Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

&nbsp;

&nbsp;

VIT University

Mechanical

Rule learning based approach to fault detection and diagnosis is becoming very popular, mainly due to their high accuracy when compared to older statistical methods. Fault detection and diagnosis of various mechanical components of centrifugal pump is essential to increase the productivity and reduce the breakdowns. This paper presents the use of rough sets to generate the rules from statistical features extracted from vibration signals under good and faulty conditions of a centrifugal pump. A fuzzy inference system (FIS) is built using rough set rules and tested using test data. The effect of different types of membership functions on the FIS performance is also presented. Finally, the performance of this classifier is compared to that of a fuzzy-antminer classifier and to multi-layer perceptron (MLP) based classifiers. © 2011 Elsevier B.V. All rights reserved.

World University root node

School of Mechanical Engineering

Chennai Campus

Applied Soft Computing

Automatic rule learning using roughset for fuzzy classifier in fault categorization of mono-block centrifugal pump

The comparison of limit load based on small displacement limit analysis and collapse load based on large displacement analysis for shape-imperfect pipe bends, under combined in-plane closing bending and an internal pressure, were carried out using finite element method. The limit and collapse moments were obtained from moment-rotation curves drawn for each model. Twice-elastic-slope method was used to obtain collapse load. The effect of thinning on limit and collapse moments are minimal and hence thinning need not be considered for the analysis of pipe bends. The influence of ovality on both limit and collapse loads for most of the cases considered are significant. Comparison of effect of ovality on limit and collapse loads reveals that the determination of collapse load is preferable when ovality is included in the analysis of pipe bend. A closed-form solution is presented to include ovality in the determination of the collapse load of pipe bends. © 2012 Elsevier Ltd.

International Journal of Pressure Vessels and Piping

Comparison of plastic limit and collapse loads in pipe bends with shape imperfections under in-plane bending and an internal pressure

The effect of ovality and variable wall thickness (thickening at intrados and thinning at extrados) on the collapse loads in pipe bends subjected to in-plane bending moment that tend to close the bend was investigated using finite element limit analyses based on elastic-perfectly plastic material with large geometry change option. The collapse moments were obtained from load-deflection curves of the models with circular (uniform wall thickness) and irregular cross sections and compared. The presence of ovality in the pipe bends significantly affects the collapse loads while thinning produce very less effect. Based on finite element collapse load (twice-elastic-slope) results, a mathematical equation is proposed to include the effect of ovality. © 2011 Elsevier Ltd.

Engineering Fracture Mechanics

Effect of ovality and variable wall thickness on collapse loads in pipe bends subjected to in-plane bending closing moment

Diesel combustion appears to be the most prominent way to improve fuel efficiency for global CO2 emissions reduction. To achieve this, the combustion inside the cylinder should be studied and the pollutant emissions, especially NOx and soot, need to be considered simultaneously. Over the past, substantial advances have been made in the modeling of combustion in direct injection diesel Engines and the progress is attributed to the development of a new model, which take into account explicitly all the described phenomena. In the current work, the operating characteristics of direct injection diesel engine is studied using Extended Coherent Flame Model for 3 zones (ECFM-3Z) model in a CFD tool named es-ICE, an expert system for internal combustion engines. The present study is validated with the experimental work performed by Colin et. al. The combustion and emission characteristics are studied by varying the swirl ratio. It is found that in cylinder pressure and temperature increases with swirl ratio. NOx emissions increases and soot levels decreases at higher swirl ratio. © 2013 All rights reserved.

Department of Automotive Engineering

Vellore Campus

CFD Letters

Effect of swirl in a constant speed DI diesel engine using computational fluid dynamics

Three degrees of freedom (DOF) parallel manipulator is used in the applications such as base for various machining operations, drilling inclined holes, airplane and automobile simulators, walking machines, pointing devices, contour milling and machining etc. The 3 DOF parallel manipulator consists of a fixed platform and a movable platform, which are connected by means of three identical links. Pin joints are used to connect the one end of the link and the lead screw pair. This 3 DOF 1R2T parallel manipulator is having one orientation freedom and two translational freedom, which is actuated by means of screw pair, which in turn operated by a stepper motor. The inverse kinematics and velocity equations of this mechanism have been derived mathematically. Based on this inverse kinematics and velocity equations singularity analysis is completed. Two kinds of singularities are compared with ADAMS simulation results and a prototype of the manipulator is developed for further study. © (2012) Trans Tech Publications, Switzerland.

Advanced Materials Research

Kinematic and singularity analysis of 3 prr parallel manipulator

Science and Technology of Welding and Joining

Influence of weld geometry and mismatch on formability of aluminium tailor welded blanks: numerical and experimental analysis

This paper investigates the effect of an external magnetic field in the electroplating of Ni, one of the four ferromagnetic materials at the room temperature. Nickel plating is done using Watts bath with a composition of 250g/L of Nickel sulphate, 35g/L of Nickel Chloride, 25g/L of Boric acid with pH between 5 and 6 at room temperature under a current density of 0.05-0.1 A/dm2 under the presence of an external magnetic field to obtain a coherent coating. The arrangement of the coated particles is studied by SEM analysis. © 2012 American Institute of Physics.

AIP Conference Proceedings

Effect of magnetic field on the electrodeposition of nickel

Fulltext

Thermal Science

Combustion and emission characteristics of a diesel engine fuelled with jatropha and diesel oil blends

Vibration signals are used in fault diagnosis of rotary machines as a source of information. Lots of work have been reported on identification of faults in roller bearing by using many techniques. Of late, application of machine learning approach in fault diagnosis is gaining momentum. Machine learning approach consists of chain of activities like, data acquisition, feature extraction, feature selection and feature classification. While histogram features are used, there are still a few questions to be answered such as how many histogram bins are to be used to extract features and how many samples to be used to train the classifier. This paper provides a mathematical study to choose the bin size and the minimum sample size to train the classifier using power analysis with statistical stability. A typical bearing fault diagnosis problem is taken as a case for illustration and the results are compared with that of entropy based algorithm (J48) for determining minimum sample size and bin size. Copyright © 2011 Inderscience Enterprises Ltd.

International Journal of Data Analysis Techniques and Strategies

Determination of sample size using power analysis and optimum bin size of histogram features

Visual inspection on the surface of components is a main application of machine vision. Visual inspection finds its application in identifying defects such as scratches, cracks bubbles and measurement of cutting tool wear and welding quality. Machine learning approach to machine vision helps in automating the design process of machine vision systems. This approach involves image acquisition, preprocessing, feature extraction and classification. Study shows a library of features, and classifiers are available to classify the data. However, only the best combination of them can yield the highest classification accuracy. In this study, images with different known conditions were acquired, preprocessed, and histogram features were extracted. The classification accuracies of C4.5 classifier algorithm and Naïve Bayes algorithm were compared, and results are reported. The study shows that C4.5 algorithm performs better. © 2010 Elsevier Ltd. All rights reserved.