The paper is concerned with principal component analysis and factor analysis of data for three phase asynchronous electrical machines of 300 W. The observed data are: torque (M), rotation speed (n), voltage (U) and current (I). The number of four analyzed variables: torque (M), rotation speed (n), phase voltage (U) and phase current (I) can be reduced using the proposed multivariate methods: principal component analysis and factor analysis. The components/factors explaining 99,5% (star configuration), respectively 99,7% (delta configuration) of total amount of variation for the data are the first two components/factors; so the number of variables can be reduced to only two factors. Although very useful for explaining relationships between data and for simplification reasons, this reduction of the number of the variables produces a certain loss of information.
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