Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Cluster analysis. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.

Design of Fractional Order PI controller for liquid level control of spherical tank modeled as Fractional Order System

Abstract: In this paper, Fractional Order Proportional Integral (FOPI) controller is designed for a liquid level control in a spherical tank which is modeled as a Fractional Order System (FOS). The performance of FOPI controller is compared with the traditional Integer Order PID (IOPID) controller designed for the same spherical tank which is modeled as a First Order Plus Dead Time (FOPDT) system in simulation and with the Integer Order PI (IOPI) controller in experimental setup. The FOPI controller is designed following a set of imposed tuning constraints, which can guarantee the desired control performance and the robustness to the loop gain variations. This design scheme offers a practical and systematic way of the controllers design for the considered class of fractional order plant. The integer order controller is tuned based on Ziegler-Nichols (ZN) tuning method. From the simulation and experimental results presented, it is observed that the designed fractional order controller works efficiently, with improved performance comparing with the integer order controller.

Disease Detection in Fruits using Image Processing

Abstract: In this project, this approach will be detecting the diseases which affect the fruits and can even identify some types of diseases which attacks fruits based on some comparisons. On account of that, the approach is using CNN(Convolutional Neural Networks), which is a deep learning algorithm that is where input is taken as images, and those images were differentiated based on various aspects and parameters taken from it and is most commonly applied to analyzing visual imagery. This will be definitely helpful for the farmers to enhance the growth of the crops in the mere future. For this approach, python language has been chosen for further analysis. By applying this proposed system, the accuracy level reached is 97%.

Prediction of cutting force in turning process: An experimental and fuzzy approach

Abstract: This paper presents a comparison of experimental results and a fuzzy rule based system model for calculating the cutting force in the turning operation A full bridge dynamometer was used to measure the cutting forces over the mild steel work piece and Cemented Carbide Insert tool for different combinations of cutting velocity, feed rate and depth of cut The rake angle, approach angle and nose radius of the cutting tool insert is kept constant throughout the experiment This fuzzy model consists of 27 rules and Mamdani Max-min inference mechanism was used The Taguchi designs of experiments were used to determine the number of experiments Also, an attempt had been made to analyze the influence of the parameters using the regression analysis which yields a maximum error of 3214% at the time of prediction which was smaller The experiments are planned based on Taguchi's design and the measured cutting forces were compared with the predicted forces in order to validate the feasibility of the proposed design The percentage contribution of each process parameter had been analyzed using Analysis of Variance ANOVA Experimental results were compared with the regression analysis and predicted fuzzy model The difference between experimental and predicted results was obtained as around 9884%

Sensor-Based Turmeric Finger Growth Characteristics Monitoring Using Embedded System under Soil

Abstract: Modern agribusiness is becoming increasingly reliant on computer-based systems which was formerly performed by humans. One such technological innovation is the embedded system-based sensor array module such as flex sensor, temperature sensor, and pH sensor that have been used to monitor the turmeric finger growth characteristics. The experimental work has been tested with five different nodes and the average flex sensor resistance changes in five nodes are calculated. Among the five nodes, nodes II and V were diseased. Purposely node II was left as such and node V was treated with Pseudomonas and viride to restrict the Rhizome rot disease attack. As a result, after cultivation, it was found that the Rhizome rot disease attack on node V is comparatively lesser than node II. The greatest advantage of this method is that it helps the farmers to detect the Rhizome rot disease and also prevent it an early stage by monitoring the growth of the turmeric fingers when it is under the soil.

Combined MHD convection and thermal radiation of nanofluid in a lid-driven porous enclosure with irregular thermal source on vertical sidewalls

Abstract: Mixed convective heat transfer of Cu–water nanofluid in a porous cavity with non-uniform temperature profiles on vertical sidewalls in the presence of thermal radiation and magnetic field is examined numerically. The vertical sidewalls are heated sinusoidally. Thermally insulated walls are considered at the remaining sides of the cavity. The magnetic field is applied parallel to the horizontal walls uniformly. The SIMPLE algorithm based on finite volume approach is applied to solve the governing equations. The numerical outcomes are discussed in the wide range of the parameters, Richardson number, phase deviation, amplitude ratio, Darcy number, Hartmann number, the thermal radiation, and the solid volume fraction. It is found that the average Nusselt number is decreased in value with the raise in the either Hartmann number or Richardson number in the presence of thermal radiation. The average heat transfer rate is enhanced with an augment in the solid volume fraction, and this enhancement is more effective in the presence of thermal radiation than that of in the absence of thermal radiation. The highest heat transfer rate is obtained for $$\varphi =0$$ in the forced convection regime, whereas it is maximum at $$\varphi =3\pi /4$$ in the mixed and free convection regimes.