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Entry  Wed Jun 3 17:04:08 2015, ericq, Update, PEM, Wilcoxon Accelerometer Huddle Test AccHuddle.jpg
    Reply  Wed Jun 10 02:50:39 2015, ericq, Update, PEM, Wilcoxon Accelerometer Huddle Test hats2Acc.png3hatcode.zip
       Reply  Mon Jun 15 16:55:39 2015, ericq, Update, PEM, Accelerometers installed MC2.jpgMC1.jpgmc2accspectra.png
          Reply  Wed Jun 17 15:31:50 2015, ericq, Update, PEM, Accelerometers fully installed IMCcoherence_Jun172015.xml.zipIMCcoherence.png
       Reply  Sun Jul 5 18:14:13 2015, Ignacio, Update, PEM, Wilcoxon Accelerometer Huddle Test 8x
    Reply  Sun Jun 21 13:21:03 2015, rana, Update, PEM, Wilcoxon Accelerometer Huddle Test 
Message ID: 11350     Entry time: Wed Jun 10 02:50:39 2015     In reply to: 11345     Reply to this: 11359   11391
Author: ericq 
Type: Update 
Category: PEM 
Subject: Wilcoxon Accelerometer Huddle Test 

Here are some results for the 3-corner hat subtraction for the six accelerometers, from ~1 hour of data that didn't look to have any sharp features/glitches from human activity in the lab. 

I used the python uncertainties package to try and get an estimate of the uncertainty in the subtracted noise floor, by taking into account every possible possible combination of 3 sensors and the fluctuations in the spectrograms of the subtracted signals. I've attached the python code if anyone is interested in the implementation. 

I pulled out the accelerometer data sheets to read their slightly varying V/g calibration (which differs on the order of a few percent from unit to unit). This improved the subtraction factor from ~20 to over 100 at some frequencies. I've edited the filter modules such that the OUT_DQ channels are already calibrated into m/s^2.

Attachment 1: hats2Acc.png  299 kB  Uploaded Wed Jun 10 04:26:10 2015  | Hide | Hide all
Attachment 2: 3hatcode.zip  2 kB  Uploaded Wed Jun 10 04:27:54 2015
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