Sudharsan Engineering College

Pudukkottai, India

Sudharsan Engineering College

Pudukkottai, India
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Ganesan K.,Sudharsan Engineering College
Construction and Building Materials | Year: 2014

In this paper, the durability properties of self-compacting concrete (SCC) containing rice husk ash (RHA), metakaolin (MK) and a combination of MK and RHA (1:1 ratio) were evaluated and their relationships discussed. The durability properties of the various mixtures were studied. The results showed that SCC blended with RHA and a combination of RHA and MK showed a considerable improvement in durability than unblended SCC (100% OPC). However, the performance of SCC blended with MK was unsatisfactory in an acid environment. In addition, it was found that resistance to acid attack was directly related to the silica ratio (SR). © 2013 Elsevier Ltd. All rights reserved.

Sudha M.,Sudharsan Engineering College | Palani S.,Sudharsan Engineering College
Current Medical Imaging Reviews | Year: 2017

Background: Generally, the texture information stored in the natural scene images provide some vital clues to the image based on the applications include Content Based Image Retrieval (CBIR), scene understanding, assistive navigation and automatic coding. Still locating the text from complex background and recognizing the characters with different colors are the major issues in image processing applications. Methods: To overcome these problems, a new structure is proposed in this paper for detecting and recognizing the text strings present in the natural scene images. To execute an efficient framework, the preparation of an input image is necessary that contains two preliminary tasks. It includes preprocessing based on Gaussian filtering and preprocessing based on Histogram equalization. Moreover, an Edge based Intensity Aided Clustering (EIAC) is introduced to detect the text by using the Sobel operator. Then, the neuro-fuzzy algorithm is used classify the text and non-text portions. A new Rule-based Region Map algorithm is introduced for text segmentation, where the necessary features are extracted based on the Local Tetra Patterns (LTrPs). Finally, the characters are recognized with the help of Fuzzy based Relevance Vector Machine (RVMs) classification algorithm. Results: The simulation results obtained by the proposed method are compared with the existing techniques for proving the better performance. The results are analyzed in terms of sensitivity, specificity, accuracy, precision, recall, recognition rate and F-Measure. Conclusion: The proposed framework is fully based on the combination of text detection, classification, segmentation, feature extraction and character recognition. The major advantages of this paper are, accuracy, simplicity and easy to use. Moreover, it provides the best classification results, when compared to the existing techniques. © 2017 Bentham Science Publishers.

Natarajan U.,Kyungpook National University | Periyanan P.R.,Sudharsan Engineering College | Yang S.H.,Kyungpook National University
International Journal of Advanced Manufacturing Technology | Year: 2011

In the present trend, new fabrication methods for producing miniaturized components are gaining popularity due to the recent advancements in micro-electro mechanical systems. Micro-machining differs from the traditional machining with the small size tool, resolution of x-y and z stages. This paper focuses RSM for the multiple response optimization in micro-endmilling operation to achieve maximum metal removal rate (MRR) and minimum surface roughness. In this work, second-order quadratic models were developed for MRR and surface roughness, considering the spindle speed, feed rate and depth of cut as the cutting parameters, using central composite design. The developed models were used for multiple-response optimization by desirability function approach to determine the optimum machining parameters. These optimized machining parameters are validated experimentally, and it is observed that the response values are in good agreement with the predicted values. © 2011 Springer-Verlag London Limited.

Kumar P.R.,KS Rangasamy College of Technology | Palani S.,Sudharsan Engineering College
International Conference on Pattern Recognition, Informatics and Medical Engineering, PRIME 2012 | Year: 2012

With growing of applications of the embedded system technology to mobile systems, energy efficiency is becoming an important issue for designing real time embedded systems. One of the possible techniques to reduce the energy consumption is the Dynamic Voltage Scaling (DVS). DVS utilizes the slack time and adjusts the supply voltage so as to reduce the energy expense. However, how to optimally adjust the supply voltage is a NP hard problem. This paper focuses the combinational optimization problem, namely, the problem of minimizing schedule length with energy consumption constraint and the problem of minimizing energy consumption with schedule length constraint. These problems emphasize the tradeoff between power and performance and are defined such that the power-performance product is optimized by fixing one factor and minimizing the other. We propose the analytical result which gives the variation factor of each power supply which depends on the workload and provides the same power supply while meeting the constraints. We address to the use of genetic algorithm to schedule the tasks and then find the optimal power supplies and determine the schedule length on the multiprocessor system. © 2012 IEEE.

Sundareswaran K.,National Institute of Technology Tiruchirappalli | Vignesh kumar V.,National Institute of Technology Tiruchirappalli | Palani S.,Sudharsan Engineering College
Renewable Energy | Year: 2015

This paper explains the development of a new algorithm for maximum power point tracking (MPPT) in large PV systems under partial shading conditions (PSC). The new algorithm combines the use of particle swarm optimization (PSO) for MPPT during the initial stages of tracking and then employs the traditional perturb and observe (PO) method at the final stages. The methodology has been first simulated in two different PV configurations under varying shading patterns and experimentally verified using a microcontroller based experimental system. The integration of swarm intelligence with PO algorithm is shown to yield faster convergence to the global maximum power point (GMPP) than when the two methods are individually used. The oscillations in the output power, voltage and current of the PV system with the proposed method are the least when compared to the ones obtained during PSO based MPPT. © 2014 Elsevier Ltd.

Anandakrishnan V.,National Institute of Technology Tiruchirappalli | Mahamani A.,Sudharsan Engineering College
International Journal of Advanced Manufacturing Technology | Year: 2011

This paper presents the results of an experimental investigation on the machinability of in situ Al-6061-TiB2 metal matrix composite (MMC) prepared by flux-assisted synthesis. These composites were characterized by scanning electron microscopy, X-ray diffraction, and micro-hardness analysis. The influence of reinforcement ratio of 0, 3, 6, and 9 wt.% of TiB2 on machinability was examined. The effect of machinability parameters such as cutting speed, feed rate, and depth of cut on flank wear, cutting force and surface roughness were analyzed during turning operations. From the test results, we observe that higher TiB2 reinforcement ratio produces higher tool wear, surface roughness and minimizes the cutting forces. When machining the in situ MMC with high speed causes rapid tool wear due to generation of high temperature in the machining interface. The rate of flank wear, cutting force, and surface roughness are high when machining with a higher depth of cut. An increase in feed rate increases the flank wear, cutting force and surface roughness. © 2010 Springer-Verlag London Limited.

Sundareswaran K.,National Institute of Technology Tiruchirappalli | Peddapati S.,National Institute of Technology Tiruchirappalli | Palani S.,National Institute of Technology Tiruchirappalli | Palani S.,Sudharsan Engineering College
IEEE Transactions on Energy Conversion | Year: 2014

This paper reports the development of a maximum power-point tracking (MPPT) method for photovoltaic (PV) systems under partially shaded conditions using firefly algorithm. The major advantages of the proposed method are simple computational steps, faster convergence, and its implementation on a low-cost microcontroller. The proposed scheme is studied for two different configurations of PV arrays under partial shaded conditions and its tracking performance is compared with traditional perturb and observe (P&O) method and particle swarm optimization (PSO) method under identical conditions. The improved performance of the algorithm in terms of tracking efficiency and tracking speed is validated through simulation and experimental studies. © 1986-2012 IEEE.

Sundareswaran K.,National Institute of Technology Tiruchirappalli | Peddapati S.,National Institute of Technology Tiruchirappalli | Palani S.,Sudharsan Engineering College
IET Renewable Power Generation | Year: 2014

The power-voltage (P-V) curve of a photovoltaic (PV) power generation system under partially shaded conditions (PSCs) is largely non-linear and multimodal, and hence, global optimisation techniques are required for maximum power point tracking. A traditional optimisation algorithm is proposed here, namely random search method (RSM) for tracking the global maximum power point in a solar power system under PSC. The RSM is based on the use of random numbers in finding the global optima and is a gradient independent method. The major advantage of RSM is its very simple computational steps, which requires very less memory. The performance of RSM in tracking the peak power is studied for a variety of shading patterns and the tracking performance is compared with two-stage perturb and observe (P&O) and population-based particle swarm optimisation (PSO) methods. The simulation results strongly suggest that the RSM is far superior to two-stage P&O method and better than PSO method. Experimental results obtained from a 120-watt prototype PV system validate the effectiveness of the proposed scheme. © The Institution of Engineering and Technology 2014.

Ravi S.,Sudharsan Engineering College | Joseph M.,St. Joseph's College
ACM Transactions on Design Automation of Electronic Systems | Year: 2014

High-level test synthesis is a special class of high-level synthesis having testability as one of the important components. This article presents a detailed survey on recent developments in high-level test synthesis from a synthesis process flow perspective. It also presents a survey on controller synthesis techniques for testability. © 2014 ACM.

Abdul Hameed K.,Anna University | Palani S.,Sudharsan Engineering College
Archives of Electrical Engineering | Year: 2013

In this paper, a novel bacterial foraging algorithm (BFA) based approach for robust and optimal design of PID controller connected to power system stabilizer (PSS) is proposed for damping low frequency power oscillations of a single machine infinite bus bar (SMIB) power system. This paper attempts to optimize three parameters (Kp, Ki, Kd) of PID-PSS based on foraging behaviour of Escherichia coli bacteria in human intestine. The problem of robustly selecting the parameters of the power system stabilizer is converted to an optimization problem which is solved by a bacterial foraging algorithm with a carefully selected objective function. The eigenvalue analysis and the simulation results obtained for internal and external disturbances for a wide range of operating conditions show the effectiveness and robustness of the proposed BFAPSS. Further, the time domain simulation results when compared with those obtained using conventional PSS and Genetic Algorithm (GA) based PSS show the superiority of the proposed design.

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