Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Antony, D.

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    Genetic algorithm in location identification of AEPD source: Some aspects
    (IEEE Computer Society, 2013) Punekar, G.S.; Antony, D.; Bhavanishanker, T.; Nagamani, H.N.; Kishore, N.K.
    Using the experimental data obtained from an Acoustic Emission Partial Discharge (AEPD) system, efforts are made to locate the source of Partial discharge (PD) with a transformer tank. The AEPD data with 8 sensors (available in the literature) is numerically experimented with a Genetic Algorithm, although minimum of 4 sensors only are necessary for identifying the location. With eight sensors, four sensors considered at a time, form 70 ( 8C4) combination of sensors. The effect, implication and usage of superfluous sensor data in identifying the location with GA is analyzed and reported. Results are compared with Newton's method. © 2013 IEEE.
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    Improvements in AEPD location identification by removing outliers and post processing
    (Institute of Electrical and Electronics Engineers Inc., 2016) Antony, D.; Punekar, G.S.
    The mathematical model of an Acoustic Emission Partial Discharge (AEPD) system is solved in the literature using Newton's method with redundant number of sensors (more than 4; eight in this case). The system for numerical experiments consists of eight sensors. The algorithm is implemented using three different initial guesses. For the calculated PD source coordinates, histograms are plotted. After finding the mean and standard deviation, coordinate values which are lying outside different fractions of sigma are removed. The average of remaining set is calculated and it is found that, the accuracy of location identification can be greatly improved. © 2015 IEEE.
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    Case studies on transformer fault diagnosis using dissolved gas analysis
    (IEEE Computer Society, 2017) Shanker, T.B.; Nagamani, H.N.; Antony, D.; Punekar, G.S.
    In this paper the results of dissolved gas analysis (DGA) along with details of the DGA data from in-service transformers are discussed. Two case studies are given of which, first case study deals with the detection of the partial discharge and the second case study deals with the detection of thermal fault in transformers at thermal power stations in India. The interpretation of DGA data are conducted using key gas method. The interpretations are validated by the application of gas ratio method. Gas ratio method included in this study are Rogers ratio and Doernenburg ratio. © 2017 IEEE.
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    Effects of error in time-delay on AEPD source localization using Newton's method: Numerical experimentation
    (Institute of Electrical and Electronics Engineers Inc., 2017) Antony, D.; Punekar, G.S.; Kishore, N.K.
    Newton's method is one of the commonly used methods for acoustic emission partial discharge (AEPD) source localization in power transformers. The major problem in the AEPD source localization is the difficulty in accurately measuring the signal arrival time from the source to the multiple sensors. The exact instant at which the partial discharge (PD) occurs is not known. Therefore, instead of the absolute time, the time-delay in signal reception of each sensor with respect to the sensor nearest to the PD source is estimated. In the present study the effect of time-delay error on the accuracy of the PD source localization is analyzed through numerical experimentations. The solution of the Newtons's method in turn depends on the choice of the initial guess. Hence, different initial guesses are selected for Newton's method randomly. For a fixed set of coordinates for the four sensors and the PD source positions, the time-delays are theoretically calculated. The error is systematically increased in the calculated time-delay to form different groups of time-delays. The PD source is localized using each initial guess for all the groups of time-delays to analyze the effect of error in time-delay on accuracy of PD source localization. The error in time-delay greatly affects the AEPD source localization. Moreover, if Newton's method with a bad initial guess is used then the errors in AEPD source localizations are not systematic. © 2017 IEEE.