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Articles 1 - 6 of 6
Full-Text Articles in Engineering
Improved Vehicle-Bridge Interaction Modeling And Automation Of Bridge System Identification Techniques, Omar Abuodeh
Improved Vehicle-Bridge Interaction Modeling And Automation Of Bridge System Identification Techniques, Omar Abuodeh
All Dissertations
The Federal Highway Administration (FHWA) recognizes the necessity for cost-effective and practical system identification (SI) techniques within structural health monitoring (SHM) frameworks for asset management applications. Indirect health monitoring (IHM), a promising SHM approach, utilizes accelerometer-equipped vehicles to measure bridge modal properties (e.g., natural frequencies, damping ratios, mode shapes) through bridge vibration data to assess the bridge's condition. However, engineers and researchers often encounter noise from road roughness, environmental factors, and vehicular components in collected vehicle signals. This noise contaminates the vehicle signal with spurious modes corresponding to stochastic frequencies, impacting damage monitoring assessments. Thus, an efficient and reliable SI …
Oam-Based Wavelets In A High Speed Optical Probing System For Measuring The Angular Decomposition Of The Environment, Justin Free
Oam-Based Wavelets In A High Speed Optical Probing System For Measuring The Angular Decomposition Of The Environment, Justin Free
All Theses
This thesis presents the theoretical development of orbital angular momentum (OAM) based wavelets for the analysis of localized OAM information in space. An optical probing system for generating and detecting these wavelets is demonstrated; individual wavelets can scan the environment in 10µs or less. The probing system was applied to a three-dimensional atmospheric turbulence distribution to obtain a continuous wavelet transform of the angular information of the turbulent propagation path about a fixed radius. An entire continuous wavelet transform was measured in 3.8ms; the measurements are much faster than the turbulence and give insight into the short time scale of …
Hybrid Smart Transformer For Enhanced Power System Protection Against Dc With Advanced Grid Support, Moazzam Nazir
Hybrid Smart Transformer For Enhanced Power System Protection Against Dc With Advanced Grid Support, Moazzam Nazir
All Dissertations
The traditional grid is rapidly transforming into smart substations and grid assets incorporating advanced control equipment with enhanced functionalities and rapid self-healing features. The most important and strategic equipment in the substation is the transformer and is expected to perform a variety of functions beyond mere voltage conversion and isolation. While the concept of smart solid-state transformers (SSTs) is being widely recognized, their respective lifetime and reliability raise concerns, thus hampering the complete replacement of traditional transformers with SSTs. Under this scenario, introducing smart features in conventional transformers utilizing simple, cost-effective, and easy to install modules is a highly desired …
Deep Learning Based Localization Of Zigbee Interference Sources Using Channel State Information, Dylan Kensler
Deep Learning Based Localization Of Zigbee Interference Sources Using Channel State Information, Dylan Kensler
All Theses
As the field of Internet of Things (IoT) continues to grow, a variety of wireless signals fill the ambient wireless environment. These signals are used for communication, however, recently wireless sensing has been studied, in which these signals can be used to gather information about the surrounding space. With the development of 802.11n, a newer standard of WiFi, more complex information is available about the environment a signal propagates through. This information called Channel State Information (CSI) can be used in wireless sensing. With the help of Deep Learning, this work attempts to generate a fingerprinting technique for localizing a …
Deep Learning Based Speech Enhancement And Its Application To Speech Recognition, Ju Lin
Deep Learning Based Speech Enhancement And Its Application To Speech Recognition, Ju Lin
All Dissertations
Speech enhancement is the task that aims to improve the quality and the intelligibility of a speech signal that is degraded by ambient noise and room reverberation. Speech enhancement algorithms are used extensively in many audio- and communication systems, including mobile handsets, speech recognition, speaker verification systems and hearing aids. Recently, deep learning has achieved great success in many applications, such as computer vision, nature language processing and speech recognition. Speech enhancement methods have been introduced that use deep-learning techniques, as these techniques are capable of learning complex hierarchical functions using large-scale training data. This dissertation investigates the deep learning …
Analysis Of Deep Learning Methods For Wired Ethernet Physical Layer Security Of Operational Technology, Lucas Torlay
Analysis Of Deep Learning Methods For Wired Ethernet Physical Layer Security Of Operational Technology, Lucas Torlay
All Theses
The cybersecurity of power systems is jeopardized by the threat of spoofing and man-in-the-middle style attacks due to a lack of physical layer device authentication techniques for operational technology (OT) communication networks. OT networks cannot support the active probing cybersecurity methods that are popular in information technology (IT) networks. Furthermore, both active and passive scanning techniques are susceptible to medium access control (MAC) address spoofing when operating at Layer 2 of the Open Systems Interconnection (OSI) model. This thesis aims to analyze the role of deep learning in passively authenticating Ethernet devices by their communication signals. This method operates at …