhanced flexibility of fractional order calculus PID with the superior nonlinear approximation capabilities of polynomial fuzzy models, enabling dynamic adjustment of all control parameters without requiring precise mathematical modeling of system dynamics. By extending traditional PID control with fractional-order operations, the controller achieves improved frequency response and robustness against disturbances. Experimental validation on a DC motor position control system demonstrates significant performance improvements. Compared to traditional PID, the …

Analog To Digital Converters Topologies For Radar System Application: A Comparison, Kulsoom Mateen, Wafa Alharbi, Aziza I. Hussein

Effat Undergraduate Research Journal

Analog-to-digital converters (ADCs) that convert analog signals into digital ones play a significant role in radar systems. The accuracy and resolution of radar readings are significantly influenced by the quality and performance of ADCs. This paper discusses and compares the application of five different types of ADCs in radar systems. It also elaborates on each ADC's working principle, advantages, and limitations. The parameters compared are resolution and dynamic range, signal-to-noise ratio (SNR), latency and sampling rate, power consumption, size, and cost. After thorough research, we concluded that each ADC differs depending on the designer’s desired application. For example, flash ADCs …

Sar Analog-To-Digital Converters For Point-Of-Care Biosensors: A Comparison, Eithar Alammari, Joud Alamro, Sara Alashwali, Ghadah S. Alyami, Aziza I. Hussein

Effat Undergraduate Research Journal

The SAR ADC, recognized for its low power consumption, moderate resolution, and satisfactory processing speed, stands as an ideal choice for ultra-low power biomedical applications. Recent efforts have been concentrated on enhancing the power efficiency of the SAR ADC sub-components through intricate refinements and innovative techniques. These efforts aim to minimize energy consumption without compromising the ADC's performance. Therefore, this paper aims to thoroughly examine various implementation approaches for the main components of the SAR ADC, highlighting their individual strengths, weaknesses, and limitations within wireless biomedical applications.

Electrical Energy Consumption Forecasting Based On Conventional And Artificial Intelligence Methods: A Comparison, Haya H. Binsalim, Jana Kamal, Salma Badaam, Danah Milyani, Ghadah S. Alyami, Aziza I. Hussein

Effat Undergraduate Research Journal

Artificial Intelligence (AI)-based models have been widely applied for energy consumption forecasting over the past decades. The purpose of this paper is to review and compare the classical techniques and the emerging new AI-based techniques used for forecasting electrical energy consumption in buildings. The findings revealed that the Artificial Neural Network (ANN) model achieved the lowest Mean Absolute Percentage Error (MAPE) of 0.928%. AI-based techniques have many advantages over classical techniques, such as their ability to handle a large amount of data and provide accurate and fast results.