NITIN KESHAORAO DHOTE
@stvincentngp.edu.in
Associate Professor & Head, Electrical Engineering
St. Vincent Pallotti College of Engineering & Technology
RESEARCH INTERESTS
Power System protection
Dissolved Gas Analysis
Electrical Power System
Renewable Energy Sources
Scopus Publications
Scopus Publications
Swapna Choudhary, Nitin Dhote, Ashwini A Deshpande, Ansh Sambhariya, and Poorvi K Joshi
Seventh Sense Research Group Journals
H Stinia, K Kukliński, A Jaiswal, R Fadnavis, Sushmit Meshram, N Dhote, G Gadge, M Dudek, and A Raźniak
IOP Publishing
Swapna Choudhary, Kamlesh Kalbande, and Nitin Dhote
IEEE
At present, there are different types of pesticides sprayer but in general, farmers prefer the use of backpack type sprayer, which is being operated by many farmers across the globe due to its economical and low maintenance characteristics. With the assistance of this system, farmers can spray pesticides at their farms. However, it consumes more time and labour cost is comparatively high. Famers, who are spraying pesticides are tormented by it and makes them more vulnerable to their health, eyes and they will also develop a lumbar pain due to the weight of the sprayer. This paper proposes automated spraying machines as a way to reduce both time and labour cost.
Nitin K. Dhote and J.B. Helonde
The Korean Institute of Electrical Engineers
Power transformer is one of the most important equipments in electrical power system. The detection of certain gases generated in transformer is the first indication of a malfunction that may lead to failure if not detected. Dissolved gas analysis (DGA) of transformer oil has been one of the most reliable techniques to detect the incipient faults. Many conventional DGA methods have been developed to interpret DGA results obtained from gas chromatography. Although these methods are widely used in the world, they sometimes fail to diagnose, especially when DGA results falls outside conventional method codes or when more than one fault exist in transformer. To overcome these limitations, fuzzy inference system (FIS) is proposed. 250 different cases are used to test the accuracy of various DGA methods in interpreting the transformer condition.
Nitin K. Dhote and Jagdish B. Helonde
Hindawi Limited
Dissolved gas analysis (DGA) of transformer oil has been one of the most reliable techniques to detect the incipient faults. Many conventional DGA methods have been developed to interpret DGA results obtained from gas chromatography. Although these methods are widely used in the world, they sometimes fail to diagnose, especially when DGA results fall outside conventional methods codes or when more than one fault exist in the transformer. To overcome these limitations, the fuzzy inference system (FIS) is proposed. Two hundred different cases are used to test the accuracy of various DGA methods in interpreting the transformer condition.