1. Methods that determine powers and reactions in
the
working organ of hydraulic
one
bucket excavator TYPE O&K RH 200 C.
Methods that determine powers and support reactions in typical points of working organ
of
hydra
ulic one bucket excavator,
"shovel"
typ
e
. We have chosen hydraulic one buc
ket
excavator type O&K RH 200 C
since
this machine is used in big opencast mines in
Bulgaria.
2. Determining the power of cylindrical mills' engines via neural network with
independent entry parameters.
An attempt is
made to train a neural network to determine the powe
r of cylindrical mills'
engines
using program QwikNet 2.23. As a result
,
we have received trained neural
netwo
rk with maximum error 3.16224%..
It can be used in
the
determination of
the
approximate power
of cylindrical mil
ls’ electric engine, but it can
not be considered
an
accurate mathematical model.
3. Congestion of slacks and volumes among bottoms, necks and coatings of cylindrical
mills.
Researching the reasons for
the
appearance of slacks and volum
es among bottoms, necks
and coatings of cylindrical mills. An observation of these slacks in cylindrical ball mills
,
type
МШЦ 4
,
5
x 6 is conducted. Engineering solutions for solving the problem are
offered.
4.
Determining the installed power of cone brea
kers’ (for small and medium breaking)
engines via neural network with geometric entry parameters.
A neural network to determine the power of cone breakers' (for small and medium
breaking) engines, using program QwikNet 2.23 is trained. As a result
,
we have
received
trained neural network with maximum error

1,6329.10

7
.. It can be used in determination
of power of these cone breakers’ engine
s, but it can
not
be considered an
accurate
mathematical model.
5.
Methods for choice of crane for lifting, moving, l
oading and unloading of heavy
details, in mining enterprises' open

air warehouses.
There are methods
developed
for choice of crane for lifting of large scale and heavy
details. These methods refer both to work with one crane and use of
two cranes. They
in
clude analytical
expressions that determine loadability of
a
chosen machine and check
via
a safety
coefficient.
6. Determining the power of cylindrical mills' engines via neural network with dependent
entry parameters.
A successful attempt is made to t
rain a neural network to determine the powe
r of
cylindrical mills' engines
using program QwikNet 2.23. As a result
,
we have received
trained neural network with maximum error 3,762.10

2
%.. It can be used in
the
determination of
the
power of cylindr
ical mil
ls’ electric engines and
it can be considered
an
accurate mathematical model.
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