Browsing by Author "Sudhakar, S."

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Performance enhancement of FSO communication system using machine learning for 5G/6G and IoT applications
(Elsevier GmbH, 2022) Kumar, L.J.S.; Krishnan, P.; Shreya, B.; Sudhakar, S.
6G networks will provide extremely high capacity and will support a wide range of new applications in the future, but the existing frequency bands may not be sufficient. Furthermore, because traditional wireless communications are incapable of providing high-speed data rates, 6G enables superior coverage by integrating space/air/underwater networks with terrestrial networks. 5G-and-beyond (5 GB) and 6G networks have been mandated as a paradigm shift to take the enhanced broadband, massive access, and ultra-reliable and low latency services of 5G wireless networks to an even more advanced and intelligent level, to meet the ever-growing quantities of demanding services. In 5G and 6G wireless communication systems, artificial intelligence (AI), particularly machine learning (ML), has emerged as an essential component of fully intelligent network orchestration and management. 5 GB and 6G communication systems will also rely heavily on a tactile Internet of Things (IoT). The diverse nature of heterogeneous traffic and the established service quality parameters in 5 GB networks will present numerous challenges. Many other wireless technologies, including free space optics (FSO), look promising for meeting the demands of 5 GB systems. FSO has been identified as a promising technology for achieving higher data rates while consuming less power. However, attenuation due to weather, pointing errors, and turbulences limits its performance. Traditional Maximum likelihood decoding techniques require prior channel information to decode the signals. in this paper, first time we proposed a novel decoding technique for decoding on–off keying (OOK) modulated FSO signals using support vector machines (SVM). The model is tested under various atmospheric weather conditions such as fog, rain, and snow, as well as turbulence and pointing errors. Simulated numerical results demonstrate that the proposed SVM-based decoding schemes are capable of mitigating attenuation, pointing error, and turbulent channel impairments. © 2021 Elsevier GmbH
Performance evaluation of mechanical micro-drilling, electrical discharge machining and laser beam machining on nimonic 80A alloy
(2018) Sudhakar, S.; Kumar, P.; Srinivas, G.; Ravishankar, S.; Chakradhar, D.; Barshilia, H.C.
Micromachining techniques such as mechanical micro-drilling, electrical discharge machining (EDM) and laser beam machining (LBM) play an important role in the manufacturing of micro-devices used in mechanical, electronics, aerospace and medical applications. In this paper, an effort has been made to compare the performance of these micromachining techniques with regard to tool wear, burr formation and surface integrity. This is done by producing 20 micro-holes of approximately 800 ?m diameter on a rectangular block (90 30 3 mm3) of Nimonic 80A superalloy. TiAlN coated WC micro-drills, Cu electrodes and CO2 laser beam are used to produce these holes in conventional micro-drilling, EDM and LBM, respectively. The quality of the drilled hole (diameter, surface roughness and micro-burr formation), tool diameter analysis, taper angle and material removal rate (MRR) are compared and reported. A comprehensive analysis is also carried out on overcut, which leads to hole inaccuracy. Results show that mechanical micro-drilling produces better results in the above mentioned characteristics in comparison to LBM and EDM techniques. The relatively better performance of mechanical micro-drilling is attributed to the usage of TiAlN coating on WC tool. 2018, National Institute of Science Communication and Information Resources (NISCAIR). All rights reserved.
Performance evaluation of mechanical micro-drilling, electrical discharge machining and laser beam machining on nimonic 80A alloy
(National Institute of Science Communication and Information Resources (NISCAIR) ijact.editor@gmail.com Dr. K. S. Krishnan Marg (Near Pusa Gate) New Delhi 110-012, 2018) Sudhakar, S.; Kumar, P.; Srinivas, G.; Ravishankar, S.; Dupadu, D.; Barshilia, H.C.
Micromachining techniques such as mechanical micro-drilling, electrical discharge machining (EDM) and laser beam machining (LBM) play an important role in the manufacturing of micro-devices used in mechanical, electronics, aerospace and medical applications. In this paper, an effort has been made to compare the performance of these micromachining techniques with regard to tool wear, burr formation and surface integrity. This is done by producing 20 micro-holes of approximately 800 ?m diameter on a rectangular block (90×30×3 mm3) of Nimonic 80A superalloy. TiAlN coated WC micro-drills, Cu electrodes and CO2 laser beam are used to produce these holes in conventional micro-drilling, EDM and LBM, respectively. The quality of the drilled hole (diameter, surface roughness and micro-burr formation), tool diameter analysis, taper angle and material removal rate (MRR) are compared and reported. A comprehensive analysis is also carried out on overcut, which leads to hole inaccuracy. Results show that mechanical micro-drilling produces better results in the above mentioned characteristics in comparison to LBM and EDM techniques. The relatively better performance of mechanical micro-drilling is attributed to the usage of TiAlN coating on WC tool. © 2018, National Institute of Science Communication and Information Resources (NISCAIR). All rights reserved.