Dr.S.Murugan

@tec-edu.in

Professor/Department of ECE
Thamirabharani Engineering College

https://researchid.co/srivimurugan

EDUCATION

Ph.D Electrical Engineering

RESEARCH INTERESTS

Sensor modelling, optimization and control engineering

Scopus Publications

Scholar Citations

Scholar h-index

Scholar i10-index

Scopus Publications

Optimized Convolutional Neural Network-Based Adaptive Controller for 6-Phase DFIG-Based Wind Energy Systems
Arunkumar Azhakappan, Agees Kumar Chellappan, and Murugan Sethuramalingam
Informa UK Limited

Automatic Skin Tumour Segmentation Using Prioritized Patch Based Region–A Novel Comparative Technique
A. Ashwini and S. Murugan
Informa UK Limited
Skin tumour detection plays a key factor in medical research. Nowadays, tumour detection process is of crucial importance as the number of persons affected is increasing substantially. The aim of this research work is to develop a new approach for efficient image enhancement and tumour detection from other unaffected regions on computed tomographic skin images. This work is mainly related to medical application methods on computed tomography (CT) skin tumour images that have been designed and implemented efficiently. The initial method, which was based on the quality of image, enhanced the medical image performance. Normally, these images are very noise sensitive and create difficulty in handling procedures. Proper care has to be taken which involves the introduction of pre-processing algorithms like enhancement techniques and filters. According to this, Anisotropic Diffusion Filtering (ADF) followed by Recursive Mean Separate Histogram Equalization (RMSHE) algorithm was introduced to improve the contrast of tumour images. In the second method, Public Contour Metric Based Segmentation (PCMBS) Mapping and Prioritized Patch Based Region Segmentation (PPBRS) Algorithm is proposed for skin tumour segmentation. These techniques are performed in CT skin tumour image which are benign or malignant. Overall accuracy of 98.5% and 95.4% is obtained for various benign and malignant tumours, respectively, in MATLAB 2018a software.

Brain tumor findings in patient with a novel cascaded function
R. Remya, S. Murugan, and K. Parimala Geetha
Springer Science and Business Media LLC

A series of exponential function, as a novel methodology in detecting brain tumor
R. Remya, K. Parimala Geetha, and S. Murugan
Elsevier BV

Enhancing the linearity characteristics of photoelectric displacement sensor based on extreme learning machine method
Murugan Sethuramalingam and Umayal Subbiah
Springer Science and Business Media LLC

An evolutionary optimized algorithm approach to compensate the non-linearity in linear variable displacement transducer characteristics
S. Murugan and S.P. Umayal
The Korean Institute of Electrical Engineers
Linearization of transducer characteristic plays a vital role in electronic instrumentation because all transducers have outputs nonlinearly related to the physical variables they sense. If the transducer output is nonlinear, it will produce a whole assortment of problems. Transducers rarely possess a perfectly linear transfer characteristic, but always have some degree of non-linearity over their range of operation. Attempts have been made by many researchers to increase the range of linearity of transducers. This paper presents a method to compensate nonlinearity of Linear Variable Displacement Transducer (LVDT) based on Extreme Learning Machine (ELM) method, Differential Evolution (DE) algorithm and Artificial Neural Network (ANN) trained by Genetic Algorithm (GA). Because of the mechanism structure, LVDT often exhibit inherent nonlinear input-output characteristics. The best approximation capability of optimized ANN technique is beneficial to this. The use of this proposed method is demonstrated through computer simulation with the experimental data of two different LVDTs. The results reveal that the proposed method compensated the presence of nonlinearity in the displacement transducer with very low training time, lowest Mean Square Error (MSE) value and better linearity. This research work involves less computational complexity and it behaves a good performance for nonlinearity compensation for LVDT and has good application prospect.

A Novel Nonlinearity Compensation Method to Improve the Linearity Characteristics of Constant Temperature Anemometer Using Optimized Evolutionary Algorithms

RECENT SCHOLAR PUBLICATIONS

Optimized Convolutional Neural Network-Based Adaptive Controller for 6-Phase DFIG-Based Wind Energy Systems
A Azhakappan, AK Chellappan, M Sethuramalingam
Electric Power Components and Systems 51 (19), 2262-2283 2023

Automatic skin tumour segmentation using prioritized patch based region–a novel comparative technique
A Ashwini, S Murugan
IETE Journal of Research 69 (1), 137-148 2023

Brain tumor findings in patient with a novel cascaded function
R Remya, S Murugan, KP Geetha
Signal, Image and Video Processing 16 (6), 1533-1540 2022

GNVDF: A GPU-accelerated Novel Algorithm for Finding Frequent Patterns Using Vertical Data Format Approach and Jagged Array
P Sumathi, S Murugan
International Journal of Modern Education and Computer Science (IJMECS) 13 2021

A series of exponential function, as a novel methodology in detecting brain tumor
R Remya, KP Geetha, S Murugan
Biomedical Signal Processing and Control 62, 102158 2020

A METHOD AND DEVICE: REAL TIME MONITORING OF PATIENTS
DSM Dr. G. Rajakumar, Dr. N. Muthukumaran, Dr. T. Samraj Lawrence, Dr.S ...
IN Patent 201,941,044,451 2019

Generation of Electric Power using Wind Energy through Moving Vehicles
TVJYM S.Murugan, M.Marimuthu, N.R.Shakthy
International Journal of Advanced Research in Electrical, Electronics and 2019

A fuzzy logic controlled solar power generation with integrated maximum power point tracking using multi-level inverter
A Ravi, S Murugan, SJ Daniel, R Aandal
International Journal of Applied Engineering Research. 10, 2315-2326 2019

WDO Based Security Constrained Unit Commitment with Flexible Set for Variable Wind Power
M Sumathy, AG Saravanan, S Murugan, AA Manuela
ICON (Integrating Concepts) 3 (1), 7 2018

Configuration and Augmentation of Solar Humidifier System
KSSS S.Murugan, B.Rupanraj
International Journal of Research in Advanced Technology 3 (3), 1-4 2018

Nonlinearity error compensation of Venturi flow meter using evolutionary optimization algorithms
S Murugan, SP Umayal, K Srinivasan, M Aruna
IJIRST 3 (7) 2016

Web Mining
S Murugan
International Journal of Telecommunications & Emerging Technologies 1 (2), 1-10 2015

Enhancing the linearity characteristics of photoelectric displacement sensor based on extreme learning machine method
M Sethuramalingam, U Subbiah
Photonic Sensors 5, 24-31 2015

An Evolutionary Optimized Nonlinearity Compensation Technique to Improve the Linearity Characteristics of Thermocouple Sensor
SM M S Devi
International Journal of Applied Engineering Research 10 (1), 945-951 2015

A NOVEL NONLINEARITY COMPENSATION METHOD TO IMPROVE THE LINEARITY CHARACTERISTICS OF CONSTANT TEMPERATURE ANEMOMETER USING OPTIMIZED EVOLUTIONARY ALGORITHMS
S MURUGAN, SP UMAYAL
INTERNATIONAL JOURNAL OF APPLIED ENGINEERING RESEARCH 9 (23), 21639-21656 2014

An evolutionary optimized algorithm approach to compensate the non-linearity in linear variable displacement transducer characteristics
S Murugan, SP Umayal
Journal of Electrical Engineering and Technology 9 (6), 2142-2153 2014

A Review on Enhancing the Linearity Characteristic of different types of Transducers- A Comparative Study’
SPU S. Murugan
International Conference on Instrumentation, Communication, Control and 2013

A Case Study on Enhancing the Performance of Linear Variable Differential Transformer by using ANN Based Temperature Compensation Circuits
SPU S. Murugan
European Journal of Scientific Research 96 (1), 7-16 2013

A review on enhancing the linearity characteristic of different types of transducers-a comparative study
S Murugan, SP Umayal
Int. J. Mod. Eng. Res 3, 1186-1191 2013

Sensor Fusion in Time Triggered Network
SG S. Murugan
Recent Advances in Industrial Automation and Networking- RAIN 2005 2005

MOST CITED SCHOLAR PUBLICATIONS

Automatic skin tumour segmentation using prioritized patch based region–a novel comparative technique
A Ashwini, S Murugan
IETE Journal of Research 69 (1), 137-148 2023
Citations: 24

A series of exponential function, as a novel methodology in detecting brain tumor
R Remya, KP Geetha, S Murugan
Biomedical Signal Processing and Control 62, 102158 2020
Citations: 7

Brain tumor findings in patient with a novel cascaded function
R Remya, S Murugan, KP Geetha
Signal, Image and Video Processing 16 (6), 1533-1540 2022
Citations: 3

Enhancing the linearity characteristics of photoelectric displacement sensor based on extreme learning machine method
M Sethuramalingam, U Subbiah
Photonic Sensors 5, 24-31 2015
Citations: 3

Web Mining
S Murugan
International Journal of Telecommunications & Emerging Technologies 1 (2), 1-10 2015
Citations: 2

Nonlinearity error compensation of Venturi flow meter using evolutionary optimization algorithms
S Murugan, SP Umayal, K Srinivasan, M Aruna
IJIRST 3 (7) 2016
Citations: 1

A review on enhancing the linearity characteristic of different types of transducers-a comparative study
S Murugan, SP Umayal
Int. J. Mod. Eng. Res 3, 1186-1191 2013
Citations: 1