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Power Spectral Density (PSD)
       Probability Density Functions (PDF)
                 Seismic Data QC,
     Network Des...
PSD Probability Density Function for ISCO
                 BHZ



Individual histograms for each period
are converted to P...
Method: Power Spectral Density Probability Density Functions
                                           Raw waveforms cont...
Power Frequency Distribution Histograms
                   PSDs are accumulated in 1dB power
                   bins
     ...
Artifacts in the Noise Field
HLID - automobile traffic along
a dirt road only 20 meters from
station HLID creates a 20-30d...
Current Noise PDF Uses
                                  Hailey, ID 08/2001-05/2002
Network SOH monitoring
       Dead sta...
Current Noise PDF Uses

Network SOH monitoring
       Dead station
       Detection Modeling    GOTO:
       Design Planni...
Current Noise PDF Uses

Network SOH monitoring
       Dead station           Lightning strike hours after
       Detection...
Current Noise PDF Uses

Network SOH monitoring
       Dead station
       Detection Modeling
                             ...
Regional Network Simulation
6 stations from NM regional network with
well established noise baselines.

Detection threshol...
Detection Maps Used for Prioritization of Maintenance Issu
        Backbone Stations on Satellite GR4
                    ...
Current Noise PDF Uses

Network SOH monitoring
       Dead station
       Detection Modeling 3km from train               ...
Current Noise PDF Uses

Network SOH monitoring
       Dead station            GSN Standing Committee Report:
       Detect...
Current Noise PDF Uses

Network SOH monitoring
       Dead station
       Detection Modeling
       Design Planning
Statio...
Plans for future development: QDAT
Database hourly PSDs to allow:
       creative selection of data for PDF generation
   ...
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 s...
Plans for future development: QDAT
Database hourly PSDs to allow:
       creative selection of data for PDF generation
   ...
Plans for future development: QDAT
Database hourly PSDs to allow:
       creative selection of data for PDF generation
   ...
Regional Noise Characteristics




                   QuickTime™ and a
        TIFF (Uncompressed) decompressor
          ...
Plans for future development: QDAT
Database hourly PSDs to allow:
       creative selection of data for PDF generation
   ...
Constructed from
90th percentile
computed from
PDFs binned for
each hour of the
day.




Data from
Sept 2001 to
Oct 2004  ...
Constructed from
90th percentile
computed from
PDFs binned for
each month of
the year.


                                 ...
Plans for future development: QDAT
Database hourly PSDs to allow:
       creative selection of data for PDF generation
   ...
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
   ...
McNamara_NoiseDetection.ppt
McNamara_NoiseDetection.ppt
McNamara_NoiseDetection.ppt
McNamara_NoiseDetection.ppt
McNamara_NoiseDetection.ppt
McNamara_NoiseDetection.ppt
McNamara_NoiseDetection.ppt
McNamara_NoiseDetection.ppt
McNamara_NoiseDetection.ppt
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McNamara_NoiseDetection.ppt

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McNamara_NoiseDetection.ppt

  1. 1. Power Spectral Density (PSD) Probability Density Functions (PDF) Seismic Data QC, Network Design Tool and Capability Modeling Developers: Dan McNamara, Ray Buland @ ANSS NOC Richard Boaz @ Boaz Consultancy Others involved: Harold Bolton, Jerry Mayer @ ANSS IDCC Paul Earle, Harley Benz, Rob Wesson @ ANSS NEIC Tim Ahern , Bruce Weertman @ IRIS DMC
  2. 2. 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.
  3. 3. Method: Power Spectral Density Probability Density Functions Raw waveforms continuously extracted from waveserv 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, s 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.
  4. 4. 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
  5. 5. 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). QuickTime™ and a Body waves occur as low TIFF (Uncompressed) decompressor are needed to see this picture. 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.
  6. 6. 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
  7. 7. Current Noise PDF Uses Network SOH monitoring Dead station Detection Modeling GOTO: Design Planning ANSS QC Station Quality Site quality http://gldqc/cgi-bin/pdf Current stations IRIS DMC future backbone http://www.iris.washington.edu/servlet/quackqu ANSS Rankings ery/ Noise Research sources hurricanes ambient noise model
  8. 8. Current Noise PDF Uses Network SOH monitoring Dead station Lightning strike hours after Detection Modeling Station began operation Design Planning Station Quality Site quality Current stations future backbone ANSS Rankings Noise Research sources hurricanes ambient noise model
  9. 9. Current Noise PDF Uses Network SOH monitoring Dead station Detection Modeling Brune minimum Mw Mw Design Planning Station Quality Site quality Current stations future backbone ANSS Rankings Noise Research sources hurricanes ambient noise model
  10. 10. Regional Network Simulation 6 stations from NM regional network with well established noise baselines. Detection threshold lowered in Mw New Madrid region by 0.1-0.3 units with addition of NM network. PVMO Regional Station Limitations: - high noise in Cultural noise band (1-10Hz) - PVMO instrumented with Guralp CMG- 3esp seismometer (50Hz) and Quanterra Q- 380 digitizer at 20sps. Power rolloff at Nyquist~10Hz.
  11. 11. Detection Maps Used for Prioritization of Maintenance Issu Backbone Stations on Satellite GR4 ANSS backbone distributed over 2 satellites to protect against total network outage. Simulations demonstrate detection in the event of a Mw satellite failure. Maintenance decisions could be made based on real-time changes in detection thresholds. Backbone stations on Satellite SM5 GR4 expected to die within 3 years.
  12. 12. 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 QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture. QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture. future backbone ANSS Rankings Noise Research sources Meremonte, M., D. McNamara, A. Leeds, D. Overturf, J. McMillian, hurricanes and J. Allen, ANSS backbone station installation and site characterization, EOS Trans. AGU, 85(47), 2004. ambient noise model
  13. 13. Current Noise PDF Uses Network SOH monitoring Dead station GSN Standing Committee Report: Detection Modeling Design Planning Station Quality An Assessment of Seismic Noise Site quality Characteristics for the ANSS Backbone and Selected Regional Broadband Stations Current station future backbone By D. McNamara, Harley M. Benz and W. ANSS Rankings Leith Noise Research sources hurricanes Also ambient noise model McNamara, D.E., H.M. Benz and W. Leith, USGS Open-File Report, in press, 2005.
  14. 14. 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.
  15. 15. 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
  16. 16. Hurricanes QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture.
  17. 17. Seismometer casing differential motion QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture.
  18. 18. 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
  19. 19. 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
  20. 20. Regional Noise Characteristics QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture.
  21. 21. 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
  22. 22. 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).
  23. 23. 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.
  24. 24. 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
  25. 25. Noise Baselines: Which Statistic? Mode, Average or Median
  26. 26. 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 spectragrams Research noise sources baselines auto ID of problem artifacts Operations vault design telemetry performance automated problem reporting and notification

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