  Data collapse enables comparison of measurement data measured in different
laboratories on different samples. In the case of energy losses in Soft
Magnetic Materials (SMM) the data collapse is possible to achieved only if the
measurement data can be described by the two components formula. For more
complicated cases we propose to perform data collapse's sequence in the
two-dimensional subspaces $L_{i,i+1}$ spanned by the appropriate powers of
frequency $\{f^{i},f^{i+1}\}$. Such approach enables the data comparison in the
different two-dimensional subspaces. This idea has been tested with measurement
data of the four SMM-s: amorphous alloy
\textrm{Fe}_{78}\textrm{Si}_{13}\textrm{B}_{9}$, amorphous alloy
$\textrm{Co}_{71.5} \textrm{Fe}_{2.5} \textrm{Mn}_{2} \textrm{Mo}_{1}
\textrm{Si}_{9} \textrm{B}_{14}$, crystalline material -- oriented
electrotechnical steel sheets 3% Si--Fe, iron--nickel alloy $79%
\textrm{Ni}-\textrm{Fe}$. Intermediate calculations revealed interesting
property of the energy losses in the cristalline and amorphous SMM-s which lead
to the following hypothesis. Let $P_{tot\,1,2}=f_{1,2}(1+f_{1,2})$ be scaled
two-components formula for the energy loss in SMM, where $f_{1,2}$ is the
corresponding scaled frequency. Then the scaled energy losses' values in
amorphous SMM are below the second order universal curve
$P_{tot\,1,2}=f_{1,2}(1+f_{1,2})$, whereas the scaled energy losses' values in
crystalline SMM are above that universal curve.
