Seismic Network Operations
San Juan, Puerto Rico
IU SJG commences operations on: 1993,146
|Host:||US Geological Survey|
|Telemetry Status at the NEIC:||Last Data In Less Than 10 Minutes|
Vault Condition: The seismometer vault is built into a hillside and has an overburden of approximately 3 meters. Piers are isolated from floor and connected to bedrock. Temperature and humidity in the vault are stable. There is a four lane highway located 1100 feet from the vault. Traffic is heavy, and includes large trucks.
Site Geology: The vault is on interfingering lenticular units of volcanic breccia, conglomerate, sandstone and siltstone of cretaceous age. Seismometer piers are attached to decomposed rock of these materials.
|Location Code||Channel Code||Instrument||Flags||Sample Rate||Dip||Azimuth||Depth|
|30||LDO||CI/PAS pressure sensor||CW||1.00||0.00||0.00||0.00|
|30||BDO||CI/PAS pressure sensor||CW||40.00||0.00||0.00||0.00|
|20||LNZ||FBA ES-T EpiSensor Accelerometer||CG||1.00||-90.00||0.00||0.00|
|20||LN2||FBA ES-T EpiSensor Accelerometer||CG||1.00||0.00||90.00||0.00|
|20||LN1||FBA ES-T EpiSensor Accelerometer||CG||1.00||0.00||0.00||0.00|
|20||HNZ||FBA ES-T EpiSensor Accelerometer||TG||100.00||-90.00||0.00||0.00|
|20||HN2||FBA ES-T EpiSensor Accelerometer||TG||100.00||0.00||90.00||0.00|
|20||HN1||FBA ES-T EpiSensor Accelerometer||TG||100.00||0.00||0.00||0.00|
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As part of the annual calibration process, the USGS runs a sequence that includes a random, a step, and several sine wave calibrations. The USGS analyzes the random binary calibration signal in order to estimate the instrument response. The figures below show the results from the analysis of the most recent processed calibration at the station.
We use an iterative three-step method to estimate instrument response parameters (poles, zeros, sensitivity and gain) and their associated errors using random calibration signals. First, we solve a coarse non-linear inverse problem using a least squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a non-linear parameter estimation problem to obtain the least squares best-fit Laplace pole/zero/gain model. Third, by applying the central limit theorem we estimate the errors in this pole/zero model by solving the inverse problem at each frequency in a 2/3rds-octave band centered at each best-fit pole/zero frequency. This procedure yields error estimates of the 99% confidence interval.
|Loc||Chan||Cal Date||Epoch-Span||Grade||Amp Nominal Error (dB)||Amp Best Fit Error (dB)||Phase Nominal Error (degree)||Phase Best Fit Error (degree)||Sensor||Cal Type|
|10||BHZ||2012:138||2010:362 to No Ending Ti||A||0.01506||0.014233||0.12821||0.11531||STS-2-HG||Random|
|00||BHZ||2012:137||2010:361 to No Ending Ti||A||0.016401||0.0087196||0.13855||0.12456||STS1VBBE3||Random|
|00||BH2||2012:137||2010:361 to No Ending Ti||A||0.023475||0.014004||0.14089||0.10495||STS1VBBE3||Random|
|00||BH1||2012:137||2010:361 to No Ending Ti||A||0.016707||0.0089101||0.13127||0.11205||STS1VBBE3||Random|
Current IssuesLNZ Episensor component is noisy.
2010-04-22Upgraded to Q330 digitizer.