Kongu Engineering College

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

Wear prediction on silicon nitride bearing couple in human hip prosthesis using finite element concepts

Abstract: Wear is one of the important tribological parameter that increases the revision rate of artificial hip implantation. Silicon nitride (Si3N4) is one of the promising ceramic materials with low wear ...

Study of pH System in Common Effluent Treatment Plant

Abstract: This investigation considers the study of pH system in Common effluent treatment plant (CETP). For this purpose, Perundurai Common Effluent Treatment (PCETP) is taken for study. Waste from textile industries is rarely neutral. Certain processes such as reactive dyeing require large quantities of alkali but pre-treatments and some washes can be acidic. It is therefore necessary to adjust the pH in the treatment process to make the wastewater neutral. This is particularly important if biological treatment is being used, as the microbes used in biological treatment require a pH in the range of 6-8 and will be killed by highly acidic or alkali wastewater. In PCETP, the wastewater is mostly alkali wastes (high pH). For this purpose, hydrochloric acid (HCl) is added to maintain the pH value from 7.5 to 7.8 to save the microbes used in biological treatment as well as to reduce the wastage of chemicals.

Investigation of blend biopolymer electrolytes based on Dextran-PVA with ammonium thiocyanate

Abstract: A new polymer electrolytes based on Dextran, poly vinyl alcohol (PVA) with different concentrations of ammonium thiocyanate (NH4SCN) have been prepared by solution casting technique using distilled water as a solvent. The synthesized biopolymer membranes have been characterized by various techniques such as X-ray diffraction (XRD), Fourier transform–infrared spectroscopy (FTIR), differential scanning calorimetric (DSC), AC impedance, linear sweep voltammetry (LSV), and transference number measurement. The increase in amorphous nature of the blend polymer (700 mgDextran:300 mgPVA) with increase in salt concentration is observed in XRD pattern. The complex formation between the blend polymer and salt has been confirmed by FTIR. The glass transition temperature (Tg) of the prepared polymer membranes have been analyzed by DSC. From AC impedance analysis, a maximum ionic conductivity of 8.03 × 10−3 S/cm has been achieved by incorporation of 0.6 M.wt% NH4SCN with blend polymer (700 mgDextran:300 mgPVA). The electrochemical stability of the highest conducting polymer electrolyte 700 mgDextran:300 mgPVA:0.6 M.wt%NH4SCN has been observed as 3.01 V by LSV. From Wagner’s polarization method, transference number has been calculated. The proton battery has been constructed with the highest conducting polymer electrolyte 700 mgDextran:300 mgPVA:0.6 M.wt%NH4SCN. The open-circuit voltage (OCV) has been observed as 1.75 V and the battery performance is studied.

Treatment of tannery effluent using sono catalytic reactor

Abstract: The effluent released from the leather process industries contain high amount of chemical oxygen demand (COD), biologicaloxygen demand (BOD), suspended solid (SS), ammonia nitrogen, Total Kejeldahl Nitrogen, nitrate, nitrogen, hexavalent and trivalent chromium, chloride, sulphates, etc. In the present study the lime pre-treated effluent is exposed to a sonocatalytic reactor, in which the TiO 2 catalyst was used. The parameters such as BOD, COD and total dissolved solids (TDS) were studied by varying the concentration of effluent, time and catalyst load. The results reveal that the efficiency of sono catalytic reactor on percentage removal of COD, BOD and TDS were 89.53, 87.35 and 92.63 respectively. The response surface methodology (RSM) was used to optimize the variables such as catalyst loading and time. Statistical results were assessed with various descriptive such as p value, lack of fit (F-test), coefficient of R 2 determination. The predicted and adjusted R 2 values were found to be 0.9956, 0.9673 for% COD removal, 0.9484, 0.9926 for% BOD removal and 0.9980, 0.9954 for% TDS removal respectively.

Harmonic minimization of a solar fed cascaded H Bridge inverter using Artificial Neural Network

Abstract: The major concern in the design of inverters is dealing with harmonics. Harmonics in inverter are generated due to improper selection of switching angles to the gates of the inverter switches. The presence of harmonics in inverter output will affect the loads connected to it. This paper deals with the selective harmonic elimination problem in multilevel inverter using Artificial Neural Networks (ANN) to generate the switching angles for an eleven-level full-bridge cascaded H bridge multilevel inverter powered by five varying DC input sources (solar panels). The Harmonic equations are solved and angles are obtained such that the fundamental was kept constant and the low-order harmonics were minimized or eliminated. The different data sets of angle values for various input DC voltage conditions are obtained. The data sets thus collected are used to train the multi-layered feed forward neural network. The trained network is then tested for its performance. The network model is integrated with cascaded H bridge multilevel inverter to generate the switching angles in real-time.