•A set of modes (20 mode) are applied at the same time modulated by different frequencies.
The interaction matrices have been acquired for a total number of modes up to 600.
The following parameters for the IM acquisition have been explored in order to optimize the
performances of the sinusoidal technique:
- ordering of the modes inside the set
- the lower frequency of each set; this in order to avoid disturbances induced by system
vibration
- the frequency of each mode inside a single set has been calculated in order to avoid the
cross-talk between the modes
-the mode amplitudes have been selected optimizing the signal on the WFS
• 30 set of 20 reordered modes for a total of 600 modes
• starting frequency at 30Hz .
•The reconstructors obtained from sinusoidal and push and pull techniques have been tested in
closed loop in order to evaluate their performances. The closed loop has been performed with
and without the disturbance simulating the atmospheric turbulence (seeing = 0.8” wind speed =
6 ms equivalent).
Convolution of the frequency in the time integration selected, in order avoid the
cross-talk between the modes
Delta freq between frequencies for each integration time selected:
delta_freq_hz=[10.,5.,3.33,2.5,2.0,1.67,1.43,1.25,1.11,1.0,0.5,0.33,0.25,0.2,0.17,0.14,0.13,0.11,0.10]
time_integr_s=[.1,.2,.3,.4,.5,.6,.7,.8,.9,1,2,3,4,5,6,7,8,9,10.]
Time integr:
0.1
0.4
0.8
1.0
4.0
8.0
Plot of max values of convolution for each integration time.
The red line is a soglia=3sigma of conv. Valuated in order to find a minimum value for the cross talk
10.0
delta_freq_set-f_0 minimum range between frequecies of the array
1-soglia
0.35
0.67
0.76
0.79
0.89
0.92
0.93
6.52588
12.4676
14.2740
15.4290
32.4636
47.9820
49.8036
0.1
1.60146
3.05956
3.50285
3.75875
7.72355
10.7698
12.0447
0.4
0.798454
1.52543
1.74645
1.87336
3.84842
5.36223
5.99046
0.8
0.637861 0.160563 0.0847416
1.21863 0.306753 0.161896
1.39519 0.351198 0.185352
1.49643 0.376492 0.197601
3.07671 0.770308 0.381285
4.29043
1.07027 0.533566
4.79032
1.19455 0.597626
1.0
Time_integr
4.0
8.0
0.0623665
0.119152
0.136415
0.145840
0.314583
0.431211
0.478733
10.0
Mappa dei massimi (log scale)
Signal_sin
Mappa freq corrisp al max
Signal_pp
problem
Modo 0
Abs(signal_pp)
rms_ref
rms_sin
0.176775
0.186964
diff
Mappa dei massimi (log scale)
Signal_sin
Modo 30
Mappa freq corrisp al max
Signal_pp
Abs(signal_pp)
diff
Single mode_408
metodo prova media dati
1090 subap su 1220
freq_modulation (35.7444)
89%  media 10 data
846 subap su 1220
freq_modulation (35.7444)
69%  NO MEDIA
AMP_PP:2e-07
AMP_SIN:2e-08
x=[1,2,3,4,5,10,12]
Y=[69,78,82,85,86,89]
At least there is not cross-talk effect, the choice of df = 0.478 Hz seems sensible
Mappa dei massimi (log scale)
Signal_sin
Mappa freq corrisp al max
Signal_pp
Amplitude problem?
Modo 0
Abs(signal_pp)
amp_pushpull_modo(m0) 2.01977e-006
amp_sin_modo(m0) 2.01977e-007
diff
amp_sin_modo(m0)
rms_sin 0.16
2.01977e-006
amp_sin_modo(m0)
rms_sin
0.19
2.01977e-007 amp_pushpull_modo(m0) 2.01977e-006
rms_ref] 0.18
Available Integration time ?
Optimization of bandwidth according
to number of modes in each set
Amplitude optimization of
chosen modes inside a
single set
Determination of best
frequency set
-Creation of an automatization of the overall process
-Creation of a routine for cleaning measured modes
-Need to re-do measurements with new improvements
Cross_talk_check
Log
0.1 sec
M50x50 of modes
Df=1Hz (freq=[30,80] Hz)
Each row is found with cross
talk procedure
Log
1 sec
Log
10 sec