noise analysis tools at virgo
DESCRIPTION
Noise Analysis Tools at Virgo. Summary. Tools for monitoring non-stationary noises Project for an automatic noise budget tool. Part 1 Non-Stationary Noise Monitor. Compute band-limited RMS Identify lines. Trends Correlation with ITF status. Non Stationary Noise Monitor. Purpose - PowerPoint PPT PresentationTRANSCRIPT
Gabriele Vajente
ILIAS WG1 meeting - Frascati 21.03.06
Noise Analysis Tools Noise Analysis Tools at Virgoat Virgo
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 2
SummarySummary
Tools for monitoring non-stationary noises
Project for an automatic noise budget tool
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 3
Part 1Part 1Non-Stationary Noise MonitorNon-Stationary Noise Monitor
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 4
Non Stationary Noise MonitorNon Stationary Noise Monitor
PurposeMonitor time evolution of noise level in dark fringe
Find correlation with ITF status (alignment, environmental conditions, etc.)
Two partsRunning online: NonStatMoni
Running offline periodically: NonStatMoniOffline
Compute band-limited RMS
Identify lines
Trends
Correlation with ITF status
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 5
NonStatMoni – Band-limited RMSNonStatMoni – Band-limited RMS
Band-limited RMSCompute short spectra (1, 5, 10 s) every 1 s
Output RMS in bands in the main data stream
Fully configurable (channel, spectrum length, etc.)
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 6
NonStatMoni – Lines identification 1NonStatMoni – Lines identification 1
Lines identificationSeparate lines from “background”
Band-limited RMS of background
Frequency, height, SNR of main lines (SNR threshold)
Running only during “locked” periods
Mai
n da
ta s
trea
m
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 7
NonStatMoni – Lines identification 2NonStatMoni – Lines identification 2
In main data stream
Number of lines found
Background band-limited RMS
Frequency, height, SNR for each line found
full RMS
bkg RMS
full RMS
bkg RMS
1.11 kHz
3.88 kHz
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 8
NonStatMoniOffline - SummaryNonStatMoniOffline - Summary
Run periodically, analyze all locks of last period
Output as web pages
Summary of monitored channels
Links to locked periods details
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 9
NonStatMoniOffline – Lock details 1NonStatMoniOffline – Lock details 1
Run periodically, analyze all locks of last period
Output as web pages
Plot of RMS time evolution
Spectrum of RMS evolution
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 10
NonStatMoniOffline – Lock details 2NonStatMoniOffline – Lock details 2
Run periodically, analyze all locks of last period
Output as web pages
Time plot
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 11
NonStatMoniOffline – Lock details 3NonStatMoniOffline – Lock details 3
Run periodically, analyze all locks of last period
Output as web pages
Spectrum plot
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 12
NonStatMoniOffline – Lock details 4NonStatMoniOffline – Lock details 4
Run periodically, analyze all locks of last period
Output as web pages
Coherence table and plots
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 13
Examples of applicationsExamples of applications
Enviromental monitoring (seismometers and microphones)
Airplanes
F. Fidecaro
Monitor band-limited RMS for seismic sensors in all buildings.
One can recover direction and speed
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 14
Correlation with alignment and freq noiseCorrelation with alignment and freq noise
PR yaw BS yaw
NE pitch
Freq. noise
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 15
Modes ring-downModes ring-down
During lock acquisition mirror and violin modes are strongly excited
Extimation of Q factor
3884 Hz
= 106 ± 7 sQ = 1.29 x 106
167 Hz
= 550 ± 20 sQ = 2.89 x 105
Line
hei
ght [
Hz/
rHz]
RM
S b
etw
een
100
and
200
Hz
[Hz/
rHz]
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 16
Part 2Part 2Automatic Noise Budget ProjectAutomatic Noise Budget Project
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 17
Automatic Noise BudgetAutomatic Noise Budget
PurposeTo measure precise projection of technical noises into dark fringe (or other channels)
WhyTo precisely identify the contribution of the most important noise sources
To track the evolution of noise couplings
To gain data to model noise couplings
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 18
MethodMethod
1. Measure transfer function from error/correction signal to dark fringe with noise injection
2. Project the normal noise using the measured TF
Interferometer
Control loop
Dar
k fr
inge
NOISE
NOISE
SINGLE CAVITY
SINGLE CAVITY
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 19
TF measurement methodsTF measurement methods
Full measurementBy injecting (white) noise into each channel separatelySlow (at least 60s per channel)Precise measurements of TFsMight cause saturation problems or unlocksNeed to “shape” the noise
Fast measurementMeasure once the TFs with full method
Use calibration lines to correct their overall gain
Fast (can inject lots of lines simultaneously)
Might be not very precise
Can easily track time evolution
Lines measurementInject several (10) lines for each d.o.f. at different frequencies
Need to know the approximate shape of the TF
Faster than full, more accurate than fast
Less saturation problems
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 20
Technical noise sourcesTechnical noise sources
Control noises
Longitudinal (DARM, MICH, PRCL) 3 dof
Angular (PR, BS, NI, NE, WI, WE tx & ty) 12 dof
Input beam noises
Frequency noise 1 dof
Laser power noise 1 dof
Input beam jitter (translation & tilt) 4 dof
IMC controls (angular and longitudinal) 3 dof
Modelled noises
Shot noise (need only power measurements)
Dark noise
DAC noise
Phase noise
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 21
Outcomes of the toolOutcomes of the tool
Noise budgets
Transfer functions
Using permanent calibration linesTrack time evolution of noise couplings and ITF performances
Better identify non-stationarity sources
ILIAS WG1 meeting, Frascati 21.03.06 – Gabriele Vajente 22
ConclusionsConclusions
Non-stationary MonitorDeveloped and tested, already running onlineMonitor dark fringe and 25 environmental channelsAutomatic generate summary web pages
Automatic Noise BudgetClear projectAlready tested some noise injection in single cavity configuration