Demo of a Huddle Test

 

A huddle test refers to a test where you huddle all seismic sensors at a single location and record data simultaneously for the purpose of confirming the agreement of the instrumental properties of all recording systems. In a huddle test, you can use exactly the same analysis method that is described in the demo of array data analysis, so please read that page first if you are using BIDO for the first time. You can conduct analysis following exactly the same procedure as in array analysis if only you assign identical locations to all seismic sensors in the seismfile.

 

For example, please download the demo data meant for huddle data analysis, decompress it beneath the BIDO 2.0 folder, and analyze it following the same procedure that you would use to analyze array data. The demo data have been made available by courtesy of Dr Tatsuya Noguchi at Tottori University. They were obtained by six vertical motion sensors (HS-1 Geophones) of Oyo Geospace Corporation installed on a concrete laboratory floor on the premises of Tottori University (see photos), and were recorded by an es8 data recorder via SA16 amplifiers and a low-pass filter (cutoff frequency 30 Hz).

 

  

 

Let us move on to data analysis by typing

 

run.sh demo/HDL0001/param.sh [RETURN KEY].

 

Just like in array analysis, the analysis results are stored in a folder, named RESULT, that is generated beneath the data folder.

 

The graphic output of the huddle test includes:

 

- Power-spectral densities

 

 

- Magnitude-squared coherences

 

 

- Phase differences

 

 

- Noise-to-signal ratios

 

 

and

- Power-spectral densities of incoherent noise.

 

 

All graphic output is shown up to the maximum frequency with the frequency axis scaled logarithmically. The maximum frequency here refers to the smaller one between the value set by the parameter freqmax_ave in \script/\setpar.sh (50 Hz by default but modifiable on your own) and the Nyquist frequency. If you do not prefer logarithmic scaling, comment out the line containing the parameter autologscale_x in \script/\setpar.sh by appending # to the head of the line.

 

The legends for the magnitude-squared coherences and phase differences are denoted like Average (by No 1 .vs. 2: S01.d .vs. S02.d). This refers to the mean of coherences between record numbers 1 and 2, of their phase differences (positive when 2 is more advanced than 1 in phase), and of NS ratios and noise intensities calculated on their basis. Record number 1 refers to the data indicated at the top of the seismfile. The records are numbered 2, 3 and so forth in the descending order of indication in the seismfile from top to bottom. The letters "by No 1 .vs. 2" in the graph legends indicate that record numbers 1 and 2 are concerned. To make this point sure, these numbers are followed by data file names like "S01.d .vs. S02.d." Please refer to ave.info in the ave folder for a table of correspondence between the record numbers and file names. ST. D. means standard deviation. The above analysis results show that record number 3 (records of S03.d; blue) has distinctly low coherences and has large phase differences with respect to the other records.

 

Bendat and Piersol (1971) and Carter et al. (1973) are useful references for the estimation and physical meaning of magnitude-squared coherences. The NS ratios are the inverse of the SN ratios calculated by substituting the magnitude-squared coherences (coh2) into the equation

 

 

(Carter et al., 1973). The power-spectral densities of noise are calculated by multiplying the power-spectral densities of the records by the NS ratios.

 

These plot data are stored, as in the case of array analysis, in a folder named RESULT/ave. Please refer to a list (here) of the file names and descriptions of the plot data. There is a file named DIFINSTRES1_2e.d. This file name is short for Differences in instrumental response. It lays out the amplitude ratios and phase differences of record number 2 with respect to record number 1 in the format

 

Frequency F [Hz]   Amplitude ratio R [non-dimensional]   Phase difference P [deg]

 

for each frequency. This file, when renamed, can be used directly for the purpose of correcting for instrumental characteristics in array data analysis (see Demo of data preprocessing).

 

Bendat, J. S., and A. G. Piersol,  Random Data: Analysis and Measurement Procedures: John Wiley & Sons, 1971.

Carter, G. C., C. H. Knapp, and A. H. Nuttall, 1973, Estimation of the magnitude-squared coherence function via overlapped Fast Fourier Transform processing: IEEE Transactions on Audio Electroacoustics, AU-21, 337344.

 

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