HACR at Virgo: implementation and results
Gabriele Vajente
12th ILIAS WG1 meeting
Geneva, March 29th -30th 2007
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Summary
HACR algorithm
Implementation at Virgo
Some results from WSR9
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HACR algorithm
Based on HACR developed at GEO60
Search for transients in time-frequency domainTimes and frequencies with an excess of power with respect to the mean
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How HACR works
Compute short FFTs (50 ms) of a signal without averages
Frequency resolution about 40 Hz
Create a time – frequency map of the signal
),( ftF
Simulated data, white noise plus sine-gaussian
Zoom around one transient
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How HACR works
Compute an averaged spectrum over time
Using a decay average with time constant of about 10 s
Compute also the standard deviation over time for each frequency
),()( ftFfM
22 )(),()( fMftFf
),()( ftFfM
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How HACR works
Compute the deviation of the point from the mean
This gives an indication of how much each point deviates from the mean statistics of the spectrum(significance of the bin)
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f
fMftFftS
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How HACR works
Trigger if the significance is above a given threshold THIGH
Build up a cluster by searching neighboring points with significance above a lower threshold TLOW
For each cluster computeMean time and frequency (weighted average with power)Time and frequency widthMaximum and mean significanceSNR as square root of power in the cluster divided by power in the mean spectrum Number of points
Points above THIGHPoints above TLOW
CLUSTER
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Implementation at VirgoProgram written in C using FFTW and Virgo frame interfaceRunning online since a couple of weeksSome performances
10 hours of data, analyzing 11 channelstook 3.3 hours Analysis of one frame, one 20kHz channel, estimated with profiler 14 ms of machine timeLimited mainly by data access
Output sent to MySQL databaseAlso: number of cluster per second and max snr for each second sent to main data stream
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Report generator
Simple script written in Perl and OctaveQuery the database, perform basics analysis and produce plots
Time, frequency, SNR distributionTime – freuency – SNR mapsCorrelogramsCoincidences between pairs of channels
Examples at http://wwwcascina.virgo.infn.it/MonitoringWeb/HACR/
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Time – Frequency – SNR map
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Distributions
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Correlograms
WSR7 WSR9
During WSR7 strong 600mHz excitation of BS transversal motion
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Coincidences phase - quadrature
Coincidence between phase and quadrature of dark fringe signal
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Coicidences both frequency and time
20 % of all glitches are coincident both in time and frequency
dt < 0.1s df < 100 Hz
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Coincidences both time and frequency
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Conclusions
HACR is working well at Virgo
Still some tuning needed for the reports
Soon the report generator will run automatically (once every 8 hours)
HACR can give lots of information on the quality of data
Vetoes?