M.Phil / MS

Permanent URI for this collectionhttps://repository.cuilahore.edu.pk/handle/123456789/42

This collection archives the complete set of theses produced by students of the COMSATS University Islamabad, Lahore Campus.

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A HYBRID MAC LAYER PROTOCOL FOR HETEROGENEOUS WIRELESS BODY AREA NETWORKS
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2019) Hina Bushra; CIIT/FA14-REE-007/LHR; Dr. Ali Nawaz Khan; LHR TP 5627
The rapid advancements in wireless communication technologies and micro-electronics systems have fostered the development of small and intelligent micro-components that incorporate sensing devices and wireless communications into a single miniature circuit which is wearable or implantable inside the human body for medical and healthcare applications. These components when deployed over or across the body of subject communicate wirelessly to constitute Wireless Body Area Networks (WBANs). Since several WBAN nodes are sharing the wireless channel to report their collected data back to a base-station or sink node, the medium access mechanism must be robust, scalable, and energy efficient. Furthermore, it may also adapt to different data-rate requirements for different sensors in a heterogeneous WBAN. In this research, Adaptive Sleep and Dynamic GTS allocation algorithms in WBAN have been implemented and compared with the proposed protocol entitled Adaptive Dynamic MAC that takes into consideration number and type of sensors, variable data-rates and energy requirements through managing sleep/wakeup intervals for WBAN nodes and implementing adaptive schedules for communication within the network. Network performance is compared on the basis of network lifetime, throughput and channel utilization through analytical model that is also verified in a customized simulator. Simulation results are gathered by observing network performance under variable network energy conditions, change in the position of gateway node, and effect of heterogeneous sensor nodes on mentioned performance parameters. It has been shown that Adaptive Dynamic MAC performs better than Dynamic GTS Allocation framework in all mentioned parameters. Furthermore, proposed algorithm has better network lifetime and throughput characteristics in comparison to baseline Adaptive Sleep algorithm.
Diagnosis of Doubly Fed Induction Generator Inter-Turn Faults (ITF) in Wind Energy Conversion System
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2023) Anisa Sharif; SP20-REE-014; LHR TP 8686
The most often utilized wind turbine generators right now are Doubly Fed Induction Generators (DFIG). When compared to other generators, it offers significant benefits such as low mechanical stress, excellent system efficiency, and a variable speed constant frequency mechanism. Mechanical and electrical faults are the two categories into which DFIG faults exist. The stator inter-turn fault is one of the stator problems that are not detectable by traditional protective devices. This study focuses on the identification of stator inter-turn short circuit (ITSC) Faults in DFIG since it accounts for more than one-third of all DFIG faults. Because the DFIG system is nonlinear, estimating its states without linearizing the system is challenging. Many approaches, including adaptive extended Kalman filtering, Wavelet Transform, Hilbert-Hang Transform, and Neural Networks can be utilized to identify stator inter turn faults and produce reasonable results. These approaches are less precise and efficient because some of these techniques linearize the DFIG nonlinear model for fault identification. The Unscented Kalman Filter (UKF) is really a derivative-free strategy for nonlinear systems that outperform linearization-based Kalman filter algorithms in fault detection approaches. Because the UKF is a nonlinear estimate approach that solves directly without linearization, it produces more accurate results than the Extended Kalman Filter (EKF). In this contribution, the UKF is implemented to detect stator inter-turn faults in the DFIG. By creating and examining the electrical currents residual from the stator, the fault is detected. The outcomes of the simulation demonstrated how well the suggested technique performs in both the diagnosis of a high and a low value of the ITSC fault in the generator stator windings. Firstly, by applying the state space model equations we created both healthy and defective DFIG-based wind turbine models in Matlab/Simulink, and then we used the UKF to identify inter-turn faults and describe the UKF estimation response. Simulation results of the UKF and EKF are compared for performance Analysis. For the implementation of the proposed scheme, the state space model of DFIG in the dq-reference framework is used and the simulations are carried out in the MATLAB/Simulink environment. Although, the trade-off between accuracy and speed of estimation response has played an important role in deciding the most effective technique.