Date: 12th August 2023
Time: 2:30pm – 4:30pm
Meet the Speakers
Debangshu Dey
Post Hold: Associate Professor in the Electrical Engineering Department, Jadavpur University
Coordinator: Mr. Dipanjan Datta, Assistant Professor, (Contact no. 9674298076)
Abstract
The growth in economy and developmental index in India has increased the per capita energy requirement in the country. The government has also taken up firm programmes to extend grid power to the entire population.
On the other hand, a large section of the power infrastructure in developed as well as developing countries has become old. To extend the life of existing infrastructure, most of the power utilities now-a-days give effort towards condition-based predictive testing and maintenance. Costs can be reduced, first of all, by a transition from time-based maintenance (TBM) to condition based maintenance (CBM), as well as reliability can be increased if the actual conditions of the expensive high voltage components within the electric power transmission systems are accurately known. It is pertinent to mention here that such costly equipment like power transformers cannot be replaced overnight, if required. Proper asset management strategy is required which requires advanced methods and systems to obtain reliable condition monitoring data of such critical equipment in the power infrastructure.
In India, there exists a lack of indigenous research in this domain, which is evident from number of research publications and possession of intellectual property rights. Most of the equipment and diagnosis packages are based on any single methodology and are foreign proprietary, which are used in our country as a black box. But considering the present scenario of our country’s power infrastructure this is high time to develop indigenous tools for such CBM of various electrical equipment.
Hence, the present topic will throw some light on the conducted research and developed systems to address this issue by synergizing data acquisition, advanced signal processing and machine learning tools. This topic has practical importance in Indian power scenario and also has large societal impact considering the economic benefits as well as the benefits in getting uninterrupted power supply derived from such condition monitoring which is in line with the present day need for resource-constrained translational technologies.
