http://localhost:8081/jspui/handle/123456789/28 2025-06-30T18:47:38Z http://localhost:8081/jspui/handle/123456789/15783 Title: INVESTIGATION ON SIX-PHASE SELF-EXCITED INDUCTION GENERATOR Authors: Singh, Kiran Abstract: Multi-phase /high phase number (more than 3Φ) systems are potential alternative to their three phase counterpart systems in respect of various beneficial advantages for high power electric applications. The affectionate utilization of renewable /non-conventional energy resources in fuel redemption had a need of low cost and appropriate generating systems in enlivening the small /large scale industrial applications and variety of future energy demands. Stand-alone /isolated induction generators are attractive substitutes having numerous relative advantages over the well-known synchronous generators in electric power generation in conjunction with non-conventional energy resources. The cost effective utilization of advantageous features during isolated mode in induction generator technology had opportunity to supplement the electric power from different site resources to underprivileged far-flung and remote areas. So, investigation on six-phase self-excited induction generator (SP-SEIG) has taken place during past decades for exploiting the propitious features of multiphase machines conjointly stand-alone self-excited induction generators (SEIG) in the area of non-conventional energy generation for being a viable alternative over other generating systems. Apart from literature, which interpret correlations among the machine parameters and variety of variables in multi-phase (six-phase) isolated mode of SEIG, further, efforts are made to draw special attention to highlight other potential issues related to the use of SP-SEIG (when both 3-Φ sets are designed with 30° displacement and their neutrals are isolated) in aspect of present and future development. As compared to existing new methodology, conventional techniques used during last several decades focus on modelling and analysis of SP-SEIG to analyze the steady state and dynamic performance of simple and compensated SP-SEIG during balanced /unbalanced conditions. Steady-state study is needed for ensuring good quality power and assessing the suitability of different configurations of SEIG. Transient behaviour during dynamic analysis provides the knowledge about the suitability of capacitor ratings, machine winding, and its insulation level for protection purpose. Small signal stability analysis is requisite to deliberate the stability of proposed system when each machine variable goes through small disturbances from its reference value by using popular techniques. An appropriate controller design and analysis is also carried out on simple SP-SEIG during consumer load variations for ensuring good quality power delivery in small reasonable generating system by a new technique. In steady state analysis, a simple technique along with machine data is contemplated to predict the saturated magnetizing reactance ‘Xm’ and per-unit frequency ‘F’. The steady state performance deals with a mathematical matrix model of simple and compensated six-phase self-excited (isolated) induction generator (SP-SEIG) using loop impedance method, based on graph theory from its per unit representation of per-phase generalized equivalent circuit, to ii study the comparative steady-state behaviour of different configurations. The machine voltage regulation are enhanced by employing supplementary series capacitors within short-shunt and long-shunt configurations in self-excited induction generator ‘SEIG’. The resultant matrix model is simple and flexible for various future modifications. The optimization of ‘Xm’ and ‘F’ variables of generalized matrix model are performed by using Newton-Raphson ‘NR’ routine based analytical technique for a variety of loading conditions and in different operating modes of fundamental configurations. Further, the computation of optimized ‘Xm’ and ‘F’ value participates in the estimation of various machine performance parameters. Steady state study is also needed for initializing the dynamic and transient simulation. During dynamic analysis, a popular two axis (dq0) model of a saturated simple and compensated multi-phase (six-phase) self-excited induction generator (SP-SEIG) is constructed by park’s transformation using mixed (stator current and magnetizing flux) state variables. The model is characterized with very simple system matrix in which only four elements could be dependent on saturation, when considered. Mixed stator current and airgap flux state space model possesses the advantage of having variable speed operation under variable magnetizing flux level in the machine. Under variable speed operating conditions, flux level in the machine needs to be modelled accordingly that accounts for the main flux saturation. This mixed stator current and air-gap flux as a state-space variables model preserves the information about both stator and rotor parameters. On the other perspective, considerably simpler than d-q axis winding current model and has simple matrix. This saturated machine model is mostly applied in air-gap flux field oriented vector control strategy. In transient behaviour analysis, performance equations in dynamic model utilize the steady state magnetizing inductance ‘Lm’ along with dynamic inductance ‘L’ rather than saturated magnetizing inductance ‘Lm’ and its derivative. During analysis, the effects of common mutual leakage inductance between two three-phase winding sets and cross saturation coupling between d- and q- axis of stator have not been considered. Differential equations has been computed with an explicit MATLAB algorithm for the implementation of 4th order Runge-Kutta ‘RK4’ subroutine. Proper values of shunt capacitor avoid the excessive voltage at the terminals of SP-SEIG under loading condition. A careful value selection of the combination, i.e. shunt and series capacitors also eliminates the enormous terminal voltage when switching the load, and can maintain the no-load voltage because of extra reactive power supplied by the series capacitors. The involvement of series capacitors satisfy the requirement of voltage regulation when load is suddenly switched on after few second and retains the no-load terminal voltage as per self-regulating nature. The stability investigation in this thesis reveals that the eigenvalues are dependent upon the machine parameters and variables. The most critical parameter is the variation in iii magnetizing inductance ‘Lm’, which focuses on stabilization of SP-SEIG. Firstly, Taylor series is applied to linearize the nonlinear equations of the machine; secondly, Eigenvalue basic criterion is used to find out the machine eigenvalues about small deviation using a group of higher order equations from the linearized SP-SEIG model during balanced operating condition. Lastly, the nature and magnitude of eigenvalues are correlated with the machine parameters and variables under no load and different loading conditions which provide a ground in the study of machine stability. So, the eigenvalue behaviour of a six-phase selfexcited induction generator is varied in accordance with small deviations of machine parameters and variables for determining its small signal stability analysis. Further, two transfer functions between the mechanical input torque and small changes in active power and reactive power have also been established to identify the machine stability by graphical means. Generator terminal voltage and frequency are also markedly affected by the excitation capacitor, connected load and rotor speed at renewable energy plants in remote sites or developing countries. On faults due to abrupt reduction in torque during short circuits, machine speed may accelerate and tends towards terminal voltage collapse with the immediate increase in reactive power of self-excited induction generator. So, there is need of control in extreme values of generator terminal voltage and frequency during variations in machine load characteristics or prime mover speed, and also need of speed control during faults in system. For enhancement in voltage and frequency regulation of SEIG, there are others different power electronics aid controllers. Power electronics aid controller are efficient, fast and up-todate which facilitates a new birth and growth in to previous terminal voltage and generated frequency ‘Voltage and Frequency’ control schemes of self-excited induction generator during various operating conditions and /or in variable speed applications of SEIG when there is no governor control in small energy generating plants. Before, voltage and frequency control of 3- phase isolated induction generator was in consideration for researcher, here attempt is control of voltage and frequency of 6-phase isolated induction generator i.e. SP-SEIG. Various isolated /capacitor-excited induction generator control techniques are in practice today. The most simple and popular control technique is by generating variable frequency supply which has constant voltage to frequency ratio. The constant ‘voltage to frequency ratio’ technique is popularly known as V/F control scheme, in which voltage is proportional to system frequency for keeping flux remains constant in control process. Similarly, a constant ‘voltage and frequency’ or ‘V and F’ or ‘volt and hertz’ new strategy controller and its scheme should be designed and formulated, respectively, for the sake of maintaining desired power quality, in spite of variations in consumer loads. Simplified and moderate Simulink model for voltage and frequency control of isolated six-phase induction generator can keep the terminal voltage and generated frequency remain constant so that generator output power remains constant. iv Complete Simulink model has SP-SEIG, controller and its control scheme, and static load arrangement which retains the voltage and frequency almost fixed with marginal drop in machine speed during variations in consumer energy demands. A new control strategy in voltage and frequency controller of SP-SEIG supplying static load is described with two closed control loops. V and F (volts and Hz) controller consists of current controlled voltage source inverter (CC-VSI) and a high frequency DC chopper. Both keeps the generated voltage and frequency constant against changes in load characteristics. Simulation outputs depict the constant generated voltage and frequency with change in load characteristics. In this way, proposed controller behaves as frequency and voltage regulator. Simplified Simulink model possess control scheme which generates gate drive signals to IGBTs switches of VSI and chopper switches. Simulink model of voltage fed controller ‘VFC’ has two PI controllers, first is to regulate AC terminal voltage (Vt) and second is for regulating DC bus voltage of VSI. First, a mathematical model of SP-SEIG supplying static load is derived under transient and dynamic conditions. Then, model of D.C. side of inverter along with current controlled voltage source inverter is developed for the control purpose of SP-SEIG. Having two PI controllers in Simulink model, it has complex functionality which is overlooked by its reliable and goal accomplished output performance. An Outlook on whole research work involves change of variables approach revolutionized by R.H.Park in late 1920s. Park’s theory has served as the advantageous theoretical foundations for the equations of transformation in arbitrary reference frame (proposed reference frame is stationary) in the analysis of SP-SEIG. Steady-state modelling using loop impedance and graph network theory; Steady-state analysis using NR numerical technique; Dynamic modelling using mixed variable approach; Transient analysis using conventional RK4 algorithm; Stability analysis by using an eigenvalue criterion in addition to standard (Rootlocus) graphical tool, and, V and F control of SP-SEIG is carried out by using a new strategy. Although, NR numerical technique and RK4 algorithm are not seeding well in the computational analysis, yet not obsoleted being simple, fast and effective if initial guesses are perfectly chosen. Thesis task presents an opportunity to focus on following performances of SP-SEIG under balanced or unbalanced and resistive ‘R’ or resistive-inductive ‘R-L’ static loads to analyze the performance parameters of simple-shunt and compensated SP-SEIG.  The steady state analytical machine performance results obtained by the proposed schemes are compared. Steady state initial values of few machine variables have been used for dynamic and transient analysis. v  Analytical dynamic and transient performance results are found for the R and RL loading on the machine system. In both the cases (R and R-L loading), the voltage drops are unequal and marked when variation from no load to full load.  Stability is also an important factor being considered to investigate the effect of given values of excitation capacitance, speed and loads. Root-locus graphical tool create an opportunity to observe the behaviour of characteristic roots (or eigenvalues or latent roots) in the s-plane.  Besides the assistance of isolated /capacitor excited induction generator, it has two crucial deficiencies for need of extra reactive power during faults and loss of excitation during abrupt change in machine load or prime mover speed. Capacitor excitation survives when there is almost constant system load or prime mover speed. So, a new controller scheme is employed for constant ‘volt and hertz’ or rotor speed for only one particular R loading to demonstrate an introspective spotlight on new strategy being applied in to the Matlab Simulink model of voltage and frequency controller of SP-SEIG. 2018-06-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/15782 Title: FUSION OF MULTIMODAL NEUROLOGICAL IMAGES Authors: Singh, Sneha Abstract: Medical imaging plays a vital role in modern medicine. With the advent of modern technology, there is a tremendous improvement in the capabilities of several medical imaging modalities such as X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) and functional imaging modalities such as single photon emission computed tomography (SPECT), positron emission tomography (PET) etc. which are extensively prescribed by the clinicians/radiologists for diagnosis purposes. In usual, the diagnostic procedures based on the perception of medical images are performed in a subconscious way which is based on the conclusion drawn upon how the clinicians understand and interpret them. However, due to several sources of medical images used by the clinicians and radiologists, a big problem of information overloading occurs. Moreover, none of the medical imaging modality is able to provide comprehensive and accurate information, especially in critical diseases such as brain hemorrhage, tumor, cancer, other nervous system disorders, any accidental injuries, etc. For example, anatomical imaging (CT/MR) provides morphological information about the human body, but do not reflect the functional status, whereas functional imaging (SPECT/PET) provides the physiological information, but do not reveal anatomical information. Therefore, it is necessary to correlate one modality of medical images to other to provide the significant diagnostic information that requires lots of years of experience and this process is very rigorous, costly and time consuming and has the chance of lots of human errors. Moreover, the advanced imaging modalities prescribed by the doctors multiple times, are too much costlier that also puts an extra financial and mental burden on an individual. Therefore, there is a need to develop some effective multimodal medical image fusion (MIF) approaches to merge all of the features taken from each of individual modality into a single composite fused image that has a significant clinical information and is suitable for the effective diagnostic analysis. Thus, in the above perspective, the medical image fusion algorithms should fulfil the following three principal criteria: 1. The MIF algorithm must be capable to preserve maximum diagnostic information from the input images with perceptible visual quality and without introducing any spatial and spectral distortion. 2. The true tissue information either anatomical or functional, including the edges and other diagnostic details should also be reflected properly. 3. The fusion algorithm must be computationally efficient, stable and robust. With the above background, the main objective of the present research work has been chosen as to design and develop the effective fusion approaches by integrating all the complementary and contrasting information from the different image datasets of same organ and tissues so that the fused image is more useful and acceptable to the human visual ii system and machine perception. Accordingly, the entire research work has been planned and carried out under the following two major objectives. 1. A comparative evaluation of several existing fusion approaches has been carried out and new efficient CT and MR image fusion approaches have been designed, developed and implemented to improve the fusion performance by preserving the clinically relevant information present in the source CT and MR images with higher contrast level and without introducing any artifacts. 2. Based on the post-analysis of the existing and developed fusion approaches, new suitable anatomical and functional (MR, SPECT, PET) image fusion approaches have been designed to reflect the anatomical details produced by the MR/CT images without disturbing any functional status of the tissue reflected in the SPECT/PET images. In order to achieve the first objective of the initial phase of work by developing and implementing the MIF approach, three different fusion techniques are proposed in the present work that will also lead to fullfil the different sub-objectives. Based on the prominent features and advantages of multiscale transformation techniques presented in the literature, the first fusion approach based on the nonsubsampled shearlet transform (NSST) is proposed in the present work. In the proposed NSST domain medical image fusion (NSST-MIF), anatomical (CT-MR) image fusion is performed in the NSST domain using a modified pulse coupled neural network. The proposed fusion approach incorporates the regional energy (RE) based activity level measure to fuse the low frequency (𝑙𝑓) NSST coefficients and novel sum modified Laplacian (NSML) motivated PCNN to fuse the high frequency (ℎ𝑓) NSST components which help to reflect more amount of informative contents present in the source CT and MR images. The performance of the proposed approach is compared with eight different fusion approach in which WT, NSCT and NSST with different fusion rules such as averaging of 𝑙𝑓 coefficient fusion, maximum and spatial frequency motivated PCNN based ℎ𝑓 subband fusion are utilized. Their performance is not only analyzed and evaluated in terms of visual perception, but also in terms of different performance measures such as entropy (En), standard deviation (STD), mutual information (MI), spatial frequency (SF), image quality index (IQI) and Xydeas edge index (XEI). Based on the experimental results, it is observed that the proposed NSST-MIF approach is able to fuse the CT and MR images in a better way without distorting the information and showing a significant improvement in detectability of the source images. Based on the findings obtained from the results presented in the literature, it observed that the curvelet transform also produce better results, however, it uses a parabolic scaling law to resolve the two-dimensional singularities along 𝐶2 curves. To represent the diagnostic edge detail more efficiently, discrete ripplet transform with two new additional iii parameters is utilized in second proposed fusion approach which provides a new tight frame with a sparse representation for the source images with discontinuities along 𝐶𝑑 curves, where 𝑑=2 refers to parabolic scaling the same as curvelets and 𝑑=3, refers that ripplet has the cubic scaling and so forth. In the second proposed image fusion approach named as DRT-MIF, firstly, DRT has been applied to decompose the source images, individually in one 𝑙𝑓 and several ℎ𝑓 ripplet components which are fused by computing NSML and novel sum modified spatial frequency (NMSF) motivated PCNN model that is able to capture the fine details present in the reference images. This model helps to preserve redundant information also. The PCNN model is utilized for 𝑙𝑓 and ℎ𝑓 DRT coefficients based on the firing times and improved feeding inputs as NMSF for ℎ𝑓 components and NSML for 𝑙𝑓 ripplet subband. Fusion rules help to capture the suitable differences and provide the resultant images with high contrast and clarity. Finally, fused images are reconstructed by applying the inverse DRT. The results of the proposed DRT-MIF method is compared with wavelet transform (WT), nonsubsampled contourlet transform (NSCT) and NSST with PCNN based fusion approaches including the proposed NSST-MIF. It is observed from their comparative results that the proposed DRT-MIF approach provides a better quality of fused images by preserving the edge and important morphological information. Moreover, the proposed approach provides higher values of En, MI, SF and XEI than NSST-MIF and other existing fusion methods. Based on the analysis of experimental results obtained earlier in two proposed fusion methods, it is observed that both, the NSST and DRT both the decomposition methods provide better fusion results. DRT helps to reflect the higher-order singularities whereas, NSST overcomes the problem of shift-invariance and helps to lose the important information. Considering their motivation, a cascaded medical image fusion (C-MIF) framework has been proposed for CT and MR images in DRT and NSST domain. At the first stage decomposition, a PCNN model motivated by different feeding inputs such as NSML and NMSF is utilized to fuse the 𝑙𝑓 and ℎ𝑓 DRT coefficients, respectively. The NSST decomposition is used in the second stage where regional energy is computed to fuse the 𝑙𝑓 NSST approximation coefficients and for ℎ𝑓 NSST detail coefficients, the sum of absolute difference (SAD) and absolute maximum (AM) based fusion rules are applied to provide the richer representation of the edge detail information with improved contrast, respectively. The fusion performance of the proposed C-MIF approach is validated by extensive simulations performed on a different CT-MR image dataset and a detailed comparison is made with WT, dual-tree complex wavelet transform (DTCWT), NSCT, NSST, stationary wavelet transform (SWT) decomposition based and other fusion approaches. It is observed from their comparative analysis that the C-MIF approach gets more informative content in the fused image by computing higher values of En and MI as compared to the others. Moreover, the C-MIF iv approach ensures to retain the contrast and edge detail information by producing higher STD, SF and XEI values than others, thus providing the fused images with better visual quality. In order to achieve the next objective of the present work, four different multimodal image fusion methods are proposed to fuse MR-SPECT, MR–PET along with CT-MR Images. All these four MIF approaches are developed and implemented in such a way that all these methods help to provide more robust and clean structural detail information without introducing any artifacts and without altering the functional information of the tissue reflected in the source images. To achieve the fusion of anatomical and functional images, an improved fusion approach has been proposed that uses the entire features extracted by NSST and adaptive PCNN model (ADPCNN) to retain the desirable contrast and detail information in the fused results. In the proposed approach (ADP-MIF), the ADPCNN model is applied to fuse the 𝑙𝑓 NSST decomposed coefficients with adaptive linking strength parameter based on local visibility and NSML motivated feeding input which helps to provide higher sensitivity and clarity in the visual perception. For fusing the ℎ𝑓 NSST coefficients, a local log Gabor energy (LLGE)-based fusion is used to extract optimal texture feature with broad spectral information. The fusion performance is compared with existing fusion methods. It is observed from the fusion results that the proposed ADP-MIF approach is able to reproduce the significant visual information with the preservation of structural and spectral content and provides a clear picture of edge details available in the source images. Furthermore, the fusion performance of the proposed ADP-MIF approach is also compared with twenty seven existing image fusion methods for CT-MR images. From the results, it is concluded that the proposed ADP-MIF approach helps to provide a significant improvement in terms of the visual quality of fused images by providing additional diagnostic information especially for the fusion of anatomical with functional images. In the next proposed fusion approach, a hybrid multimodal medical image fusion (H-MIF) approach based on the NSST and SWT decomposition has been proposed for the anatomical with functional and anatomical with anatomical images. In the proposed approach, SWT is applied only on the 𝑙𝑓 NSST subband and letting the ℎ𝑓 NSST components to remain the same. After SWT decomposition, another 𝑙𝑓 and ℎ𝑓 SWT subbands are produced. To fuse the 𝑙𝑓 SWT coefficients, an ADPCNN model motivated by NSML based fusion rule is utilized while LLGE based fusion rule is applied for ℎ𝑓 SWT coefficients to extract the salient features available in the source image and to retain the color and edge details without introducing any artifacts. Finally, AM and SAD based fusion rules are applied to remaining ℎ𝑓 NSST subbands to retain more information related to edge details. The proposed H-MIF maintains the spatial and spectral details well with sharp minute v details shown by higher scores of En and IQI. The higher values of FMI obtained for the proposed method indicate that the brighter minute features in source images are preserved properly with the appropriate consistency and localization. Moreover, similar performance has also been reflected for CT-MR image fusion by the proposed H-MIF approach that achieves good complementary information with more structural details but it suffers from contrast reduction of fused images having lower STD value that may be acceptable with its ability to retain more diagnostic information. Based on the results and limitations (chromatic imbalance, overbrightness, sensitive to random noise, etc.) of the state of the art methodologies, a unified multimodal fusion framework named as SDL-MIF has been proposed here using multiscale geometric analysis with sparse representation (SR) and guided filtering. The proposed SDL-MIF approach is based on the sparse K-SVD dictionary learning and guided filtering in the NSST domain in which an overcomplete dictionary is learned (training of medical image dataset) to capture complex details of medical images and sparsely represented 𝑙𝑓 NSST subband for better visual feature (luminance, contrast) projection without any spectral distortion. Fusion rule using a dictionary learning (DL) based SR is utilized to improve the comprehensive information in 𝑙𝑓 NSST subband, while guided filtering based rule is adopted to fuse ℎ𝑓 NSST subbands, which is able to extract the salient features from the source images and reflect color and edge detail properly in the fused outcomes without incorporating any artifacts. Several experimental results are performed on MR-CT, MR-PET and MR-SPECT dataset to validate the proposed SDL-MIF method and showed a detailed comparative analysis with the other available fusion methods. Based on the comparative experimental results, it is observed that the proposed SDL-MIF method is able to preserve the significant information of multimodal input images by producing better visual quality of fused images with improved contrast. In the next fusion approach, a feature level multimodal image fusion framework (CNN-MIF) has been proposed using two-scale ℓ1−ℓ0 hybrid layer decomposition with convolutional neural network (CNN) based feature mapping and structural patch clustering. In the proposed CNN-MIF approach, ℓ𝑛-norm based two scale hybrid layer decomposition is utilized to preserve the desired edges and intensity variations at each scale. A pre-trained CNN model followed by consistency verification is used to extract the prominent features from each of the decomposed base layer components and to generate the pixel activity and fusion weight map. For each output feature map, RE based activity measure is computed and refined in the consistency verification step to optimize the activity weight map for merging the decomposed base layers. The two-scale detail layers are merged by utilizing clustering based pre-learned multichannel dictionary with saliency matching rule to efficiently map the structural details of the layers. Moreover, the color components associated with both vi the source images are also combined using pixel saliency measure and finally all three components, i.e. fused base layer, fused detail layer and color component get merged to reconstruct the fused image. From the experimental results, it is observed that the proposed CNN-MIF approach highlights the ability to preserve the layer information (structural, fine details, brightness, and color) and increases fusion accuracy. A ℓ𝑛-norm based two-scale hybrid layer decomposition method is used to separate out the main information from the textural details in the spatial domain. The experimental results also show that the proposed CNN-MIF approach can efficiently extract the complex structure and maintains the spectral information as well without introducing any processing artifacts. It is further observed that the proposed CNN-MIF approach achieve higher performance measures than the other fusion approaches which itself signifies an improvement in the results of the proposed CNN-MIF approach. For the purpose of implementing and evaluating the performance of the above discussed proposed methods, the multimodal CT, MR, SPECT and PET neurological images were acquired from the multimodal image database available at Harvard whole brain atlas (http://www.med.harvard.edu/AANLIB/home.html). 2019-08-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/15781 Title: IMPROVED SCHEMES FOR BUSBAR AND BREAKERFAILURE PROTECTION Authors: Jena, Soumitri Abstract: Electric power substations across the globe have undergone immense transitions in the past decade. With the introduction of state-of-art modern equipment and power elec- tronics overhaul, complexity of busbar con gurations has been signi cantly increased. Busbar in a substation, as a converging point of transmission lines and connection point of sophisticated equipment, requires meticulous and reliable protection. Though busbar faults are relatively fewer, the consequences are severe in terms of damaged equipment and widespread supply interruption. These repercussions alarm protection engineers about the need for reliable and secure busbar protection. The high MVA levels, ex- tensive interconnections, complex arrangements, and safety of connected equipment further necessitates faster operation of the busbar relay. Clearance of a busbar fault requires the opening of all line circuit breakers (CBs) connected to the busbar, which results in supply interruption in no small part of the power system. On the contrary, the consequences of an unprotected bus during a bus fault is catastrophic. The present practice is to reduce the fault clearance time of the relay rather than developing new arc extinction methods for the CBs. Hence, busbar protec- tion should be designed and implemented in such a way that it operates in every single instance of bus fault and avoids unwanted tripping because of any possible reason. Stability is another prime aspect while designing a bus zone relay as its mal-operation causes power outage to a large portion of the power system. Hence, bus protection is challenging in terms of reliability and speed. By implementing bus sectionalizers and duplicated bus arrangements, the part of the circuit to be interrupted can be minimized. An internal bus fault, in this case, disturbs only a smaller part of the substation and fewer components are a ected. Enhanced numerical data processing units introduce implementation of numerical relays into the area of busbar protection. They provide greater exibility and possible on-chip implementation of smart solutions. i Hence, choosing excellent mathematical analysis tools and algorithms has the utmost signi cance to provide highly reliable and fast busbar protection, which also ensures stable and secure operation of the entire grid. Further, to improve the system reliability, all the protection equipment are du- plicated at a substation. However, duplication of a CB is not suitable because of economic and functional constraints. A CB is monitored by Breaker-Failure Protec- tion (BFP) implemented as a supplementary function inside existing relays. For several years, power system engineering has provided realistic BFP as a local solution to high- voltage (HV) and EHV (EHV) systems. The role of BFP is to identify a failed breaker to interrupt current and to operate with a pre-de ned time delay. Owing to the lim- itations of current technology, such as inaccurate timers with slow-reset over-current elements, BFP has been historically seen as the main reason for mal-operation of large number of relays and subsequent blackout situations. Keeping the severe consequences of a busbar fault in mind, protection engineers try to clear the fault in the minimum possible time. This time must be within the critical fault clearance time as determined from the system stability point of view. With the shrinking of stability limits, a fast BFP function is more challenging to achieve. The total BFP time is decided from the worst-case scenarios of principal protection operating time, tripping time of primary breaker, and pickup/dropout time of BF threshold functions. Within the total BFP time of 10 - 12 cycles, often only one cycle is available for the BFP reset/response time in case of mal-operations. The recent developments in the eld of numerical re- laying, digital signal processing, and high-class Current Transformers (CTs) allow the implementation of improved BFP modules with substantial performance enhancement. The work presented in this thesis is concentrated upon the development of im- proved busbar and BFP techniques. In this work, using both numerical and statis- tical analysis such as LR, alpha plane characteristics, travelling wavefronts and dq- components, it has been demonstrated that the sensitivity and response speed of ex- isting busbar protection schemes can be improved. This work also emphasizes on the development of an integrated busbar and breaker-failure scheme that prevents the mal- operation from subsidence current. Furthermore, the probable on- eld implementation procedures and architectures of the proposed schemes has also been discussed in details. 2020-02-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/15780 Title: AUTHENTICATION OF DOCUMENT IMAGES Authors: Kumar, Parveen Abstract: The intense development and extensive evolution of multimedia technologies is a current trend, and progressively multimedia data are used to provide authentication of document images. This implies robustness of a digital image against any security breaches. Moreover, it also renders the service of providing authorization and verification of users for distinct type of services worldwide [1–4]. With the concurrent, continuous and progressive improvisations in modern steganalysis techniques, the security of the information stored in digital images is at potential danger [5, 6]. This report gives information about Writer Identification (WI) related problems [7, 8]. The goal of the research is to design authentication systems for predicting writer of a given sample image and answer certain questions regarding handwriting style, representation and performance of the models created by reducing the parameters involved for the same, along with minimizing human intervention in the process. The approaches used in this report raise certain questions in computer vision, for example, whether handwriting style of an individual can be characterized using various algorithms and what features must be used to represent the model and how can they be combined in these models. The proposed models were evaluated on different datasets, the computer algorithms being unaware of what was written on these datasets sample images. These methods have potential to make it feasible for practical applications like in forensic science, banking system, human identification etc. The term WI is used to identify a writer from handwritten images. In most of the languages, various types of symbols and signs have been employed for communication purposes in the present work. Generally, writer identification research is conducted using handwritten document in different languages such as English, Arabic, Devanagari, etc [9]. Handwriting-based WI is an active research area in pattern recognition and machine learning. There are many intermediate steps to identify the writers from handwritten documents, which are as follows; Design and development of distinct writer recognition methods and algorithms. Different feature extraction techniques and methods. Identify appropriate characteristics from the handwriting feature set. Evaluate handwritten image-based writer identification performance. 1 Features extraction and segmentation of an image plays significant role in many pattern recognition applications such as handwriting recognition and writer identification. Some of the feature extraction techniques that are used for WI are Global Wavelet-based features [10], Pattern-based features [11], Contour-based Orientation and Curvature-based features [12], Edge Structure Code (ESC) Distribution feature [13], Grid Micro-structure features [14], Curvature-free features [15], etc. Feature extraction is used to resize the vector dimension of the feature. If the feature vector is too large to process, it requires to be reduced to a set of features, called the feature vector, in order to improve the model’s efficiency. The extracted and selected features have appropriate information of the input data. Further, segmentation is the method of splitting a digital image into several sections (pixels) in image processing [16]. The fundamental objective of segmentation is to simplify or alter the image as required by the user. It is used as a pre-processing technique for many applications of pattern recognition. Several approaches have been developed for authentication of documents images by researchers during last few decades for enhancing authenticity [1, 3]. WI, Signature Verification [17, 18] and Presence of seal in the documents are some of the approaches to provide the authentication of document images [19, 20]. In the era of smart computation, artificial intelligence and machine learning play an important role to simplify the human lives by developing smart devices and systems. However, intrusion and falsification cannot be avoided. To ensure the identification, several recognition systems have already been developed, commercialized and functional at peak. Writer identification is one of the methods to identify the document writer. Statistics show that machine learning methods help in predicting the writer in a better way compared to humans. The advent of deep learning revolutionized the learning and improved the performance of systems exponentially. Though, deep learning computation is expensive, it outperforms the traditional methods. In the present research work, the existing features have been used and new feature extraction techniques have been developed, and these features are used to learn the model based on machine and deep learning to classify the document writer. The designed and developed proposed research scheme is illustrated in Figure 1. The contributions of the proposed work are as follows: i. A new model, Histogram Weight Transformation (HWT), is proposed for Writer Identification and Verification (WIV) that provides an authentication of handwritten document images. The model targets the drawbacks of traditional data analysis and 2 Writer Identification Models Datasets Performance HWT Model DCWI Model SEG-WI Model IAM Kannada Devanagari CVL IFN/ENIT Arabic IAM = 99.48 % CVL = 82.55 % Kannada = 98.25% Arabic = 45.95 % Devanagari = 99.87 % IAM = 97.80 % IFN/ENIT = 97.50 % Kannada = 99.80 % Devanagari = 99.90 % IAM = 97.27 % CVL = 99.35 % IFN/ENIT = 98.24 % Kannada = 100 % Devanagari = 87.24 % Figure 1: Designed and Developed Proposed Research Scheme. Histogram Symbolic Representation (HSR) approach. The majority vote technique is adapted to identify the writer of a document having multiple text-lines. ii. Next, a novel approach of feature extraction based on Distribution Descriptive Curve (DDC) and Cellular Automata (CA) has been presented and utilized in a new developed model to obtain high accuracy compared with recent techniques. Eventually, an efficient model, DCWI, for writer identification has been presented based on DDC and CA. iii. Furthermore, a Segmentation-free Writer Identification (SEG-WI) model based on CNN is proposed to identify the writer. The region selection mechanism is also developed to improve the overall performance of the model. The lexical similarity between two documents of different writers makes the training difficult, therefore, a new training strategy is suggested to train the model 2019-11-01T00:00:00Z