Velagapudi Ramakrishna Siddhartha Engineering College

About: Velagapudi Ramakrishna Siddhartha Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Antenna (radio). The organization has 1307 authors who have published 1155 publications receiving 6163 citations.

Spectroscopic studies of chromium doped alkali earth lead zinc phosphate glasses

Abstract: X-Ray diffraction, energy dispersive X-ray, Fourier transform infrared, Raman spectroscopy, differential scanning calorimetry, UV–Visible spectroscopy and electron paramagnetic resonance spectroscopic studies have been carried out on alkali earth lead zinc phosphate glasses doped with 0.1 % chromium ions. The energy dispersive X-ray spectra reveal fundamental compositional information of the glasses. Infrared spectra indicate that phosphate network is depolymerized with progressive substitution of alkali earth content and inform the characteristic vibrations of PO4 3− units. Raman spectra suggest that these glasses are consisting of metaphosphate [Q2] units along with some bands related to pyrophosphate [Q1] and orthophosphate [Q0] units. The crystal-field parameter and inter-electronic repulsion parameters have been evaluated from optical absorption spectral data. Electron spin resonance spectra of Cr3+ systems indicate that g ∥ > g ⊥ and Cr3+ ions are located at sites with lower symmetry. It is obtained that the glass transition temperatures fall in region of 377–360 °C. Increase in density of the glass system brings changes in structure of the glasses on replacement of alkali earth content.

Application of 3D wavelet transforms for crack detection in rotor systems

Abstract: The dynamics and diagnostics of a cracked rotor have been gaining importance in recent years. The early detection of faults like fatigue cracks in rotor shafts are very important to prevent catastrophic failure of the rotor system. Vibration monitoring during start up or shut-down is as important as during steady state operation to detect cracks especially for machines such as aircraft engines which start and stop quite frequently and run at high speeds. So, the transient data of the cracked rotor has been transformed using the wavelet transforms for crack detection. Most of the works quoted in the literature used 1D wavelets or 2D wavelets (Continuous Wavelet Transform-CWT) for crack detection. The crack detectors in the signals are both time as well as frequency dependent. So, the use of 2D wavelets is also not enough to detect the crack. In the present work a 3D wavelet (CWT) has been utilized which clearly indicates both the time and frequency features of the crack. The presence of sub-criticals in the CWT may be a best crack indicator but it is not always reliable. The addition of noise to the signal may sometimes lead to inaccurate results. So, there is a need to identify a parameter in addition to the sub-criticals. The phase angle between the two signals (cracked and un-cracked) or two transverse vibrations can be a better crack indicator because it is very less sensitive to noise disturbance. So, to extract the above phase angle a new transform has been applied called Cross Wavelet Transform (XWT). The XWT is exploited for the first time to a rotor fault detection system in the present work. Some interesting results have been obtained using the same. The advantage of the XWT is that both, the phase angles between the transverse signals and also the amplitudes of sub-criticals are viewed in a single plot. Parametric analysis is also carried out by varying crack depth and crack position for diagnostic purposes. The inverse problem of crack identification (i.e. determining the crack parameters through known vibration data) has also been carried out using Artificial Neural Network (ANN).

Effective Comparison of LDA with LSA for Topic Modelling

Abstract: The process of converting unstructured data into a structured readable format is becoming hard day by day Till day every organization consists of more than 80% of its operational data in an unreadable format The proposed method helps in converting unreadable data to a readable structured format with the help of Machine learning were classification, and clustering plays a crucial role in converting the operational data into data models and visualize the processed information to the end-user As organizations have specific requirements, considering them, we are going to implement latent dirichlet allocation (LDA) and latent semantic analysis (LSA), which were able to handle discrete data Also, a comparison is made to test divergence, throughput, quality, and response time, as both of them can classify the data based on the content and by giving labels to each category The algorithm with better divergence is implemented that can handle the organizational requirements by presenting the top areas that need to improve/concentrate depending on the analytics made by the algorithm on the available discrete data, and by implementing visualization techniques, the results will be even displayed in graphical format

Experimental investigation of the influence of burnishing tool passes on surface roughness and hardness of brass specimens

Abstract: The process of burnishing is performed by applying a highly polished and hardened ball or roller with external force onto the surface of a cylindrical work piece. The burnishing process increases the surface hardness of the work piece, which in turn improves wear resistance, increases corrosion resistance, improves tensile strength, maintains dimensional stability and improves the fatigue strength by inducing residual compressive stresses in the surface of the work piece. In the present experimental work, both ball and roller burnishing tools are used. Experiments are conducted to study the performance of the ball and roller burnishing tools on lathe, along with the influence of number of burnishing tool passes on the surface roughness and surface hardness of brass specimens. The results revealed that improvements in the surface finish and increase in the surface hardness are obtained by the increase of the number of burnishing tool passes in both ball burnishing and roller burnishing on the brass specimens.

Preparation and Properties of Sintered Copper–Tin Composites Containing Copper Coated or Uncoated Fly Ash

Abstract: Copper–5%tin–fly ash mixtures containing 0–16 wt% fly ash with or without copper coating were prepared. Small cylindrical specimens of 9 mm diameter and 10.5 mm length were fabricated at 300 MPa using single action die compaction at ambient temperature. These compacts were sintered in argon atmosphere for a period of 45 min at 700°, 740°, and 780°C, respectively. The green and sintered properties of the compacts were determined as a function of fly ash weight percent. The results indicated that density, hardness, and compression strength of the green compacts were improved by the electroless copper coating on fly ash reinforcement. It was also observed that coated green compacts exhibited lower spring back and higher ejection pressures compared to uncoated compacts. Sintering resulted in increase in density and decrease in volume of green compacts. Sintered density of the composites was found to decrease with increasing weight percent of fly ash. It was further observed that sintering of coated composites...