Transcript Document 7371914

Power Spectral Density (PSD)
Probability Density Functions (PDF)
A Seismic Data QC and Network Design Tool
Developers:
Dan McNamara, Ray Buland @ ANSS NOC
Richard Boaz @ Boaz Consultancy (formerly IRIS PASSCAL)
Others involved:
Harold Bolton, Jerry Mayer @ ANSS IDCC
Tim Ahern , Bruce Weertman @ IRIS DMC
USGS-IRIS Collaborative QC Development Effort
USGS noise PDF algorithm USGS informal QC PDF IRIS DMC Quack RFP Proposal funded Programmer hired DMC QUACK PDF operational BSSA Paper published USGS Formal QC PDF Stand Alone PDF -
Summer 2001
Fall 2001
Fall 2002
Spring 2003
Fall 2003
June 2004
Aug. 2004
Sept. 2004
Oct. 2004
Phase II Development QDAT:
database PSDs
analyst GUI
FY 2005-2006
PDF Locations
ANSS NOC IDCC
http://gldqc/cgi-bin/pdf (ANSS backbone, internal USGS)
IRIS DMC (IU, II, UW, NM most global and US regional networks)
http://www.iris.washington.edu/servlet/quackquery/
IRIS PASSCAL
Earthscope USarray
http://www.iris.washington.edu/servlet/quackquery_us/
Berkeley Seismic Lab
http://moho.geo.berkeley.edu/seismo/PDF/
University Utah Seismogram Network
ORFEUS
Taiwan National Seismograph Network
PDF Methods and Explanation website
http://geohazards.cr.usgs.gov/staffweb/mcnamara/PDFweb/Noise_PDFs.html/
Method: Power Spectral Density Probability Density Functions
Raw waveforms continuously extracted from waveserver
In 1 hour segments, overlapping by 50%.
PSD pre-processing:
trend and mean removal
10% cos taper applied
No screening for earthquakes, or transients and
instrumental glitches such as data gaps, clipping, spikes,
mass re-centers or calibration pulses
PSD calculated for each 1 hour segment
With ASL algorithm for direct comparison
to NLNM.
PSD is smoothed by averaging powers over
full octaves in 1/8 octave intervals.
Points reduced from 16,385 to 93.
Center points of octave averages shown.
Power Frequency Distribution Histograms
PSDs are accumulated in 1dB power bins
from -200 to -50dB.
Distributions are generated for each period
in 1/8 octave period intervals.
Histograms vary significantly by period.
- 1s has strong peak and a narrow range
of powers.
- bimodal distributions at 10, 100s
-All have sharp low-power floor with
higher power tails
Next step:
Convert histograms to
Probability Density Functions
PSD Probability Density Function for ISCO BHZ
Individual histograms for each period are
converted to PDFs by normalizing each
power bin by total number of
observations.
Total distribution of powers plotted.
Not simply minimum powers.
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Artifacts in the Noise Field
HLID - automobile traffic along
a dirt road only 20 meters from
station HLID creates a 20-30dB
increase in power at about 0.1
sec period (10Hz). This type of
cultural noise is observable in
the PDFs as a region of low
probability at high frequencies
(1-10Hz, 0.1-1s).
Body waves occur as low
probabily signal in the 1sec
range while surface waves are
generally higher power at
longer periods.
Automatic mass re-centering
and calibration pulses show up
as low probability occurrences
in the PDF.
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Current Noise PDF Uses
Hailey, ID 08/2001-05/2002
Network SOH monitoring
Dead station
Detection Modeling
Design Planning
Station Quality
Site quality
Current stations
future backbone
ANSS Rankings
Noise Research
sources
hurricanes
ambient noise model
Realistic view of noise conditions at a station. Not simply lowest levels experienced.
McNamara and Buland (2004) BSSA
Current
Noise PDF Uses
Network SOH monitoring
Dead station
Detection Modeling
Design Planning
Station Quality
Site quality
Current stations
future backbone
ANSS Rankings
Noise Research
sources
hurricanes
ambient noise model
GOTO:
IRIS DMC
http://www.iris.washington.edu/servlet/quackquery/
Earthscope USarray
http://www.iris.washington.edu/servlet/quackquery_us/
Current Noise PDF Uses
Network SOH monitoring
Dead station
Detection Modeling
Design Planning
Station Quality
Site quality
Current stations
future backbone
ANSS Rankings
Noise Research
sources
hurricanes
ambient noise model
Lightning strike hours after
Station began operation
Current Noise PDF Uses
Network SOH monitoring
Dead station
Detection Modeling
Design Planning
Station Quality
Site quality
Current stations
future backbone
ANSS Rankings
Noise Research
sources
hurricanes
ambient noise model
Brune minimum Mw
Mw
Regional Network Simulation
6 stations from NM regional network with
well established noise baselines.
Detection threshold lowered in
New Madrid region by 0.1-0.3 units
with addition of NM network.
Regional Station Limitations:
- high noise in Cultural noise band (1-10Hz)
- PVMO instrumented with Guralp CMG3esp seismometer (50Hz) and Quanterra Q380 digitizer at 20sps. Power rolloff at
Nyquist~10Hz.
Mw
PVMO
Detection Maps Used for Prioritization of Maintenance Issues
Backbone Stations on Satellite GR4
Mw
Backbone stations on Satellite SM5
ANSS backbone distributed
over 2 satellites to protect
against total network
outage.
Simulations demonstrate
detection in the event of a
satellite failure.
Maintenance decisions
could be made based on
real-time changes in
detection thresholds.
GR4 expected to die within
3 years.
Current Noise PDF Uses
Network SOH monitoring
Dead station
Detection Modeling 3km from train
20km from train
Design Planning
Station Quality
Site quality
Current stations
future backbone
ANSS Rankings
Noise Research
sources
Meremonte, M., D. McNamara, A. Leeds, D. Overturf, J. McMillian,
and J. Allen, ANSS backbone station installation and site
hurricanes
characterization, EOS Trans. AGU, 85(47), 2004.
ambient noise model
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Current Noise PDF Uses
Network SOH monitoring
Dead station
Detection Modeling
Design Planning
Station Quality
Site quality
Current station
future backbone
ANSS Rankings
Noise Research
sources
hurricanes
ambient noise model
GSN Standing Committee Report:
An Assessment of Seismic Noise Characteristics
for the ANSS Backbone
and Selected Regional Broadband Stations
By D. McNamara, Harley M. Benz and W. Leith
Also
McNamara, D.E., H.M. Benz and W. Leith,
USGS Open-File Report, in press, 2005.
Current Noise PDF Uses
Network SOH monitoring
Dead station
Detection Modeling
Design Planning
Station Quality
Site quality
Current station
future backbone
ANSS Rankings
Noise Research
sources
hurricanes
ambient noise models
McNamara, D.E., R.P. Buland, R.I. Boaz, B. Weertman, and T. Ahern, Ambient seismic
noise, Seis. Res. Lett., in press, 2005.
Plans for future development: QDAT
Database hourly PSDs to allow:
creative selection of data for PDF generation
Playback as a movie (i.e. graphic equalizer)
Additional types of visualizations
Regional noise trends
diurnal and seasonal variations
Research
noise sources
baselines
auto ID of problem artifacts
Operations
vault design
telemetry performance
automated problem reporting and
notification
Hurricanes
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Seismometer casing differential motion
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Plans for future development: QDAT
Database hourly PSDs to allow:
creative selection of data for PDF generation
Playback as a movie (i.e. graphic equalizer)
Additional types of visualizations
Regional noise trends
diurnal and seasonal variations
spectograms
Research
noise sources
baselines
auto ID of problem artifacts
Operations
vault design
telemetry performance
automated problem reporting and
notification
Plans for future development: QDAT
Database hourly PSDs to allow:
creative selection of data for PDF generation
Playback as a movie (i.e. graphic equalizer)
Additional types of visualizations
Regional noise trends
diurnal and seasonal variations
spectograms
Research
noise sources
baselines
auto ID of problem artifacts
Operations
vault design
telemetry performance
automated problem reporting and
notification
Regional Noise Characteristics
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
Plans for future development: QDAT
Database hourly PSDs to allow:
creative selection of data for PDF generation
Playback as a movie (i.e. graphic equalizer)
Additional types of visualizations
Regional noise trends
diurnal and seasonal variations
spectograms
Research
noise sources
baselines
auto ID of problem artifacts
Operations
vault design
telemetry performance
automated problem reporting and
notification
Constructed from
90th percentile
computed from
PDFs binned for
each hour of the
day.
Data from
Sept 2001 to
Oct 2004
6am local time
Noise across all periods increases 10-15dB during the working day
with the exception of the microseism band (~7-8s).
Constructed from
90th percentile
computed from
PDFs binned for
each month of
the year.
School begins
Data from
Sept 2001 to
Oct 2004
Short period noise increases during the summer months.
Microseism band (~7-8s) noise increases during the fall and winter.
Plans for future development: QDAT
Database hourly PSDs to allow:
creative selection of data for PDF generation
Playback as a movie (i.e. graphic equalizer)
Additional types of visualizations
Regional noise trends
diurnal and seasonal variations
spectograms
Research
noise sources
baselines
auto ID of problem artifacts
Operations
vault design
telemetry performance
automated problem reporting and
notification
Noise Baselines: Which Statistic?
Mode, Average or Median
Plans for future development: QDAT
Database hourly PSDs to allow:
creative selection of data for PDF generation
Playback as a movie (i.e. graphic equalizer)
Additional types of visualizations
Regional noise trends
diurnal and seasonal variations
spectograms
Research
noise sources
baselines
auto ID of problem artifacts
Operations
vault design
telemetry performance
automated problem reporting and notification