P A College of Engineering

About: P A College of Engineering is a based out in . It is known for research contribution in the topics: Dihedral angle & Ring (chemistry). The organization has 298 authors who have published 594 publications receiving 4888 citations.

Experimental Investigation of the Friction Stir Weldability of AA8006 with Zirconia Particle Reinforcement and Optimized Process Parameters.

Abstract: A lightweight, highly corrosive resistant, and high-strength wrought alloy in the aluminum family is the Aluminium 8006 alloy. The AA8006 alloy can be formed, welded, and adhesively bonded. However, the recommended welding methods such as laser, TIG (Tungsten Inert Gas welding), and ultrasonic are more costly. This investigation aims to reduce the cost of welding without compromising joint quality by means of friction stir welding. The aluminum alloy-friendly reinforcement agent zirconia is utilized as particles during the weld to improve the performance of the newly identified material AA8006 alloy in friction stir welding (FSW). The objectives of this research are to identify the level of process parameters for the friction stir welding of AA8006 to reduce the variability by the trial-and-error experimental method, thereby reducing the number of samples needing to be characterized to optimize the process parameters. To enhance the quality of the weld, the friction stir processing concept will be adapted with zirconia reinforcement during welding. The friction stir-processed samples were investigated regarding their mechanical properties such as tensile strength and Vickers microhardness. The welded samples were included in the corrosion testing to ensure that no foreign corrosive elements were included during the welding. The quality of the weld was investigated in terms of its surface morphology, including aspects such as the dispersion of reinforced particles on the welded area, the incorporation of foreign elements during the weld, micro defects or damage, and other notable changes through scanning electron microscopy analysis. The process of 3D profilometry was employed to perform optical microscopy investigation on the specimens inspected to ensure their surface quality and finish. Based on the outcomes, the optimal process parameters are suggested. Future directions for further investigation are highlighted.

Multi Ceramic Particles Inclusion in the Aluminium Matrix and Wear Characterization through Experimental and Response Surface-Artificial Neural Networks.

Abstract: Lightweight composite materials have recently been recognized as appropriate materials have been adopted in many industrial applications because of their versatility. The present research recognizes the inclusion of ceramics such as Gr and B4C in manufacturing AMMCs through stir casting. Prepared composites were tested for hardness and wear behaviour. The tests’ findings revealed that the reinforced matrix was harder (60%) than the un-reinforced alloy because of the increased ceramic phase. The rising content of B4C and Gr particles led to continuous improvements in wear resistance. The microstructure and worn surface were observed through SEM (Scanning electron microscope) and revealed the formation of mechanically mixed layers of both B4C and Gr, which served as the effective insulation surface and protected the test sample surface from the steel disc. With the rise in the content of B4C and Gr, the weight loss declined, and significant wear resistance was achieved at 15 wt.% B4C and 10 wt.% Gr. A response surface analysis for the weight loss was carried out to obtain the optimal objective function. Artificial neural network methodology was adopted to identify the significance of the experimental results and the importance of the wear parameters. The error between the experimental and ANN results was found to be within 1%.

Analysis and detection R-peak detection using Modified Pan-Tompkins algorithm

Abstract: Cardiac diseases that gives rise to the death and possibly forms the immedicable danger in order to monitor the heart the proposed algorithm is used. An automatic detection of peaks in Electrocardiogram (ECG) signals is presented. The aim of the design work is to achieve higher performance in terms of reliability and better diagnosis of patients through Peak detection. The new method called Modified Pan-Tompkins algorithm based on the slope and amplitude of ECG signal. The QRS complex detection algorithm uses optimized Bandpass-filtering to reduce false detection. The purpose of prefiltering is to reduce various noise components in order to achieve improved detection reliability. The QRS detection reliability of an algorithm was tested with an noisy stress ECG signal. The usefulness of the proposed method is shown by applying the algorithm to signal from MIT- BIH Arrhythmia database to obtain the number of heart-beats per minute which helps to diagnose the heart disease.