MS DEPARTMENT OF INFORMATION SYSTEM

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ONLINE DATA MONITORING FOR ASSET PREDICTIVE MAINTENANCE
(UMT, Lahore, 2022) Farhan Ahmad
Number of researches though have been conducted in order to know about the transformer oil behaviour and to know about the faults that transformer can have due to gases mixed in the oil. In this research, our main aim is to identify the faults and predict on the basis of mixed gases in the transformer oil. This research is conducted on the data set that is fetched from the real time equipment installed in the field. This equipment was installed for the purpose of identification of fault before the time. There is a gap in the field of electrical engineering that there is no prediction based on the data. There is manual trending and based on expert’s opinion, authorities do actions. SVM and KNN will be applied in order to get the predictions. These two models are selected because of data set as data set is balanced and more accurate results can be obtained. Hence, using the data set and the said models, we will identify which model will give more accuracy and we will support our results with the help of literature as well.