Abstract:
Electrical machines play an important role in our
day-to-day life. Electric machines like DC motors and 3- phase
induction motors are essential systems and widely used in
domestic, industrial and transportation systems. In order to
operate the machines optimally and efficiently, in real time
operations, it is required to predict the performance
parameters at various loaded conditions. With the
advancements in the field of predictive modelling and analytics,
several researchers have applied in the area of energy
consumption prediction, fault prediction, weather prediction,
power grid management and so on. In this paper, the machine
learning techniques are demonstrated that may be used to
examine the performance of electrical machinery by forecasting
performance characteristics like speed and efficiency. To
validate the performance of the predictive model, an
experiment was conducted at the laboratory on dc motor and 3-
phase induction motor to generate the required dataset to
train the regression algorithms. The model evaluation
metrics such MSE and the R2 value showed that the model
efficiently predicted the performance of the electrical
machines.
