Abstract: Fault diagnosis in bearings has been the subject of intensive research as bearings are critical component in manyrotating machinery applications and an unexpected failure of the bearing may cause substantial economic losses. Vibration analysis has been used as a predictive maintenance procedure and as a support for machinery maintenance decisions. In this study, we used Multiclass Support Vector Machines (MSVM) for classifica-tion task. SVM is a powerful classification tool that is becoming increasingly popular in various machine-learning applications. In data pre-processing step advance signal processing methods such as wavelet transform is used to extract the features which reveals the characteristics of the actual conditions of the bearing. To reduce the dimensionality of the feature SVM–Recursive Feature Elimination (SVM-RFE),Wrapper subset method, ReliefF meth-od and Principle component analysis (PCA). Moreover, investiga-tion is done performance of MSVM with mentioned different feature selection strategies as well as MSVM alone on basis of classification accuracy. To validate the proposed methodology, four kinds of running states are simulated with artificially created faults in bearing that is accommodated in the test rig. By com-paring classification accuracy along with computation timing the best scheme is selected for diagnostic prediction.

Abstract: This paper proposes an interaction with mechatronic system based on voice commands. The goal of this research is to develop a human-machine interface that could be able to control a mechatronic system by using voice commands. With the use of low features extracted from the voice commands, the system will be trained to recognize specific commands. After the training, the commands are recognized and transferred to the controlled system. Intelligent techniques are used with a combination of Hidden Markov Models and Dynamic Time Wrapping for the training and the recognition. The LEGO MINDSTORMS NXT robotics platform controlled by custom software developed under max/msp program is the evaluation tool of the system. The system is tested with different set of commands and the experimental results show that the interaction is efficient with a number of 92% of accuracy on voice commands.

Abstract: Level Control of spherical tank is one of the requirements in industries, where the storage of large volumes of highly pressurized liquids takes place. The level control in spherical tank is cumbersome due to variation of cross sectional area with respect to its height. In the proposed work, PI controller is used to control the level of spherical tank. Initially, the Ziegler Nicholas step response method is used to geta first order plus dead time mathematical model and single set of PI parameter.Multiple models or multiple sets of PI controller parameters are also obtained at different operating points using Z-N and online CGA based tuning methods. By conducting experimental study, the servo and regulatory responses of the spherical tank process are obtained with the controller parameters obtained through various tuning methods.The online CGA based tuning method produce better output response with minimum Integral Square Error (ISE) and Integral Absolute Error (IAE) in real-time, with respect to set point and load changes.

Abstract: A cascade is defined as an infinite row of equidistant similarly aerofoil bodies. The cascade is used to divert a flow stream with a minimal loss. The flow over an axial cascade presents a complicated intra blade fluid dynamic interaction that causes the flow to behave differently than the flow over a single aerofoil blade. A cascade tunnel in which different shapes of cascades could be tested for performance evaluation has been build. An axial flat plate cascade of 70 mm chord, 215 mm span and 0.55 pitch chord ratio has been tested in this tunnel for evaluating its aerodynamic performance. The distortion in the flow ahead of the cascade row was artificially created by using distorters of the outer size same as the cross section of the cascade tunnel and were fixed with the help of air tight flanged connections at a location which was four chords ahead of the cascade. The distorters were made from honey comb sheets and were formed into cutouts of four shapes. The present study aims to investigate the effect of inlet flow distortion on the performance of an axial two dimensional cascade. The results depict that the Reynolds number, incidence and blade angle of the cascade control the aerodynamic performance of the axial cascade. Further the experimental values of lift coefficient are less than that obtained using theory and the drag coefficients are more than the theoretical values. The aerodynamic parameters of the cascade, deflection, deviation, loss coefficients etc, have been found to depend on both the Reynolds number and the type of distortion.

Abstract: This paper aims to study the damping characteristics of Hybrid polymer composite, which can be used in many applications and in engineering structures. The investigation aims to develop glass-epoxy composite with addition of carbon(600mesh) fillers with different weight fractions and to characterize the mechanical and damping properties. The carbon filler are used reinforcement and fabricated using Hand lay-up and vacuum bag molding technique. The damping characteristics were evaluated using free and forced vibration test with different amplitudes. The result indicates that the damping characteristics improved with increase in weight percentage of carbon reinforcement content. Further it was found that glass fiber –epoxy matrix with 5% carbon particles better damping properties which can be used for structural application.

Abstract: Petroleum based fuels worldwide have not only resulted in the rapid depletion of conventional energy sources, but have also caused severe air pollution. The search for an alternate fuel has led to many findings due to which a wide variety of alternative fuels are available at our disposal now. The existing studies have revealed the use of vegetable oils for engines as an alternative for diesel fuel. However, there is a limitation in using straight vegetable oils in diesel engines due to their high viscosity and low volatility. In the present work, neat mango seed oil is converted into their respective methyl ester through transesterification process. Experiments are conducted using various blends of methyl ester of mango seed oil with diesel in a single cylinder, four stroke vertical and air cooled Kirloskar diesel engine. The experimental results of this study showed that the MEMSO biodiesel has similar characteristics to that of diesel. The brake thermal efficiency, unburned hydrocarbon and smoke density are observed to be lower in case of MEMSO biodiesel blends than diesel. The CO emission for B25, B50 and B75 are observed to be lower than diesel at full load, whereas for B100 it is higher at all loads. On the other hand, BSFC and NOx of MEMSO biodiesel blends are found to be higher than diesel. It is found that the combustion characteristics of all blends of methyl ester of mango seed oil showed similar trends with that of the base line diesel. From this study, it is concluded that optimized blend is B25 and could be used as a viable alternative fuel in a single cylinder direct injection diesel engine without any modifications.

Abstract: Flat Plate Solar Water Heaters are widely used all over the world to utilize solar energy available abundantly in nature. To utilize solar energy during off sunshine hours, it becomes necessary to store the solar thermal energy and retain it as long as possible. Depth of water in a solar thermal collector is an important geometric parameter that influences Heat retention. A mathematical modelling of transient heat transfer was done for different water depths and validated with experimental studies to optimize the depth of water from maximum temperature and maximum heat retention view point.

Abstract: This article analyzes and modeling the efficiencies of the energy, the exergy and the power conversion of mono-crystalline photovoltaic module under outdoor weather conditions in Adrar, Algeria (0.18 W, 27.82 N).The experimental data sets are determined for typical clear and cloudy days of March 21 to 23, 2013. The effect of solar radiation, ambient temperature and wind speed on the exergy efficiency is also analyzed. It is observed that the exergy efficiencies vary rapidly throughout the day. However, with an increase of wind speed and ambient temperature there is a decrease in the exergy efficiency. On the other hand, the exergy efficiency increases with an increase in solar radiation.

Abstract: Fault diagnosis in gears has been the subject of intensive research as gears are critical element in a variety of rotating machinery applications and an unexpected failure of the gear may cause substantial economic losses. Vibration analysis has been used as a predictive maintenance procedure and as a support for machinery maintenance decisions .In this present work monitoring of gear health using the vibration signals as well as usage of advance signal processing methods such as wavelet transform is implemented to extract the features which reveals the characteristics of the actual conditions of the gear. By meas-uring and analysing the signals, it is possible to determine both the nature and severity of the defect, and hence predict the ma-chine’s failure. To reduce the dimensionality of the extracted statistical features, roughset integrated principle component analysis (RSPCA) is used after feature extraction process. Back-propagation neural network (BPNN) and probabilistic neural network (PNN) were deployed for diagnostic analysis of the sig-nal. To validate the proposed methodology, four kinds of running states are simulated with artificially created faults in gear that is accommodated in the test rig. By comparing classification accu-racy along with computation timing the best scheme is selected for diagnostic prediction.

Abstract: In tractors, during front end loader, dozer, dry and wet puddling applications there will be higher frequency of operation of clutch because of increased need of quick forward and reverse transmissions. This leads to the slippage of dry clutch because of the usage of coil type clutch where there is reduction in clamp load within minimum hours of time because of inability of the coil springs to withstand high temperature. This would result in excessive scoring marks in pressure plate and flywheel, and glazing of friction material, effecting in slip of the clutch leading to replacement of dry clutch assembly as a whole. In this experimental work, it is proposed to modify the design and replace the coil springs used in the dry clutch with belleville spring which has the ability to withstand high temperature leading to enhanced clutch life in high torque applications of the tractor. This project comprises of calculations and analysis made in support to the usage of belleville spring in dry clutch for front end loader and other high torque applications. The result is a theoretical comparison of existing coil springs with the belleville spring in the clutch to prove the enhanced heat carrying capacity of the belleville spring and thus resulting in improved reliability of dry clutch in tractors.

Abstract: Gears are a vital element considering its applications in a variety of machine tool applications. An unpredicted failure of the gear may cause substantial economic losses. For this very reason, fault diagnosis in gears has been the subject of intensive research. An intelligent method to diagnose and predict the gear fault using vibration signal is proposed in this research work. A signal which contains useful information from various conditions of gear is extracted from an experimental rig. From the original acceleration vibration signals, statistical features are extracted after using the EMD (Empirical mode decomposition) which decomposes the signal into a finite number of stationary intrinsic mode functions (IMFs). Extracted features are recognized and classified by a novel heuristic classifier artificial bee colony (ABC) algorithm. In order to select the predominant features, traditional Genetic algorithm (GA) as well as ReliefF Genetic Algorithm (RFGA) is utilized. The fault diagnosis results are compared with support vector machine (SVM) classifier and their relative efficiency were compared based on the classification accuracy.

Abstract: Scaling down of technology and shrinking down of devices leads to the leakage , tunnelling and short channel effect. The importance of Scaling down of devices with the removal of disadvantage leads to the CNTFET(Carbon Nano Tube Field Effect Transistor). This paper provides the design of fault tolerant reversible D-flipflop, shift register in CNTFET and MOSFET.The comparison of the power, delay, power delay product is done.CNTFET shows low power, less delay and lesser power delay product than the MOSFET.

Abstract: Series of attempt have been made to achieve the most influencing surface roughness (Ra) process parameters of four stroke motor bike cylinder liner in honing operation. It is also evident that many of the modeling techniques have been used by different research, but Response Surface Methodology (RSM) has been worked out to give very robust model in honing process of the present investigation. RSM based artificial surface texture of bike cylinder liner was generated on a real surface measured with white light interferometer (WLI). It is the best surface measuring techniques used for the honed surface of steel liner. Honing angles between 25-75 degrees were investigated as an optimum condition to give the honed surface very smooth. Fractional factorial Design of Experiment has been used to get different set of experiment. Present studies aimed to find the most effective surface roughness process parameters as honing time, pressure, grit size of abrasive, honed fluids and quality of hone work pieces such as aluminum oxide, silicon carbide, ceramics and cubic boron nitride. The minimum surface roughness can be found by optimal parametric combinations.