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Articles 1 - 30 of 56
Full-Text Articles in Engineering
Recent Advances Of Wind-Solar Hybrid Renewable Energy Systems For Power Generation: A Review, Pranoy Roy, Jiangbiao He, Tiefu Zhao, Yash Veer Singh
Recent Advances Of Wind-Solar Hybrid Renewable Energy Systems For Power Generation: A Review, Pranoy Roy, Jiangbiao He, Tiefu Zhao, Yash Veer Singh
Electrical and Computer Engineering Faculty Publications
A hybrid renewable energy source (HRES) consists of two or more renewable energy sources, such as wind turbines and photovoltaic systems, utilized together to provide increased system efficiency and improved stability in energy supply to a certain degree. The objective of this study is to present a comprehensive review of wind-solar HRES from the perspectives of power architectures, mathematical modeling, power electronic converter topologies, and design optimization algorithms. Since the uncertainty of HRES can be reduced further by including an energy storage system, this paper presents several hybrid energy storage system coupling technologies, highlighting their major advantages and disadvantages. Various …
Application Of Deep Neural Networks To Distribution System State Estimation And Forecasting, James P. Carmichael, Yuan Liao
Application Of Deep Neural Networks To Distribution System State Estimation And Forecasting, James P. Carmichael, Yuan Liao
Electrical and Computer Engineering Faculty Publications
Classical neural networks such as feedforward multi-layer perceptron models (MLPs) are well established as universal approximators and as such, show promise in applications such as static state estimation in power transmission systems. The dynamic nature of distributed generation (i.e. solar and wind), vehicle to grid technology (V2G) and false data injection attacks (FDIAs), may pose significant challenges to the application of classical MLPs to state estimation (SE) and state forecasting (SF) in power distribution systems. This paper investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long-short term networks …
Application Of Deep Neural Networks To Distribution System State Estimation And Forecasting, James P. Carmichael, Yuan Liao
Application Of Deep Neural Networks To Distribution System State Estimation And Forecasting, James P. Carmichael, Yuan Liao
Electrical and Computer Engineering Faculty Publications
Classical neural networks such as feedforward multi-layer perceptron models (MLPs) are well established as universal approximators and as such, show promise in applications such as static state estimation in power transmission systems. The dynamic nature of distributed generation (i.e. solar and wind), vehicle to grid technology (V2G) and false data injection attacks (FDIAs), may pose significant challenges to the application of classical MLPs to state estimation (SE) and state forecasting (SF) in power distribution systems. This paper investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long-short term networks …
Nondestructive Detection Of Codling Moth Infestation In Apples Using Pixel-Based Nir Hyperspectral Imaging With Machine Learning And Feature Selection, Nader Ekramirad, Alfadhl Y. Khaled, Lauren E. Doyle, Julia R. Loeb, Kevin D. Donohue, Raul T. Villanueva, Akinbode A. Adedeji
Nondestructive Detection Of Codling Moth Infestation In Apples Using Pixel-Based Nir Hyperspectral Imaging With Machine Learning And Feature Selection, Nader Ekramirad, Alfadhl Y. Khaled, Lauren E. Doyle, Julia R. Loeb, Kevin D. Donohue, Raul T. Villanueva, Akinbode A. Adedeji
Electrical and Computer Engineering Faculty Publications
Codling moth (CM) (Cydia pomonella L.), a devastating pest, creates a serious issue for apple production and marketing in apple-producing countries. Therefore, effective nondestructive early detection of external and internal defects in CM-infested apples could remarkably prevent postharvest losses and improve the quality of the final product. In this study, near-infrared (NIR) hyperspectral reflectance imaging in the wavelength range of 900–1700 nm was applied to detect CM infestation at the pixel level for three organic apple cultivars, namely Gala, Fuji and Granny Smith. An effective region of interest (ROI) acquisition procedure along with different machine learning and data processing …
Ee-Acml: Energy-Efficient Adiabatic Cmos/Mtj Logic For Cpa-Resistant Iot Devices, Zachary Kahleifeh, Himanshu Thapliyal
Ee-Acml: Energy-Efficient Adiabatic Cmos/Mtj Logic For Cpa-Resistant Iot Devices, Zachary Kahleifeh, Himanshu Thapliyal
Electrical and Computer Engineering Faculty Publications
Internet of Things (IoT) devices have strict energy constraints as they often operate on a battery supply. The cryptographic operations within IoT devices consume substantial energy and are vulnerable to a class of hardware attacks known as side-channel attacks. To reduce the energy consumption and defend against side-channel attacks, we propose combining adiabatic logic and Magnetic Tunnel Junctions to form our novel Energy Efficient-Adiabatic CMOS/MTJ Logic (EE-ACML). EE-ACML is shown to be both low energy and secure when compared to existing CMOS/MTJ architectures. EE-ACML reduces dynamic energy consumption with adiabatic logic, while MTJs reduce the leakage power of a circuit. …
Artificial Intelligence Method For The Forecast And Separation Of Total And Hvac Loads With Application To Energy Management Of Smart And Nze Homes, Rosemary E. Alden, Huangjie Gong, Evan S. Jones, Cristinel Ababei, Dan M. Ionel
Artificial Intelligence Method For The Forecast And Separation Of Total And Hvac Loads With Application To Energy Management Of Smart And Nze Homes, Rosemary E. Alden, Huangjie Gong, Evan S. Jones, Cristinel Ababei, Dan M. Ionel
Electrical and Computer Engineering Faculty Publications
Separating the HVAC energy use from the total residential load can be used to improve energy usage monitoring and to enhance the house energy management systems (HEMS) for existing houses that do not have dedicated HVAC circuits. In this paper, a novel method is proposed to separate the HVAC dominant load component from the house load. The proposed method utilizes deep learning techniques and the physical relationship between HVAC energy use and weather. It employs novel long short-term memory (LSTM) encoder-decoder machine learning (ML) models, which are developed based on future weather data input in place of weather forecasts. In …
Equivalent Electric And Heat-Pump Water Heater Models For Aggregated Community-Level Demand Response Virtual Power Plant Controls, Huangjie Gong, Tim Rooney, Oluwaseun M. Akeyo, Brian T. Branecky, Dan M. Ionel
Equivalent Electric And Heat-Pump Water Heater Models For Aggregated Community-Level Demand Response Virtual Power Plant Controls, Huangjie Gong, Tim Rooney, Oluwaseun M. Akeyo, Brian T. Branecky, Dan M. Ionel
Electrical and Computer Engineering Faculty Publications
Advanced control techniques may be used to establish a virtual power plant to regulate the operation of electric water heaters, which may be regarded as a “uni-directional battery” and a major component of a hybrid residential energy storage system. In order to estimate the potential of regulating water heaters at the aggregated level, factors including user behavior, number of water heaters, and types of water heaters must be considered. This study develops generic water heater load curves based on the data retrieved from large experimental projects for resistive electric water heaters (EWHs) and heat pump water heaters (HPWHs). A community-level …
Improving The Power Outage Resilience Of Buildings With Solar Pv Through The Use Of Battery Systems And Ev Energy Storage, Huangjie Gong, Dan M. Ionel
Improving The Power Outage Resilience Of Buildings With Solar Pv Through The Use Of Battery Systems And Ev Energy Storage, Huangjie Gong, Dan M. Ionel
Electrical and Computer Engineering Faculty Publications
Buildings with solar photovoltaic (PV) generation and a stationary battery energy storage system (BESS) may self-sustain an uninterrupted full-level electricity supply during power outages. The duration of off-grid operation is dependent on the time of the power fault and the capabilities of the home energy management system (HEMS). In this paper, building resilience is quantified by analyzing the self-sustainment duration for all possible power outages throughout an entire year. An evaluation method is proposed and exercised on a reference house in California climate zone 9 for which the detailed electricity usage is simulated using the EnergyPlus software. The influence of …
Investigation Of Variable Switching Frequency In Finite Control Set Model Predictive Control On Grid-Connected Inverters, Luocheng Wang, Tiefu Zhao, Jiangbiao He
Investigation Of Variable Switching Frequency In Finite Control Set Model Predictive Control On Grid-Connected Inverters, Luocheng Wang, Tiefu Zhao, Jiangbiao He
Electrical and Computer Engineering Faculty Publications
Finite control set model predictive control (FCS-MPC) has been widely studied and applied to the power converters and motor drives. It provides the power electronics system with fast dynamic response, nonlinear system formulation, and flexible objectives and constraints integration. However, its variable switching frequency feature also induces severe concerns on the power loss, the thermal profile, and the filter design. Stemming from these concerns, this article investigates the variable switching frequency characteristics of FCS-MPC on the grid-connected inverters. An intuitive relationship between the switching frequency and the magnitude of the converter output voltage is proposed through the geometry analysis, where …
Centralized Thermal Stress Oriented Dispatch Strategy For Paralleled Grid-Connected Inverters Considering Mission Profiles, Luocheng Wang, Tiefu Zhao, Jiangbiao He
Centralized Thermal Stress Oriented Dispatch Strategy For Paralleled Grid-Connected Inverters Considering Mission Profiles, Luocheng Wang, Tiefu Zhao, Jiangbiao He
Electrical and Computer Engineering Faculty Publications
One of the major failure causes in the power modules comes from the severe thermal stress in power semiconductor devices. Recently, some local control level methods have been developed to balance the power loss, dealing with the harsh mission profile, in order to reduce the thermal stress. However, there is not any specific system level strategy to leverage these local control level methods responding to the multiple inverters situation. Besides, the impacts of these methods on the thermal cycle and lifetime of the power modules in the long-term time scale have not been evaluated and compared yet. Hence, in this …
On The Impact Of Gravity Compensation On Reinforcement Learning In Goal-Reaching Tasks For Robotic Manipulators, Jonathan Fugal, Hasan A. Poonawala, Jihye Bae
On The Impact Of Gravity Compensation On Reinforcement Learning In Goal-Reaching Tasks For Robotic Manipulators, Jonathan Fugal, Hasan A. Poonawala, Jihye Bae
Electrical and Computer Engineering Faculty Publications
Advances in machine learning technologies in recent years have facilitated developments in autonomous robotic systems. Designing these autonomous systems typically requires manually specified models of the robotic system and world when using classical control-based strategies, or time consuming and computationally expensive data-driven training when using learning-based strategies. Combination of classical control and learning-based strategies may mitigate both requirements. However, the performance of the combined control system is not obvious given that there are two separate controllers. This paper focuses on one such combination, which uses gravity-compensation together with reinforcement learning (RL). We present a study of the effects of gravity …
An Ultrabroadband 3d Achromatic Metalens, Fatih Balli, Mansoor A. Sultan, Aytekin Ozdemir, J. Todd Hastings
An Ultrabroadband 3d Achromatic Metalens, Fatih Balli, Mansoor A. Sultan, Aytekin Ozdemir, J. Todd Hastings
Electrical and Computer Engineering Faculty Publications
We design and fabricate ultra-broadband achromatic metalenses operating from the visible into the short-wave infrared, 450–1700 nm, with diffraction-limited performance. A hybrid 3D architecture, which combines nanoholes with a phase plate, allows realization in low refractive index materials. As a result, two-photon lithography can be used for prototyping while molding can be used for mass production. Experimentally, a 0.27 numerical aperture (NA) metalens exhibits 60% average focusing efficiency and 6% maximum focal length error over the entire bandwidth. In addition, a 200 μm diameter, 0.04 NA metalens was used to demonstrate achromatic imaging over the same broad spectral range. These …
Study Of Renewable Energy Penetration On A Benchmark Generation And Transmission System, Oluwaseun M. Akeyo, Aron Patrick, Dan M. Ionel
Study Of Renewable Energy Penetration On A Benchmark Generation And Transmission System, Oluwaseun M. Akeyo, Aron Patrick, Dan M. Ionel
Electrical and Computer Engineering Faculty Publications
Significant changes in conventional generator operation and transmission system planning will be required to accommodate increasing solar photovoltaic (PV) penetration. There is a limit to the maximum amount of solar that can be connected in a service area without the need for significant upgrades to the existing generation and transmission infrastructure. This study proposes a framework for analyzing the impact of increasing solar penetration on generation and transmission networks while considering the responses of conventional generators to changes in solar PV output power. Contrary to traditional approaches in which it is assumed that generation can always match demand, this framework …
Parameter Identification For Cells, Modules, Racks, And Battery For Utility-Scale Energy Storage Systems, Oluwaseun M. Akeyo, Vandana Rallabandi, Nicholas Jewell, Aron Patrick, Dan M. Ionel
Parameter Identification For Cells, Modules, Racks, And Battery For Utility-Scale Energy Storage Systems, Oluwaseun M. Akeyo, Vandana Rallabandi, Nicholas Jewell, Aron Patrick, Dan M. Ionel
Electrical and Computer Engineering Faculty Publications
The equivalent circuit model for utility-scale battery energy storage systems (BESS) is beneficial for multiple applications including performance evaluation, safety assessments, and the development of accurate models for simulation studies. This paper evaluates and compares the performance of utility-scale equivalent circuit models developed at multiple sub-component levels, i.e. at the rack, module, and cell levels. This type of modeling is used to demonstrate that the equivalent circuit model for a reference cell, module, or rack of a BESS can be scaled to represent the entire battery system provided that the battery management system (BMS) is active and functional. Contrary to …
Cost Minimization Of Battery-Supercapacitor Hybrid Energy Storage For Hourly Dispatching Wind-Solar Hybrid Power System, Pranoy Roy, Jiangbiao He, Yuan Liao
Cost Minimization Of Battery-Supercapacitor Hybrid Energy Storage For Hourly Dispatching Wind-Solar Hybrid Power System, Pranoy Roy, Jiangbiao He, Yuan Liao
Electrical and Computer Engineering Faculty Publications
This study demonstrates a dispatching scheme of wind-solar hybrid power system (WSHPS) for a one-hour dispatching period for an entire day utilizing battery and supercapacitor hybrid energy storage subsystem (HESS). A frequency management approach is deployed to extend the longevity of the batteries through extensively utilizing the high energy density property of batteries and the high power density property of supercapacitors in the HESS framework. A low-pass filter (LPF) is employed to decouple the power between a battery and a supercapacitor (SC). The cost optimization of the HESS is computed based on the time constant of the LPF through extensive …
Combined Numerical And Experimental Determination Of Ball Bearing Capacitances For Bearing Current Prediction, Peng Han, Greg Heins, Dean Patterson, Mark Theile, Dan M. Ionel
Combined Numerical And Experimental Determination Of Ball Bearing Capacitances For Bearing Current Prediction, Peng Han, Greg Heins, Dean Patterson, Mark Theile, Dan M. Ionel
Electrical and Computer Engineering Faculty Publications
High-frequency voltages across the steel ball bearings and the corresponding currents can cause premature bearing failures in electric machines driven by PWM converters. The bearing voltage, one of the most commonly-used failure indicators, depends heavily on the bearing capacitance. This paper presents a combined numerical and experimental approach for the calculation of ball bearing capacitances to address the uncertainty introduced by lubricant property, lubrication status and other metal parts, such as seals and ball retainers. Based on the obtained capacitance breakdown, the influences of temperature, speed and bearing load (radial, axial or combined) on the capacitance are studied. Measurements and …
Design Optimization Of Coreless Axial-Flux Pm Machines With Litz Wire And Pcb Stator Windings, Murat G. Kesgin, Peng Han, Narges Taran, Damien Lawhorn, Donovin Lewis, Dan M. Ionel
Design Optimization Of Coreless Axial-Flux Pm Machines With Litz Wire And Pcb Stator Windings, Murat G. Kesgin, Peng Han, Narges Taran, Damien Lawhorn, Donovin Lewis, Dan M. Ionel
Electrical and Computer Engineering Faculty Publications
Coreless axial-flux permanent-magnet (AFPM) machines may be attractive options for high-speed and high-power-density applications due to the elimination of core losses. In order to make full use of the advantages offered by these machines and avoid excessive eddy current losses in windings, advanced technologies for winding conductors need to be employed to suppress the eddy effect, such as the Litz wire and printed circuit board (PCB). In this paper, the best practices for designing Litz wire/PCB windings are discussed and a brief survey of state of the art PCB winding technology is provided. Three coreless AFPM machines are mainly considered. …
A Hybrid Achromatic Metalens, Fatih Balli, Mansoor A. Sultan, Sarah K. Lami, J. Todd Hastings
A Hybrid Achromatic Metalens, Fatih Balli, Mansoor A. Sultan, Sarah K. Lami, J. Todd Hastings
Electrical and Computer Engineering Faculty Publications
Metalenses, ultra-thin optical elements that focus light using subwavelength structures, have been the subject of a number of recent investigations. Compared to their refractive counterparts, metalenses offer reduced size and weight, and new functionality such as polarization control. However, metalenses that correct chromatic aberration also suffer from markedly reduced focusing efficiency. Here we introduce a Hybrid Achromatic Metalens (HAML) that overcomes this trade-off and offers improved focusing efficiency over a broad wavelength range from 1000-1800 nm. HAMLs can be designed by combining recursive ray-tracing and simulated phase libraries rather than computationally intensive global search algorithms. Moreover, HAMLs can be fabricated …
Introducing Phonetic Information To Speaker Embedding For Speaker Verification, Yi Liu, Liang He, Michael T. Johnson
Introducing Phonetic Information To Speaker Embedding For Speaker Verification, Yi Liu, Liang He, Michael T. Johnson
Electrical and Computer Engineering Faculty Publications
Phonetic information is one of the most essential components of a speech signal, playing an important role for many speech processing tasks. However, it is difficult to integrate phonetic information into speaker verification systems since it occurs primarily at the frame level while speaker characteristics typically reside at the segment level. In deep neural network-based speaker verification, existing methods only apply phonetic information to the frame-wise trained speaker embeddings. To improve this weakness, this paper proposes phonetic adaptation and hybrid multi-task learning and further combines these into c-vector and simplified c-vector architectures. Experiments on National Institute of Standards and Technology …
Enhanced Crystallinity Of Triple-Cation Perovskite Film Via Doping Nh4Scn, Ziji Liu, Detao Liu, Hao Chen, Long Ji, Hualin Zheng, Yiding Gu, Feng Wang, Zhi Chen, Shibin Li
Enhanced Crystallinity Of Triple-Cation Perovskite Film Via Doping Nh4Scn, Ziji Liu, Detao Liu, Hao Chen, Long Ji, Hualin Zheng, Yiding Gu, Feng Wang, Zhi Chen, Shibin Li
Electrical and Computer Engineering Faculty Publications
The trap-state density in perovskite films largely determines the photovoltaic performance of perovskite solar cells (PSCs). Increasing the crystal grain size in perovskite films is an effective method to reduce the trap-state density. Here, we have added NH4SCN into perovskite precursor solution to obtain perovskite films with an increased crystal grain size. The perovskite with increased crystal grain size shows a much lower trap-state density compared with reference perovskite films, resulting in an improved photovoltaic performance in PSCs. The champion photovoltaic device has achieved a power conversion efficiency of 19.36%. The proposed method may also impact other optoelectronic …
Latent Class Model With Application To Speaker Diarization, Liang He, Xianhong Chen, Can Xu, Yi Liu, Jia Liu, Michael T. Johnson
Latent Class Model With Application To Speaker Diarization, Liang He, Xianhong Chen, Can Xu, Yi Liu, Jia Liu, Michael T. Johnson
Electrical and Computer Engineering Faculty Publications
In this paper, we apply a latent class model (LCM) to the task of speaker diarization. LCM is similar to Patrick Kenny’s variational Bayes (VB) method in that it uses soft information and avoids premature hard decisions in its iterations. In contrast to the VB method, which is based on a generative model, LCM provides a framework allowing both generative and discriminative models. The discriminative property is realized through the use of i-vector (Ivec), probabilistic linear discriminative analysis (PLDA), and a support vector machine (SVM) in this work. Systems denoted as LCM-Ivec-PLDA, LCM-Ivec-SVM, and LCM-Ivec-Hybrid are introduced. In addition, three …
Automatic Look-Up Table Based Real-Time Phase Unwrapping For Phase Measuring Profilometry And Optimal Reference Frequency Selection, Jianwen Song, Daniel L. Lau, Yo-Sung Ho, Kai Liu
Automatic Look-Up Table Based Real-Time Phase Unwrapping For Phase Measuring Profilometry And Optimal Reference Frequency Selection, Jianwen Song, Daniel L. Lau, Yo-Sung Ho, Kai Liu
Electrical and Computer Engineering Faculty Publications
For temporal phase unwrapping in phase measuring profilometry, it has recently been reported that two phases with co-prime frequencies can be absolutely unwrapped using a look-up table; however, frequency selection and table construction has been performed manually without optimization. In this paper, a universal phase unwrapping method is proposed to unwrap phase flexibly and automatically by using geometric analysis, and thus we can programmatically build a one-dimensional or two-dimensional look-up table for arbitrary two co-prime frequencies to correctly unwrap phases in real time. Moreover, a phase error model related to the defocus effect is derived to figure out an optimal …
Sliding-Mode-Observer-Based Position Estimation For Sensorless Control Of The Planar Switched Reluctance Motor, Jundi Sun, Guang-Zhong Cao, Su-Dan Huang, Yeping Peng, Jiangbiao He, Qing-Quan Qian
Sliding-Mode-Observer-Based Position Estimation For Sensorless Control Of The Planar Switched Reluctance Motor, Jundi Sun, Guang-Zhong Cao, Su-Dan Huang, Yeping Peng, Jiangbiao He, Qing-Quan Qian
Electrical and Computer Engineering Faculty Publications
This paper proposes a position estimation method for a planar switched reluctance motor (PSRM). In the method, a second-order sliding mode observer (SMO) is used to achieve sensorless control of a PSRM for the first time. A sensorless closed-loop control strategy based on the SMO without a position sensor for the PSRM is constructed. The SMO mainly consists of a flux linkage estimation, an adaptive current estimation, an observing error calculation, and a position estimation section. An adaptive current observer is applied in the current estimation section to minimize the error between the measured and estimated currents and to increase …
Design And Analysis Of Long-Stroke Planar Switched Reluctance Motor For Positioning Applications, Su-Dan Huang, Guang-Zhong Cao, Yeping Peng, Chao Wu, Deliang Liang, Jiangbiao He
Design And Analysis Of Long-Stroke Planar Switched Reluctance Motor For Positioning Applications, Su-Dan Huang, Guang-Zhong Cao, Yeping Peng, Chao Wu, Deliang Liang, Jiangbiao He
Electrical and Computer Engineering Faculty Publications
This paper presents the design, control, and experimental performance evaluation of a long-stroke planar switched reluctance motor (PSRM) for positioning applications. Based on comprehensive consideration of the electromagnetic and mechanical characteristics of the PSRM, a motor design is first developed to reduce the force ripple and deformation. A control scheme with LuGre friction compensation is then proposed to improve the positioning accuracy of the PSRM. Furthermore, this control scheme is proven to ensure the stable motion of the PSRM system. Additionally, the response speed and steady-state error of the PSRM system with this control scheme are theoretically analyzed. Finally, the …
An Accurate And Efficient Time Delay Estimation Method Of Ultra-High Frequency Signals For Partial Discharge Localization In Substations, Pengfei Li, Kejie Dai, Tong Zhang, Yantao Jin, Yushun Liu, Yuan Liao
An Accurate And Efficient Time Delay Estimation Method Of Ultra-High Frequency Signals For Partial Discharge Localization In Substations, Pengfei Li, Kejie Dai, Tong Zhang, Yantao Jin, Yushun Liu, Yuan Liao
Electrical and Computer Engineering Faculty Publications
Partial discharge (PD) localization in substations based on the ultra-high frequency (UHF) method can be used to efficiently assess insulation conditions. Localization accuracy is affected by the accuracy of the time delay (TD) estimation, which is critical for PD localization in substations. A review of existing TD estimation methods indicates that there is a need to develop methods that are both accurate and computationally efficient. In this paper, a novel TD estimation method is proposed to improve both accuracy and efficiency. The TD is calculated using an improved cross-correlation algorithm based on full-wavefronts of array UHF signals, which are extracted …
Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson
Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson
Electrical and Computer Engineering Faculty Publications
Recurrent neural networks (RNNs) have shown an ability to model temporal dependencies. However, the problem of exploding or vanishing gradients has limited their application. In recent years, long short-term memory RNNs (LSTM RNNs) have been proposed to solve this problem and have achieved excellent results. Bidirectional LSTM (BLSTM), which uses both preceding and following context, has shown particularly good performance. However, the computational requirements of BLSTM approaches are quite heavy, even when implemented efficiently with GPU-based high performance computers. In addition, because the output of LSTM units is bounded, there is often still a vanishing gradient issue over multiple layers. …
Fault Identification And Location For Distribution Network With Distributed Generations, Wen Fan, Yuan Liao
Fault Identification And Location For Distribution Network With Distributed Generations, Wen Fan, Yuan Liao
Electrical and Computer Engineering Faculty Publications
Power distribution networks with distributed generations may experience faults. It is essential to promptly locate the fault for fast repair and restoration. This paper presents a novel method for identifying the faulted section and accurate location of faults that occur on power distribution grid. Appropriate matrices are set up to represent meter locations on the grid and the topology of the grid. The voltage and current measurements obtained are utilized to decide the fault sections. Then fault location is determined by solving equations that link measurements and fault locations through bus impedance matrix. The method is applicable to both single …
Effective Room-Temperature Ammonia-Sensitive Composite Sensor Based On Graphene Nanoplates And Pani, Zongbiao Ye, Yan Chen, Bohao Liu, Yuanjie Su, Zhi Chen, Huiling Tai, Yadong Jiang
Effective Room-Temperature Ammonia-Sensitive Composite Sensor Based On Graphene Nanoplates And Pani, Zongbiao Ye, Yan Chen, Bohao Liu, Yuanjie Su, Zhi Chen, Huiling Tai, Yadong Jiang
Electrical and Computer Engineering Faculty Publications
The graphene nanoplate (GN)-polyaniline (PANI) composite was developed via in-situ polymerization method and simultaneously assembled on interdigital electrodes (IDEs) at low temperature for ammonia (NH3) detection. The assembled composite sensor showed excellent sensing performance toward different concentrations of NH3, 1.5 of response value and 123 s/204 s for the response/recovery time to 15 ppm NH3. Meanwhile, an interesting supersaturation phenomenon was observed at high concentration of NH3. A reasonable speculation was proposed for this special sensing behavior and the mechanism for enhanced sensing properties was also analyzed.
Universal Phase Unwrapping For Phase Measuring Profilometry Using Geometry Analysis, Jianwen Song, Yo-Sung Ho, Daniel L. Lau, Kai Liu
Universal Phase Unwrapping For Phase Measuring Profilometry Using Geometry Analysis, Jianwen Song, Yo-Sung Ho, Daniel L. Lau, Kai Liu
Electrical and Computer Engineering Faculty Publications
Traditionally temporal phase unwrapping for phase measuring profilometry needs to employ the phase computed from unit-frequency patterned images; however, it has recently been reported that two phases with co-prime frequencies can be absolutely unwrapped each other. However, a manually man-made look-up table for two known frequencies has to be used for correctly unwrapping phases. If two co-prime frequencies are changed, the look-up table has to be manually rebuilt. In this paper, a universal phase unwrapping algorithm is proposed to unwrap phase flexibly and automatically. The basis of the proposed algorithm is converting a signal-processing problem into a geometric analysis one. …
Accurate Location Of Evolving Faults On Transmission Lines Using Sparse Wide Area Measurements, Xiangqing Jiao, Yuan Liao
Accurate Location Of Evolving Faults On Transmission Lines Using Sparse Wide Area Measurements, Xiangqing Jiao, Yuan Liao
Electrical and Computer Engineering Faculty Publications
In electric power systems, not all fault conditions remain unchanged during faults. An evolving fault has one characteristic initially and changes to a different condition subsequently. Locating evolving faults is challenging due to the change in fault type shortly after the fault initiation. This paper presents a new approach for estimating the locations of evolving faults on transmission lines. By using sparse wide area voltage measurements, this method is able to accurately locate evolving faults without requiring measurements from either end of the faulted line. There is no need to detect whether a fault is an evolving fault or not. …