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- Title
- PARTICLE FILTERING ESTIMATION APPROACH IN ADVANCED DIGITAL COMMUNICATION SYSTEMS
- Creator
- Huang, Lun
- Date
- 2013, 2013-05
- Description
-
The ever-increasing volume of users and the demand for more communication services bring about many advanced modulation and demodulation...
Show moreThe ever-increasing volume of users and the demand for more communication services bring about many advanced modulation and demodulation technologies which are developed to increase the spectrum efficiency and cope with challenging transmission conditions in digital communications. However, it is difficult to improve the performance of those traditional modulation and demodulation approaches without increasing transmit power and lowering spectrum efficiency. This thesis studies the application of powerful Particle Filtering methods to the problems associated with the interference cancellation, equalization, demodulation, and decoding of the signals over communication channel. In this thesis, theoretic models of using particle filtering approaches in digital communications are investigated, and several specific algorithms and schemes are considered as applications of the theoretic models. First, the application of particle filtering in delayed decision feed-back sequence estimation equalization is addressed. The particle filtering approach is then introduced to an efficient particle filtering receiver for inter-carrier interference cancellation and demodulation of M-ary modulated signals in OFDM/OFDMA system under time-variant Rayleigh fading channels. Subsequently, an efficient sequential Monte Carlo (SMC) demodulation approach for Polynomial Phase Modulation (PPM) is discussed. The interference cancellation and demodulation algorithm for MIMO-PPM scenario is then derived. The analysis of performance and computational complexity for SMC particle filtering approach is also provided. Comprehensive simulation results confirm that the proposed sequential Monte Carlo particle filtering approaches have better performance than the conventional methods.
PH.D in Electrical Engineering, May 2013
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- Title
- INTEGRATED PLANNING OF BEV PUBLIC FAST-CHARGING STATIONS
- Creator
- Gong, Lin
- Date
- 2015, 2015-12
- Description
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This thesis proposes a multi-layer strategy and an abstract map method to achieve an integrated planning of public fast-charging stations to...
Show moreThis thesis proposes a multi-layer strategy and an abstract map method to achieve an integrated planning of public fast-charging stations to charge certain number of lightduty battery electric vehicles in a given geographic region under its existing environment, aiming to improve application of electric vehicle in the studied region and finally enhance social welfare in a long term by optimally locating public fast-charging stations and assigning their installed capacities to maximize the possibility of effectively charging battery electric vehicles, as well as to minimize the infrastructure cost and mitigate possible negative impacts on the transportation system and the electric power system. In the first layer of this multi-layer strategy, the conditions of the transportation system are considered, analyzed and mathematically modeled, while in the second layer, based on the former layer, the conditions of the electric power system are incorporated. Then in the third layer, an integrated planning of public fast-charging stations is achieved by combining both the transportation system's and the electric power system's conditions. From the first to the last layer, a case is studied in each layer to test the idea, method and also the mathematical model which is built by the MILP method. These works are based on an abstract road network map which is rooted in the actual map of a representative geographic region. After the optimal results based on the abstract map are obtained, they will be mapped back to the actual map of the representative geographic region. Therefore, the ideas, methods and solutions studied in this thesis aiming to achieve an integrated planning of public fast-charging stations to charge battery electric vehicles are able to be applied in practice.
M.S. in Electrical Engineering, December 2015
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- Title
- HARDWARE/SOFTWARE CO-DESIGN PARTITIONING ALGORITHM FOR MACHINE VISION APPLICATIONS
- Creator
- Gonnot, Thomas
- Date
- 2017, 2017-05
- Description
-
Advancements in FPGA technologies now allows the implementation of machine vision using hardware component rather than processors for...
Show moreAdvancements in FPGA technologies now allows the implementation of machine vision using hardware component rather than processors for increased efficiency. The combination of hardware and software implementations, however, can provide even more efficient results by combining the advantages of both technologies. This leads to the problem of partitioning the machine vision algorithms between hardware and software. The hardware/software partition problem is NP-hard, which means that a solution to the problem can be checked in polynomial time, but the time to find the solution is not predictable. Automated methods based on a genetic algorithm or discrete particle swarm optimization algorithm allow a designer to implement computer vision algorithms without concerns for the hardware/software partitioning. Their reliance on randomness to explore different partitioning selections, however, means that the optimum result might not be reached and that the processing time cannot be predicted. This dissertation introduces a model for image processing and computer vision algorithms in a set of elementary blocks, each of which is assigned one or more configuration. This configuration can be either hardware or software and is linked to the corresponding resource utilization and performance. A procedure is also introduced to allocate the different blocks to either hardware or software, and a cost function is defined to evaluate the relevance of the generated design. The implementation of the model and procedure allows for the partitioning of any image processing in polynomial time by checking various implementations and selecting the optimum solution. This thesis includes two test cases used to test the efficiency of the method. The shift-invariant features transform is used to demonstrate the viability of the partitioning results on an algorithm containing multiple image convolution operations in parallel. The neural network, on the other hand, is used to demonstrate the performances of the procedure when machine vision algorithm contains many blocks. Finally, this dissertation present a set of machine vision applications, such as object tracking, object recognition, optical character recognition, facial recognition, and visually impaired assistance. The proposed model and procedure could be included in the design flow of hardware/software co-design tools and provide a library of image processing blocks ready to be implemented. This would allow image processing and computer vision designers would be able to implement any algorithm efficiently in hardware/software co-design without the need to know how to partition it.
Ph.D. in Electrical Engineering, May 2017
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- Title
- DESIGN AND DEVELOPMENT OF A DRIVETRAIN TEST BENCH FOR ELECTRIC AND HYBRID ELECTRIC VEHICLES
- Creator
- Niu, Geng
- Date
- 2013, 2013-12
- Description
-
Due to continuously increasing price of petroleum and related environmental issues, the automotive industry is more focus on the fuel...
Show moreDue to continuously increasing price of petroleum and related environmental issues, the automotive industry is more focus on the fuel efficient and low energy consumption. Electric-Drive vehicles (EDV), such as Electric Vehicles (EV), Hybrid Electric Vehicles (HEV) and Plug-in Hybrid Electric Vehicles are expected to replace the regular energy consumption vehicles and be the next generation of regular means of transportation. Low emission is one feature that will have significant effect on environment issue and less regular energy consumption is another feature that will reduce the speed of the global depletion of the world’s oil. Furthermore EDVs have relatively higher efficiency because of lots of research on the topology exploration, fuel efficiency maximization strategies, power conversion technologies, and integration into the current power grid. EDVs have mechanical system and electrical system and both of them works concurrently. So the best way to test EDV is that design a detailed drivetrain test bench for performance evaluation EVs and HEVs. This emulation test bench can be a lab setup that researchers can do an EDV program testing and also can serve as an educational tool that will provide a real observation for engineering students to realize EVs and HEVs design and how it works. The test bench has two separate sections, one is for performance evaluation all-electric-vehicle and the other is for performance evaluation series hybrid electric vehicle. These two setups use same motors, servomotor and controllers. HEV drivetrain is consist of two 6 HP axial flux permanent magnet (AFPM) brushless machines and two servomotors (PMSM) made by Kollmorgen. EV drivetrain is consist of one 6 HP axial xii flux permanent magnet (AFPM) brushless machine and one permanent magnet servomotors made by Kollmorgen. The purpose of this work is to design and develop a detailed test bench for performance evaluation of both EVs and HEVs, especially for undergraduate students and graduate students understanding the structure and design of EDVs. Labview is used as the interface to monitor all the components of the whole system. Through the EV test bench, student can observe how the all-electric-vehicle works and compare with traditional vehicles. HEV test bench can give student a vision observation of series hybrid electric vehicle. From these two test benches, students can realize the different operation modes of EDVs and observe the direction of the power flow of EDVs. [1-2] Finally, student can program different drive cycles to the servomotor and then test the cycles by running the test bench.
M.S. in Electrical Engineering, December 2013
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- Title
- SLIDING MODE CONTROL OF CONVERTERS WITH AN INDEPENDENT NEUTRAL POINT
- Creator
- Ghosh, Somsubhra
- Date
- 2017, 2017-07
- Description
-
With the increasing footprint of renewable energy, the drive towards a cleaner environment has consistently pushed forward the development of...
Show moreWith the increasing footprint of renewable energy, the drive towards a cleaner environment has consistently pushed forward the development of power electronics based power converters. While the basic principles of operating the power electronics in these power converters have been very effective in providing for a very efficient system, new topologies and advanced control strategies enable us to achieve a still higher efficiency, simplification and help us overcome some of the fundamental problems encountered in operation. One of the fundamental requirements of the power electronic converters is that they require a significantly large output capacitors. it is necessary to remove ripples in the rectified AC voltage. Numerous approaches have been presented in the past to overcome these issues including the addition of a ripple compensator to a conventional H-Bridge rectifier as well as using one leg of the H-Bridge itself as a neutral leg. A new controller; based on sliding mode has been proposed here to a neutral leg topology as well as the conventional H-Bridge topology of a single-phase power converter. In case of a rectifier, the ripple energy is separated and directed towards the lower split capacitor present at the neutral leg so that the upper split capacitor may have very small ripples while in case of an inverter the lower capacitor actually acts as an independently controlled DC source. all the while the capacitance is kept to be very small. The control of the two legs in the rectifier is performed independently granting the controller an extra degree of freedom and an easier extrapolation to the 3-phase implementation. The controller operates the power electronic switches to regulate the input grid current and achieve unity power factor as well as to maintain a stable DC bus voltage removing the need for any other power factor correction circuit.
M.S. in Electrical Engineering, July 2017
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- Title
- A NOVEL FIXED DISPLACEMENT ELECTRIC-HYDRAULIC HYBRID (EH2) DRIVETRAIN CONCEPT FOR CITY VEHICLES
- Creator
- Sun, Yingguang
- Date
- 2013, 2013-07
- Description
-
With growing emphasis on energy independence and environmental issues, alternative energy vehicles, especially Electric Vehicles (EV), Hybrid...
Show moreWith growing emphasis on energy independence and environmental issues, alternative energy vehicles, especially Electric Vehicles (EV), Hybrid Electric Vehicles (HEV) and Plug-in Hybrid Electric Vehicles (PHEV) have received significant attention. Though these solutions can have significant an impact on the environment, economy and efficiency, some challenges still exist in the widespread acceptance of EVs and HEVs. Some issues include low power density of the battery and low battery durability caused by frequent charging and discharging. This can be especially significant for city use owing to typical drive cycles. In order to address this problem, this work proposes a novel electric-hydraulic hybrid (EH2) drivetrain for PHEVs, HEVs and EVs. An EH2 drivetrain is comprised of an electric traction motor and a hydraulic system that uses a combination of hydraulic pump, motor and accumulator. All the components and their operation theory are introduced in this work. In the proposed system, a hydraulic accumulator is used for energy storage during the regenerative braking process. The energy stored in the accumulator will be released to the hydraulic motor during the power assistance process [1]. In this drivetrain, two 6 HP axial flux permanent magnet (AFPM) brushless machines are selected as the traction motor and hydraulic drive. This kind of motor is very suitable for electric vehicles, pump, valve control, fans, etc. due to its pancake shape, compact structure and high torque density [2]. To validate the proposed design, the mathematical model of the hydraulic energy storage system is built in Matlab/Simulink environment and the simulation results are given both for the regenerative braking process and power assistance process. The xiv models of the axial flux permanent magnet brushless machines and its drive system are also built in the Matlab/Simulink. The simulation results are compared with the experimental testing results from the motor test bed built in the lab. Preliminary simulation and experimental results show in the regenerative braking process, 5332 J energy is stored in the accumulator and the energy conversion efficiency is 64.39%. In power assistance process, all the energy stored in the accumulator is released and the vehicle accelerates from 0 m/s to 5.2 m/s. The energy conversion efficiency is 50.71%. These results prove that the hydraulic energy storage system can be used in power assistance and energy storage. The charging and discharging time is very short compared with other energy storage systems. More importantly, the stored energy can reduce the number of times the battery is charged and discharged. In this way the battery size can be reduced and the battery life can be extended. The parallel hydraulic-electric configuration is proved to be a promising solution towards energy storage and power assistance for electric vehicles. Finally, the electric and hydraulic components have been implemented on a go-kart setup built in the lab for future complete drivetrain testing. From the conducted research, it can be concluded that successful implementation of this concept can lead to a wider acceptance of electric vehicles.
M.S. in Electrical Engineering, July 2013
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- Title
- CAPACITY ANALYSIS OF MULTI-RADIO MULTI-CHANNEL (MR-MC) WIRELESS NETWORK
- Creator
- Li, Hongkun
- Date
- 2012-11-15, 2012-12
- Description
-
The multi-radio multi-channel (MR-MC) networking provides a generic computing platform for a wide range of next-generation wireless networks,...
Show moreThe multi-radio multi-channel (MR-MC) networking provides a generic computing platform for a wide range of next-generation wireless networks, e.g., wireless mesh networks based on the IEEE 802.16, 4G cellular networks based on the long term evolution (LTE), and cognitive radio networks based on the dynamic spectrum sharing. Multiple radio interfaces and channels allow more flexible network configuration to achieve higher network capacity. However, the capacity of the MR-MC networking is not well studied due to the lack of effective tool addressing the complex interactions of the channel assignment and radio interface allocation problem. Moreover, how to efficiently utilize multiple interfaces and channels is unexplored. Generally, we have the four main contributions in this work. 1) an efficient methodology is proposed to compute the optimal capacity of MR-MC network and the concept of critical set is revealed. 2) two sufficient conditions are developed for the flow assignment, which can be constructed and verified in distributed manner. Both conditions achieve a provable portion of the optimal capacity region. 3) a novel framework and efficient algorithms are developed for the dynamic network control in the MR-MC network. 4) a new routing metric is proposed to consider both delay and interference for path selection, and a routing protocol is designed correspondingly. Specifically, we originally construct a new multi-dimensional conflict graph (MDCG) to describe all the interference relationship in the MR-MC network. Based on MDCG, we formulate a multi-commodity flow (MCF) problem augmented with maximal independent set (MIS) constraint to compute the optimal capacity, so that the optimal capacity planning in MR-MC networks can be transformed from integer programming regime to linear programming regime. We further provide the new concept of critical MIS set, and estimate the upper bound of the size of critical MIS set. Therefore, a heuristic algorithm is designed to systematically compute those MISs, which are more likely to be involved in critical set. Moreover, we develop the sufficient conditions for the flow rate assignment, which achieve viii a provable portion of the optimal capacity region, termed as efficiency ratio. These sufficient constraints could be constructed and verified in the distributed and localized manner. We develop new method to compute the efficiency ratio for each sufficient condition by exploring the disruptively different geometric property of MR-MC networks compared with single radio single channel network. Then we develop a new framework to systematically study the resource allocation problem considering the dynamic network control in the MRMC network. The framework not only facilitates the formulation of throughput-optimal scheduling for the MR-MC network, but also allows us optimally solving the joint resource allocation problem, including routing, channel/interface assignment, flow allocation and scheduling. At last, a new routing metric is proposed to consider not only the transmission delay also queuing delay. In addition, in the MR-MC context, the inter-flow interference and intra-flow interference are taken into account. An AODV-based routing protocol is designed to implement the new metric.
PH.D in Electrical and Computer Engineering, December 2012
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- Title
- Industrial illumination
- Creator
- Arenberg, Albert Lee
- Date
- 2009, 1917
- Publisher
- Armour Institute of Technology
- Description
-
http://www.archive.org/details/industrialillumi00aren
Thesis (B.S.)--Armour Institute of Technology, 1917 B.S. in Electrical Engineering, 1917
- Title
- IMPLEMENTATION OF GENERAL-PURPOSE BENDERS DECOMPOSITION ALGORITHM IN MATLAB AND ITS APPLICATION TO POWER SYSTEM PLANNING
- Creator
- Shao, Hang
- Date
- 2013-04-29, 2013-05
- Description
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For most huge systems, planning is a very important step to adapt them for future excepted changes. Planning could figure out most of...
Show moreFor most huge systems, planning is a very important step to adapt them for future excepted changes. Planning could figure out most of potential problems and help people to make long-term decisions to get more secure and profitable. But huge system-planning problems would cost long time and lots of effort, we need some mathematic methods to simplify and solve the problems. Luckily, there comes Benders Decomposition. Benders Decomposition is a popular technique in solving certain classes of difficult problems such as stochastic programming problems, and mixed-integer nonlinear programming problems [1][2]. Then some software is needed to model basic template of Benders Decomposition algorithm with and for most engineers, MATLAB is one of the most popular software, which could solve engineering problems by matrixes. So the resultant model is solved numerically by the application of Benders Decomposition algorithm, whose implementation and development were executed using the software MATLAB. Even though the codes are for general system-planning problems, most of examples in this paper were power systems. But it does not mean it could only solve specifically, examples of power systems are popular and typical in Bender Decomposition problem solving. This paper describes the process of programming, such as basic mathematic method studying, specific models making, common models building, codes simplifying and examples testing with. At the end of it, conclusion was made about the performing of the code.
M.S. in Electrical Engineering, December 2012
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- Title
- Indirect illumination with nitrogen-filled lamps
- Creator
- Adamson, J. Priece, Borroughs, Walter L, Wright, Chester F
- Date
- 2009, 1915
- Publisher
- Armour Institute of Technology
- Description
-
http://www.archive.org/details/indirectillumina00adam
Thesis (B.S.)--Armour Institute of Technology, 1915 B.S. in Electrical Engineering, 1915
- Title
- MOTION ESTIMATION METHODS FOR RESPIRATORY GATED SPECT
- Creator
- Hurtado Jaramillo, Juan Sebastian
- Date
- 2014, 2014-12
- Description
-
Single photon emission computed tomography (SPECT) is a type of nuclear imaging test that is used for detection of cardiac diseases....
Show moreSingle photon emission computed tomography (SPECT) is a type of nuclear imaging test that is used for detection of cardiac diseases. Unfortunately it suffers from several image degrading factors, including respiratory motion, that can affect the accuracy of diagnosis. Four-dimensional (4D) respiratory gated SPECT helps to correct this issue by performing the acquisition at several intervals and applying motion-compensated reconstruction methods. With this in mind, and to improve 4D reconstruction, three different motion estimation methods (i.e., optical flow equation, center of mass, and template matching) are applied in this project. Three different sets of dose levels are simulated using NCAT and one set of clinical data is used. The results for motion estimation on simulated data show that the template matching methods have better performance overall. Additionally, noise reduction by means of a spatial smoothing filter helps on the reduction of the average error. Rotational motion estimation using principal component analysis (PCA) was also studied to examine if there can be improvements over the translational motion methods. The initial outcome is that there is a small rotation that can be detected on the ideal reconstruction; the compensation of this rotation also helps to reduce the error obtained from translational motion, albeit by a small margin. Unfortunately, the same cannot be said when noisy reconstructions were used.
M.S. in Electrical Engineering, December 2014
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- Title
- EVALUATION OF TIME-FREQUENCY DISTRIBUTIONS FOR ULTRASONIC IMAGING APPLICATIONS
- Creator
- Lu, Juan
- Date
- 2013-05-01, 2013-05
- Description
-
This thesis presents the performance evaluation of generalized time-frequency distributions (GTFD) and model-based time-frequency (TF)...
Show moreThis thesis presents the performance evaluation of generalized time-frequency distributions (GTFD) and model-based time-frequency (TF) estimation of ultrasonic signals. Two new TF distributions which are related to generalized time-frequency distribution have been examined. These methods are singular value decomposition of Choi-Williams distribution (CWD-SVD), and 2D (time and frequency) Gaussian kernel applied to generalized time-frequency distribution. The application of Short-Time Fourier Transform (STFT) is studied for chirplets estimation. Then, the Wigner distribution (also called the Wigner-Ville distribution) of estimated Chirplets yield a precise TF representation. The performance of the STFT, the Morlet wavelet transform, the Wigner distribution (WD), the CWD and the CWD-SVD are compared. CWD-SVD is a very effective algorithm to keep the high clarity of the Wigner distribution and to suppress the undesirable cross-terms resulting from multi-component signals. The Gaussian echo model is used to obtain the analytical TF distribution. For CWD the proper range of exponential kernel parameter, , is attained. This range allows CWD to sustain a high concentrated auto-terms and significant suppression of cross-terms. For this range of the CWD-SVD extracts high clarity auto-terms and facilitate eliminating the residual cross-terms. To remove the cross-terms, singular value decomposition algorithm extracts basis functions corresponding to auto-terms. After discarding the basis functions and singular values of the cross-terms and noise, the basis functions and their singular values of auto-terms are used to reconstruct the TF distribution. The results of multi-component Gaussian echoes with significant time and frequency overlaps show that the CWD-SVD is able to eliminate residual cross-terms for xi which the CWD failed to eliminate. The numerical analysis of multi-component Gaussian echoes indicates that CWD-SVD has the ability to resist noise resulting in accurate estimates of center frequencies and arrival times. The generalized time-frequency distribution with 2D Gaussian kernel is able to separate two extremely close Gaussian echoes in the time-frequency domain. In this study, typical values of the 2D Gaussian kernel parameters for efficient cross-terms elimination are provided. The relationship between the kernel's parameters and Gaussian echoes' parameters is deduced. A practical method for TF analysis is to decompose the signal into sparse chirplets. Decomposition requires chirplet parameter estimation. In this study, the parameters of a signal which is composed of two overlapping chirplets are estimated using STFT. By this method the estimation results are found to be accurate confirming that the STFT is an effective method for decomposing and estimating chirplets in a multi-component signal.
M.S. in Electrical Engineering, May 2013
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- Title
- CONTROL OF DOUBLY-FED INDUCTION GENERATOR FOR WIND APPLICATION
- Creator
- Guo, Jing
- Date
- 2012-05-03, 2012-05
- Description
-
With growing concerns over environmental pollution and globe warming, renewable energy has received considerable attention as an alternative...
Show moreWith growing concerns over environmental pollution and globe warming, renewable energy has received considerable attention as an alternative energy resource of electricity production. Because of the immense potential of wind energy on the earth, wind power generation has gained significant popularity over recent years. From this research, it has been concluded that there is a constant need to reduce the size and rating of power electronic converters, improve efficiency of the electromechanical system and make the system more reliable by eliminating the gearbox. This thesis analyzes a doubly fed induction generator (DFIG) drive system for distributed wind generation systems. The structure of a doubly fed induction generator is similar to that of an induction generator. To illustrate the operation principle and control strategy of a DFIG clearly, the fundamentals and control principle of an induction generator have been discussed. For DFIG control, two closed control loops are designed-active power control loop and rotor speed control loop; and they can be switched between each other. By utilizing active power control loop, the output power of the system can be regulated to meet different customer requirements and their dependence on grid electricity can be eliminated, therefore the cost and the power loss on transmission lines can be reduced. On the other hand, by switching to the speed control loop, the system can extract maximum power at different wind speeds, and any extra power can either be stored or sold to the utility for profit. To validate the proposed concept, Finite Element Analysis (FEA) models of a doubly fed induction generator and an induction generator have been built and simulated using the software Magnet®; furthermore, the control systems of these two generators are implemented and simulated in a Matlab/Simulink environment. Finally, a Magnet and Matlab/Simulink co-simulation has been performed for the DFIG. By analyzing the simulation results, the differences between the doubly-fed induction generator and an induction generator have been demonstrated.
M.S. in Electrical Engineering, May 2012
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- Title
- DISTRIBUTION SYSTEM STATE ESTIMATION
- Creator
- Li, Lingyan
- Date
- 2015, 2015-05
- Description
-
This thesis provides a novel method to improve distribution system state estimation by an effective approach to processing bad data in...
Show moreThis thesis provides a novel method to improve distribution system state estimation by an effective approach to processing bad data in measurements. The first part of this research is focused on modeling distribution system state estimation with bad data rejection capability. We apply transmission level model to the distribution level system with specific properties, such as fewer real measurement data for state estimation in the distribution level system, three phase unbalance power flow and so on. For building a robust state estimation model, we optimize the system in the following ways: First, we optimize objective function. We use forecasted load as pseudo measurements. Then we apply different weights to distinguish the forecasted data and actual measurements in the state estimation. Second, we apply three phase power equation in the analysis. We add real power, reactive power, active line power, reactive line flow, voltage magnitude, phase angle and others as nonlinear constraints in the three phase model of state estimation. Third, we flexibly change objective function and constraints in the state estimation model. We can change objective function when state estimation method changes. Meanwhile, we can add power flow and bus limitations in the optimization to avoid state estimation results exceeding power system limitations. Finally, we conduct hybrid calculation. In the first optimization, we filter the bad data. Then, we add another weight to reduce the bad measurement weight and enlarge the good measurement weight. After this process, we get optimized state estimation results. The second part focuses on the implementation of the model. We explain how to preprocess testing case data in this part. The third part is case study. We use IEEE 34 node feeder to test this model. There are four test cases. One test case has no bad data. Other cases have bad data in different types of measurements. We compare these cases with conventional WLS approach. The results obtained from simulation indicate our model has better performance when there is bad data in measurements.
M.S. in Electrical Engineering, May 2015
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- Title
- CYBER ATTACKS AGAINST STATE ESTIMATION IN POWER SYSTEMS: VUNERABILITY ANALYSIS AND PROTECTION STRATEGIES
- Creator
- Liu, Xuan
- Date
- 2015, 2015-07
- Description
-
Power grid is one of the most critical infrastructures in a nation and could suffer a variety of cyber attacks. With the development of Smart...
Show morePower grid is one of the most critical infrastructures in a nation and could suffer a variety of cyber attacks. With the development of Smart Grid, cyber security has become an area of growing concern. False data injection attack has recently attracted wide research interest. This thesis proposes a false data attack model with incomplete network information and develops optimal attack strategies for attacking load measurements and the real-time topology of a power grid. The impacts of false data on the economic and reliable operations of power systems are quantitatively analyzed in this thesis. To mitigate the risk of cyber attacks, a distributed protection strategies are also developed. It has been shown that an attacker can design false data to avoid being detected by the control center if the network information of a power grid is known to the attacker. In practice, however, it is very hard or even impossible for an attacker to obtain all network information of a power grid. In this thesis, we propose a local load redistribution attacking model based on incomplete network information and show that an attacker only needs to obtain the network information of the local attacking region to inject false data into smart meters in the local region without being detected by the state estimator. A heuristic algorithm is developed to determine a feasible attacking region by obtaining reduced network information. This thesis investigates the impacts of false data on the operations of power systems. It has been shown that false data can be designed by an attacker to: 1) mask the real-time topology of a power grid; 2) overload a transmission line; 3) disturb the line outage detection based on PMU data. To mitigate the risk of cyber attacks, this thesis proposes a new protection strategy, which intends to mitigate the most damaging effect of LR attacks on power system operation. The objective is to mitigate the damage effects of false data injection attacks by increasing the attacking cost of an attacker. This is achieved by protecting a small set of critical measurements. To further reduce the computation complexity, we also propose a mixed integer linear programming approach to separate the power grid into several subnetworks, then distributed protection strategy is applied to each subnetwork. The results of this thesis reveal the mechanism of local false data injection attacks and highlight the importance and complexity of defending power systems against false data injection attacks.
Ph.D. in Electrical and Computer Engineering, July 2015
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- Title
- DEVELOPMENT OF A MOBILE AD-HOC NETWORK USING WI-FI DIRECT OVER ANDROID PLATFORM
- Creator
- Liu, Kecheng
- Date
- 2015, 2015-12
- Description
-
The proliferation of smart phones enables ubiquitous Mobile Ad-hoc Networks (MANETs) where mobile devices communicate with peers over a...
Show moreThe proliferation of smart phones enables ubiquitous Mobile Ad-hoc Networks (MANETs) where mobile devices communicate with peers over a wireless channel in an ad hoc mode. In this paper, we introduce a novel method to achieve multi-hop communication among open-source, non-rooted Android devices using Wi-Fi Direct Technology (also known as Wi-Fi Peer-to-Peer (P2P» . We then implement an MANET with proactive routing using device s MAC addresses by conducting experim ents using off-the-shelf smartphones.
M.S. in Electrical Engineering, December 2015
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- Title
- TEMPORAL AND SPATIOTEMPORAL MODELS FOR SHORT-CRIME PREDICTION
- Creator
- Liu, Xiaomu
- Date
- 2017, 2017-07
- Description
-
One of the most important aspects of predictive policing is identifying the likely time and place of crime occurrences so as to prevent future...
Show moreOne of the most important aspects of predictive policing is identifying the likely time and place of crime occurrences so as to prevent future crimes. The ability to make short-term predictions may be of particular importance for optimizing police resource allocation. The goal of this study is to investigate the temporal and spatiotemporal pattern of crime in the city of Chicago and to build corresponding predictive models. First, a temporal model for forecasting citywide violent crime time count is proposed. This model is composed of a long-term trend and short-term variations using data of time, weather and crime. The importance of model reproducibility is addressed in this study to produce low-complexity models. We introduce an approach that provides a way to extend the model selection criterion to both prediction accuracy and model reproducibility. The experimental results show that models produced by this approach outperform several simple time-series models. It is also found that these models typically include fewer variables; therefore, they are more interpretable, and may provide superior generalization error. Next we develop a framework that provides predictions for tomorrow’s violent crime counts at the level of a police district. The procedures include citywide daily violent crime count prediction, violent crime density estimation, and distributing citywide predictions to districts according to the estimated densities. In order to estimate the crime spatial densities, we use mesh modeling and demonstrate that a mesh model can be used as the structure for modeling the spatial variation of crime rate since it is well adapted to the inhomogeneous crime distribution. The experimental results show that our method provides more-accurate forecasts than those given by historical crime statistics. One aspect of studying spatial pattern of crimes is identifying geographical regions with similar crime characteristics. Specifically, we illustrate applying unsupervised clustering techniques to segment the city into sub-regions. We explore the use of Gaussian mixture models combined with a Markov random field for the purpose of regularization. We also propose a framework for the evaluation of clustering models without knowing the ground truth, which can present a more-complete picture for model selection in unsupervised clustering problems. Finally, we develop a spatiotemporal prediction method that predicts the locations where violent crimes or property crimes are most likely to occur tomorrow. Crime incidents are rasterized by a spatiotemporal grid. Other factors that affect the time and location preferences of criminal activities are also leveraged and represented by that grid. Each spatiotemporal grid cell is treated as an example for training and testing our models. We also explore whether pooling data from various sub-regions based on spatial clustering can improve model performance. The experimental results show that our models are more accurate than conventional hot-spot models. It is found that the effects of using different training samples are not consistent, which depends on target crime type.
Ph.D. in Electrical Engineering, July 2017
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- Title
- License Plate Recognition in Complex Scenes
- Creator
- Wazalwar, Dhawal S.
- Date
- 2011-12-07, 2011-12
- Description
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License plate recognition is considered to be one of the fastest growing tech- nologies in the field of surveillance and control. In this...
Show moreLicense plate recognition is considered to be one of the fastest growing tech- nologies in the field of surveillance and control. In this project, we present a new design flow for robust license plate localization and recognition. The algorithm con- sists of three stages: i) license plate localization ii) character segmentation and iii) feature extraction and character recognition. The algorithm uses Mexican hat opera- tor for edge detection and Euler number of a binary image for identifying the license plate region. A pre-processing step using median filter and contrast enhancement is employed to improve the character segmentation performance in case of low resolution and blur images. A unique feature vector comprised of region properties, projection data and reflection symmetry coefficient has been proposed. Back propagation artifi- cial neural network classifier has been used to train and test the neural network based on the extracted feature. A thorough testing of algorithm is performed on a database with varying test cases in terms of illumination and different plate conditions. The results are encouraging with success rate of 98.10% for license plate localization and 97.05% for character recognition.
M.S. in Electrical Engineering, December 2011
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- Title
- Lightning arresters and schemes for testing
- Creator
- Morey, C. R., Oehne, T. C. Jr
- Date
- 2009, 1908
- Publisher
- Armour Institute of Technology
- Description
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http://www.archive.org/details/lightningarreste00more
Thesis (B.S.)--Armour Institute of Technology
- Title
- INDUCTION MOTOR MODELING FOR ELECTROMECHANICAL DYNAMIC SIMULATION AND ELECTROMAGNETIC TRANSIENT SIMULATION
- Creator
- Aserkar, Chandrahas
- Date
- 2011-11-21, 2011-12
- Description
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The initial part of this research work focuses on distribution power flow for agent based distribution systems. Power flow analysis is an...
Show moreThe initial part of this research work focuses on distribution power flow for agent based distribution systems. Power flow analysis is an essential tool for power system planning and operation. Traditionally, most distribution systems are radial or weakly meshed types. Faced with the power markets of today, increasing requirements for reliability and ongoing distributed generation have meant that the structure of the distribution systems has become more complex. Also, with the advent of smart- grid technology, distribution automation and micro-grids, the distribution systems are focusing towards distributed control with the use of smart switches via agents. Thus the need for power flow analysis in such systems becomes more important than before. The forward-backward sweep method is a very popular method for distribution power-flow analysis. But, the traditional forward-backward sweep method focuses on the load flow solution based on the bus-injection to branch-current (BIBC) matrix, which is calculated considering the network topology. For distribution systems focus- ing on distributed control, the complete distribution network topology is unknown to any one agent and hence the complete BIBC matrix is not formed. Rather, the property of these agents to communicate with each other is exploited to obtain the power flow solution. Here, we focus on altering the network topology based algo- rithm for forward-backward sweep method so as to make it suitable for agent based distribution systems. The later part of this research work focuses on development of induction motor load models for transient dynamic stability simulators (TS) and electromagnetic tran- sient simulators (EMT), to study the voltage stability of power systems. A Transient Stability simulator runs at a larger time step and is used to study relatively slower dynamics in the system. On the other hand, an Electromagnetic Transient simulator uses a smaller time step to capture the fast dynamics in the system. A combined TS-EMT simulator attempts to model the bulk of the system as a slowly varying dynamic system and a small portion of the system for which the fast dynamics are to be studied, with an electromagnetic transient model. Load modeling is a very important aspect for studying power system stability. Power system stability is the property of a power system that insures the system remains in electromechanical equilibrium throughout any normal and abnormal oper- ating conditions. It is thus defined as the ability of designated synchronous machines in the system to remain in synchronism with one another following disturbance at various locations in the system. It also indicates the ability of induction motors in the system to maintain electrical torque to carry the load following these disturbances. This research work provides a detailed modeling of the induction motor for electrome- chanical as well as electromagnetic transient simulations and uses them to study the effects of composite load models on power system voltage stability.
M.S. in Electrical Engineering, December 2011
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