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Mumbai, India

Kharb R.K.,Government Polytechnic | Shimi S.L.,Indian National Institute of Engineering | Chatterji S.,Indian National Institute of Engineering
Renewable and Sustainable Energy Reviews | Year: 2014

Solar energy, at the present time is considered as an important source in electricity generation. Electricity from the solar energy can be generated using solar photovoltaic (PV) modules. The maximization of solar power extracted from a PV module is of special concern as its efficiency is very low. The output power of a PV module is highly dependent on the geographical location and weather conditions such as solar irradiation, shading and temperature. To obtain maximum power from PV module, photovoltaic power system usually requires maximum power point tracking (MPPT) controller. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) based maximum power point tracker for PV module has been presented. To extract maximum power, a DC-DC boost converter is connected between the PV module and the load. The duty cycle of DC-DC boost converter is modified with the help of the ANFIS reference model, so that maximum power is transferred to load. Due to the complexity of the tracker mechanism and non-linear nature of photovoltaic system, the artificial intelligence based technique, especially the ANFIS method, is used in this paper. In order to observe the maximum available power of PV module, the ANFIS reference model directly takes in operating temperature and irradiance level as input. The response of proposed ANFIS based control system shows accuracy and fast response. The simulation result reveals that the maximum power point is tracked satisfactorily for varying irradiance and temperature of PV module. Simulation results are provided to validate the concept. © 2014 Elsevier Ltd.

Karande P.,Government Polytechnic | Chakraborty S.,Jadavpur University
Materials and Design | Year: 2012

The role that materials play in the design and proper functioning of the products has already been well acknowledged. An incorrectly selected material for a given product may cause premature failure of the final product. The right choice of the available material is critical to the success and competitiveness of the manufacturing organization. The earlier researchers have attempted to solve the material selection problems employing various mathematical tools and techniques. But it is interesting to note that almost all those techniques are affected by the weights assigned to the considered selection criteria and also by the normalization procedure adopted to make the elements of the decision matrix comparable. Hence, there is an ardent need for a material selection method that would remain unaffected by the criteria weights and normalization procedure. In this paper, multi-objective optimization on the basis of ratio analysis (MOORA) method is applied to solve some of the common material selection problems. The performance of the reference point approach and full multiplicative MOORA method are also tested for the considered problems. It is observed that all these three methods are very simple to understand, easy to implement and provide almost exact rankings to the material alternatives. © 2012 Elsevier Ltd.

Luthra S.,Government Polytechnic | Kumar S.,International Institute of Technology and Management | Garg D.,National Institute of Technology Kurukshetra | Haleem A.,Jamia Millia Islamia University
Renewable and Sustainable Energy Reviews | Year: 2015

Rapidly increasing energy demand and growing concern about economic and environmental consequences call for renewable/sustainable energy technologies? adoption in India. Renewable/sustainable energy technologies have faced a number of constraints that have affected their rate of adoption. In this paper an attempt has been made to identify and rank the major barriers in the adoption of 'renewable and green' energy technologies in the Indian context. Twenty-eight barriers have been identified from an extensive literature review. These identified barriers have been categorized into seven dimensions of barriers, i.e. Economical & Financial; Market; Awareness & Information; Technical; Ecological and Geographical; Cultural & Behavioral; and Political & Government Issues. Analytical Hierarchy Process (AHP) technique has been utilized for ranking of barriers to adopt renewable/sustainable technologies in the Indian context. All pair comparisons in AHP have been made based on experts' opinions (selected from academia and industry). Sensitivity analysis has also been made to investigate the priority ranking stability of barriers to adopt renewable/sustainable technologies in the Indian context. This paper may help practitioners, regulators and academician focus their future efforts in adoption of 'renewable/sustainable energy technologies' in India. Further, this understanding may be helpful in framing the policies and strategies towards adoption of renewable/sustainable energy technologies. © 2014 Elsevier Ltd. All rights reserved.

Athawale V.M.,Government Polytechnic | Chakraborty S.,Jadavpur University
International Journal of Industrial Engineering Computations | Year: 2011

Industrial robots are mainly employed to perform repetitive and hazardous production jobs, multi-shift operations etc. to reduce the delivery time, improve the work environment, lower the production cost and even increase the product range to fulfill the customers' needs. When a choice is to be made from among several alternative robots for a given industrial application, it is necessary to compare their performance characteristics in a decisive way. As the industrial robot selection problem involves multiple conflicting criteria and a finite set of candidate alternatives, different multi-criteria decision-making (MCDM) methods can be effectively used to solve such type of problem. In this paper, ten most popular MCDM methods are considered and their relative performance are compared with respect to the rankings of the alternative robots as engaged in some industrial pick-n-place operation. It is observed that all these methods give almost the same rankings of the alternative robots, although the performance of WPM, TOPSIS and GRA methods are slightly better than the others. It can be concluded that for a given industrial robot selection problem, more attention is to be paid on the proper selection of the relevant criteria and alternatives, not on choosing the most appropriate MCDM method to be employed. © 2011 Growing Science Ltd. All rights reserved.

Birajdar G.K.,Priyadarshini Institute of Engineering and Technology | Mankar V.H.,Government Polytechnic
Digital Investigation | Year: 2013

Today manipulation of digital images has become easy due to powerful computers, advanced photo-editing software packages and high resolution capturing devices. Verifying the integrity of images and detecting traces of tampering without requiring extra prior knowledge of the image content or any embedded watermarks is an important research field. An attempt is made to survey the recent developments in the field of digital image forgery detection and complete bibliography is presented on blind methods for forgery detection. Blind or passive methods do not need any explicit priori information about the image. First, various image forgery detection techniques are classified and then its generalized structure is developed. An overview of passive image authentication is presented and the existing blind forgery detection techniques are reviewed. The present status of image forgery detection technique is discussed along with a recommendation for future research. © 2013 Elsevier Ltd. All rights reserved.

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