  We present and discuss a method to identify substructures in combined
angular-redshift samples of galaxies within Clusters. The method relies on the
use of Discrete Wavelet Transform (hereafter DWT) and has already been applied
to the analysis of the Coma cluster (Gambera et al. 1997). The main new
ingredient of our method with respect to previous studies lies in the fact that
we make use of a 3D data set rather than a 2D. We test the method on mock
cluster catalogs with spatially localized substructures and on a N-body
simulation. Our main conclusion is that our method is able to identify the
existing substructures provided that: a) the subclumps are detached in part or
all of the phase space, b) one has a statistically significant number of
redshifts, increasing as the distance decreases due to redshift distortions; c)
one knows {\it a priori} the scale on which substructures are to be expected.
We have found that to allow an accurate recovery we must have both a
significant number of galaxies ($\approx 200$ for clusters at z$\geq 0.4$ or
about 800 at z$\leq$ 0.4) and a limiting magnitude for completeness $m_B=16$.
The only true limitation to our method seems to be the necessity of knowing
{\it a priori} the scale on which the substructure is to be found. This is an
intrinsic drawback of the method and no improvement in numerical codes based on
this technique could make up for it.
