National Institute of Technology, Silchar

About: National Institute of Technology, Silchar is a education organization based out in Silchar, Assam, India. It is known for research contribution in the topics: Control theory & Electric power system. The organization has 1934 authors who have published 4219 publications receiving 41149 citations. The organization is also known as: NIT Silchar.

Green synthesis of SnO2 quantum dots using Parkia speciosa Hassk pods extract for the evaluation of anti-oxidant and photocatalytic properties.

Abstract: In the present study, microwave heating method was established for the biosynthesis of SnO2 Quantum dots (QDs) using Parkia speciosa Hassk pods extract. The as-synthesized quantum dots have been characterized by various techniques such as UV, XRD, EDX, TEM, HRTEM, SAED and FTIR spectroscopy. The biosynthesized SnO2 QDs was employed for the first time as an efficient photocatalyst for the degradation of a food dye, acid yellow 23 dye from aqueous phase under the UV254 light. Various parameters, such as the effect of catalyst dose, the initial concentration of acid yellow 23 dye (AY23), pH of the solution and irradiation time on the photodegradation process are also studied for efficient and better use of the synthesized SnO2 QDs as a catalyst. The biosynthesized SnO2 QDs exhibited excellent photocatalytic performances with degradation efficiency 98% on the degradation of an aqueous solution of AY23 of concentration 5 mg/L with a catalyst dose of 20 mg under UV254 light within 24 min. The synthesized SnO2 QDs can be reused up to 5 cycles of photodegradation experiment without losing its stability and efficiency. The biosynthesized SnO2 QDs also shows a fair activity in the scavenging of 2,2-diphenyl-1-picrylhydrazyl free radical with the IC50 value of 312.6 ± 0.025 μg/mL.

A Comprehensive Review of Condition Based Prognostic Maintenance (CBPM) for Induction Motor

Abstract: This paper presents condition monitoring aspects of induction motor, its present status with possible mitigation schemes and future maintenance challenges. The induction motors constitute the major portion of motors in domestic and industrial applications. These motors experience different types of failures and faults associated with insulation, bearing, stator, rotor, and eccentricity. As a matter of fact, these faults may subsequently enhance the probability of failures unless proper introspection is not accomplished. In order to reduce the failure time and operating cost, early detection is indispensable which necessitates condition-based approach on contrary to scheduled maintenance. The condition monitoring is a strong candidate to address the diagnosis of machinery failure problems and unreliability. In this context, a comprehensive analysis is reported in the literature with a focus on different methodologies being addressed for such objective. Utmost efforts are made to comprehensively analyze in the reported literature in a sequential manner citing the advantage and limitations in this paper. The authors hopefully described and illustrated the associated problems with possible mitigation in the context of condition monitoring which would be immensely helpful for future researchers working in these aspects and the future roadmap would be clearly reflected.

Exchange market algorithm based optimum reactive power dispatch

Abstract: Graphical abstractDisplay Omitted This paper presents a maiden application of EMA to solve power system ORPD problems.Steps of implementation of EMA to solve ORPD are elaborately discussed.The performance of EMA is tested on standard IEEE test systems.The selection of control parameters of EMA is done through exhaustive parametric study. In this paper, an exchange market algorithm (EMA) approach is applied to solve highly non-linear power system optimal reactive power dispatch (ORPD) problems. ORPD is most vital optimization problems in power system study and are usually devised as optimal power flow (OPF) problem. The problem is formulated as nonlinear, non-convex constrained optimization problem with the presence of both continuous and discrete control variables. The EMA searches for optimal solution via two main phases; namely, balanced market and oscillation market. Each of the phases comprises of both exploration and exploitation, which makes the algorithm unique. This uniqueness of EMA is exploited in this paper to solve various vital objectives associated with ORPD problems. Programs are developed in MATLAB and tested on standard IEEE 30 and IEEE 118 bus systems. The results obtained using EMA are compared with other contemporary methods in the literature. Simulation results demonstrate the superiority of EMA in terms of its computational efficiency and robustness. Consumed function evaluation for each case study is mentioned in the convergence plot itself for better clarity. Parametric study is also performed on different case studies to obtain the suitable values of tuneable parameters.

HWPSO: A new hybrid whale-particle swarm optimization algorithm and its application in electronic design optimization problems

Abstract: In this paper, a new population based hybrid meta-heuristic algorithm called the Hybrid Whale-Particle Swarm Optimization Algorithm (HWPSO) for solving complex optimization problems has been proposed. The proposed algorithm tries to overcome the limitations associated in a Particle Swarm Optimization (PSO) exploration phase i.e. Stagnation Effect, by hybridizing with a whale optimization algorithm (WOA) in a novel way as WOA has been reported to have very good exploration capability. During hybridization, two novel techniques have been employed, namely ‘Forced’ Whale and ‘Capping’ Phenomenon. The ‘Forced’ WOA is introduced in exploration phase and it enables the WOA to guide PSO for better local optima avoidance and concurrently a new ‘Capping’ phenomenon is employed which restricts the WOA search mechanism during exploitation phase, thereby converging the solution faster to a global optimum value. The performance of the proposed HWPSO has tested on 18 benchmark mathematical functions and 3 Electronics Design Optimization problems. The simulation results indicate that the proposed algorithm outperforms many state of the art algorithms by achieving a better optima with a very low standard deviation for most of the benchmark functions used. The effectiveness of the proposed HWPSO has been also validated by statistical as well as complexity analysis. The performance of HWPSO algorithm is also found to be satisfactory in all three cases of electronics design optimization problems, which have been further validated with standard design tools and found to be in close agreement with each other.