The new tool box has came in! I have spent serious time organizing these tools and making it look pretty, so please take care of it! A few things I would like to note.
Hope you all like it!
We came in this morning and noted the IMC was grossly misaligned, with MC3 still damped but with >= 100 rms motion in all coil monitors (a lot but not enough to trip the WD)... Turning off the WFS didn't do much so it was obviously an issue with the recent f2A output filters, so we turned all off (though only MC3 had this excess motion). After this we aligned IMC, engaged the lock and turned WFS back on.
There was no elog about f2A beyond this test scheduled to run Friday, I guess the filters were meant to stay on long term?
WFS Whitening and Demod boards were scavenged. ' iLIGO WFS cards are in big plastic boxes placed on the north wall around Section Y5 or Y6 (not under the arm). The WFS head PCBs, empty WFS housing, WFS components, I/Q demod components are at SectionY10 under the arm tube. ' - Koji . I have taken pictures of the boards and will upload them to the DCC once I find a way to add a Serial Number . (I will upload this to the eLog as a HowTo) The next step is to search for at least 2 extender boards to troubleshoot these board and find if there are any issues. We may have replace some components and retune the boards. Attachment #1 is an example of the WFS Whitening Filter and Attachment #2 is and example of the the WFS Demod Board.
If you use the Camera DO NOT remove the strap. I have also purchased lens caps for the camera, so after usage PUT THE LENS CAP BACK ON.
Coming in this morning, I found ITMX Camera malfunctioning.
Electrical Shop came in today to replace the lightbulbs around 40m. I supervised the entire visit, inside and outside the lab area. I was sure to use the ladders which were already inside the lab area. Although, while I was crawling under the MC beam tube, I came up too quickly and bumped it. This may have caused MC to become misaligned. Anyways, Yehonathan and I are realigning now.
Here is the Yuta's Alignment Scheme from elog 17056 with these slight adjustments:
Current alignment scheme:
Current alignment scheme I figured out is the following.
- Check Y green. If it is transmitted at good spot on GTRY camera, Yarm is OK. If not, tweak ITMY/ETMY. alignment.
- Mis-align AS4, align TT1, TT2, LO1 to have BHDC_A_OUT of ~115 and BHDC_B_OUT of ~95.
- Align PR3, PR2 to maximize TRY_OUT to ~1.0
- Tweak ITMY/ETMY if the beam spot on them are not good.
- Align BS, ITMX to have good MICH fringe and TRX_OUT to ~1.0.
- Tweak ITMX/ETMX if the beam spot on them are not good.
- Misalign ETMY, ETMX, ITMY to have LO-ITMX fringe in BHD DCPDs. From Sitemap --> BHD --> Homodyne Phase Ctrl --> LO_PHASE --> Turn ON LO Phase Servo (This will lock LO and ITMX fringe) --> align AS beam with SR2 and AS4 differentially, with ratio of AS4/SR2=3.6 for YAW, with ratio of AS4/SR2= 4.5 for PITCH to have BHDC_A_OUT ~ 50.
- Restore ITMY alignment, and lock MICH.
The issue was the power supply.
I found that an old BNC cable for ITMXF video existed so I first tried swapping both ends of the cable, one on the ITMX viewport and the other one in the video MUX input in the rear. This didn't fix the issue.
I searched around in the CCD cabinet by XARM and found an identical analog camera so I swapped it and got the same image ...
I then searched for a AC/DC supply cable, but couldn't find one.
I bought the spare Full-Range Pirani Gauge a while ago and realized that I never logged this. The Pirani Gauges we are using is described below.
I purchased this gauge from Agilent through TechMart. The spare is located inside the Vac Equipment cabinet (The only brown cabinet.) along the X-Arm.
I attempted to align PMC Beam from a transmission of 0.72. I failed to do so on my own, but Paco arrived and helped me out. Transmission has gone from from 0.72 to ~0.73.
Electrical came by today to see the lights. The issue may be the switches, but they will come by tomorrow to solve the issue. A couple light bulbs were noticed to be out, but they no longer have incandescent lights. . . only LED. I figured this would be preffered because of the reduction on noise. I would prefer to go ahead and ask to change all the incandescent bulbs to LED bulbs. Are there any objections to this?
[Paco, Anchal, JC]
C1:PSL-PMC_PMCTRANSPD ~ 0.715 this morning, this was increased to ~0.730. There also seems to be an earthquake going on and the MC is flashing.
While changing out one of the N2 tanks today, one of the fitting stripped. This caused a major loss of pressure. I replaced one fitting then realized there was a second leak around the area of the gauge. Paco and I changed this and everything should be back up and running. Thhe interlocks may have been tripped within the last 2 hours.
I copied the netgpibdata folder onto rossa (under the directory ~/Agilent/), which contains all the necessary scripts and templates you'll need to remotely set up, run, and download the results of measurements taken on the AG4395A network analyzer. The computer will communicate with the network analyzer through the GPIB device (plugged into the back of the Agilent, and whose communication protocol is found in the AG4395A.py file in the directory ~/Agilent/netgpibdata/).
The parameter template file you'll be concerned with is TFAG4395Atemplate.yml (again, under ~/Agilent/netgpibdata/), which you can edit to fit your measurement needs. (The parameters you can change are all helpfully commented, so it's pretty straightforward to use! Note: this template file should remain in the same directory as AGmeasure, which is the executable python script you'll be using). Then, to actually set up, run, and download your measurement, you'll want to navigate to the ~/Agilent/netgpibdata/ directory, where you can run on the command line the following: python AGmeasure TFAG4395Atemplate.yml
The above command will run the measurement defined in your template file and then save a .txt file of your measured data points to the directory specified in your parameters. If you set up the template file such that the data is also plotted and saved after the measurement, a .pdf of the plot will be saved along with your .txt file.
Now if you want to just download the data currently on the instrument display, you can run: python AGmeasure -i 192.168.113.105 -a 10 --getdata
Those are the big points, but you can also run python AGmeasure --help to learn about all the other functions of AGmeasure (alternatively, you can read through the actual python script).
Happy remote measuring! :)
Since we are using Wiener filtering in our project, we studied the derivation of Wiener-Hopf equations. Whatever we understood we have written it as a pdf document which is attached below...
We fixed the anti-aliasing board in its aluminum black box, the box couldn't be covered entirely because of the outgoing wires of the BNC connectors, so we drilled additional holes on the top cover to slide it backwards by 1cm and then screw it.
We had to fix the AA board box in rack 1X7, but there wasn't enough space, so we tried to move the blue chassis (ligo electro-optical fanout chassis 1X7) up with the help of a jack. We removed the blue chassis' screws but we couldn't move it up because of a piece of metal screwed above the blue chassis, then we weren't able to screw the two bottom screws again anymore because it had slided a bit down. Thus, the blue chassis (LIGO ELECTRO-OPTICAL FANOUT CHASSIS 1X7) is still not fixed properly and is sitting on the jack.
To accommodate the AA board (along with the panel-mounted BNC connectors) in rack 1X7 we removed the sliding tray (which was above the CPU) and fixed it there. Now the sliding tray is under the drill press.
We laid the cable along the cable keeper from the BACARDI seismometer to the rack 1X6, the excess cable has been coiled under the X arm.
We plugged the cable to the seismometer and to the seismometer electronics box in rack 1X6. We also plugged the AC power cable from the box to an outlet in rack 1X7 (because the 1X6 outlets are full)
With the help of a function generator we tested the following labeled channels of AA board...
2, 3, 11, 12, 14, 15, 16, 18, 19, 20 and 24
that are the channels that can be viewed by the dataviewer, also the channel 10 can be viewed but it's labeld BAD so we cannot use it.
We leveled the seismometer and unlocked it, and saw his X,Y,Z velocity signals with an oscilloscope.
We have two STS-2 seismometer boxes... the blue box & the purple box. Initially we used the blue box for the STS-2 seismometer (named Bacardi by Jenne).
X = +10 V
Y = +11 V
Z = -0.1 V
Thus, X and Y axes showed abnormally high DC volt. It was also found out that in AC coupling mode of the oscilloscope... changes were observed in the signal received from Z axis when some seismic wave was generated near the Bacardi by jumping near it. No such changes were observed from signals received from X & Y axes.
X = +4.4 V
Y = +4.4 V
Z = +4.4 V
In Ac coupling mode of the oscilloscope... changes were observed in the signals from X, Y, Z axes when someone jumped near Bacardi.
The 'Bacardi' STS-2 seismometer was tested with the "purple" breakout box and it was found out that all the three axes gave a voltage of 11 V (as shown on the screen of the oscilloscope) before pressing the auto-zero button and after pressing it the voltage shown was 6 V. We tried again the blue box and it was working perfectly after pushing the auto zero button (the auto zero took a few seconds). The power of the purple box is still on, we will wait a few hours, to see if something changes.
I'm pretty sure that don't have any ADC's with this gain. It should be +/- 10V for 16 bits.
Jenne told us that the ADC was +/- 2V for 16 bits so our calibration is wrong. Since, the ADC is +/- 10V for 16 bits we need to change our calibration and now we can also use the purple STS breakout box.
New calibration for Guralp:
ADC: 216counts = 20V Hence, calibration of ADC is (215x0.1) counts/V.
Sensitivity = 800 V/ms-1
(215 x 0.1) counts/V x 800 V/ms-1 = 2621440 counts/ms-1 -----> 3.8147e-07 ms-1/count
Calibration = 3.8147e-07 ms-1/count
Using the above calibration we obtain the following plot:
When we compare this plot with the old plot (see here) we see that in our calibration, we have got a factor of 10 less than the old plot. We do not know the gain of the Guralp. If we assume this missing 10 factor to be the gain of Guralp then we can get the same calibration as the old plot. But is it correct to do so?
We turned off the power of the seismometers and moved the Guralp1 close to the STS. Both are now situated below the center of the mode cleaner vacuum tube.
We oriented the X axis of the STS & Guralp1 along the X axis of the interferometer. Then we turned on the power again, but the STS channels don't give any signal. We think this is, because we didn't push the auto zero button.
After pressing the auto-zero button (a lot of times) of the STS breakout box & aligning the bubble in the STS, we could finally get data from STS (Bacardi). So, now STS2 (Bacardi - Serial NR. 100151) is working!
Following is the coherence plot obtained when Guralp1 and STS2(Bacardi, Serial NR 100151) are placed very close to each other (but they aren't touching each other):
The seismometers were placed as shown in the picture below:
They are placed below the center of the mode cleaner vacuum tube.
Finally, we have found the correct calibration of Guralp and STS2 seismometers.
ADC: 216counts = 20V Hence, calibration of ADC is 3.2768e+03 counts/V.
Sensitivity of seismometer = 800 V/ms-1
Gain of the guralp breakout box (reference elog entry) = 20
Calibration = 3.2768e+03 counts/V x 800 V/ms-1 x 20 = 52428800 counts/ms-1 -----> 1.9073e-08 ms-1/count
Sensitivity = 1500 V/ms-1
Gain of the STS electronic breakout box = 10
Calibration = 3.2768e+03 counts/V x 1500 V/ms-1 x 10 = 49152000 counts/ms-1 -----> 2.0345e-08 ms-1/count
We moved the seismometer STS2(Bacardi, Serial NR 100151) as we told in this Elog Entry, so the distance between Guralp1 and STS2 is 31.1m. Following is the coherence plot for this case:
then we also moved the Guralp1 under the BS and plugged it with the Guralp2 cable (at 7:35pm PDT), so now the distance between the two seismometers is 38.5m. Following is the coherence plot for this case:
We did offline wiener filtering on 3rd August (Elog entry) using only Guralps' channels X and Y.
Here we report the Power spectrum of the 3 seismometers (Guralp1, Guralp2, STS1) during that time.
and also the coherence between the data from different channels of the 3 seismometers.
We see that the STS is less correlated with the two Guralps. We think it is due to the wrong alignment of the STS with the interferometer's axes.
We are going to align the STS and move the seismometers closer to the stacks of the X arm.
We used a function generator, an oscilloscope and the Data Viewer to check the gain of the new AA board (used for the seismometers). Putting a sine wave of 0.3V (using a function generator) to the AA board, we could see about 500 counts in the Data Viewer. The calibration of the ADC is 214 counts/volt, so the AA board gives to the ADC an output of 0.03V. This proves that the AA board has a gain of 0.1. Guralp1 and STS1 (Bacardi), both have a gain of 10 now, that balance the AAboard gain of 0.1. If we consider the gain of AA board in our calibrated power spectrum plot of seismic signals from Guralp1 and STS1 (Bacardi), we get the following plot:
ADC: 216counts = 4V Hence, calibration of ADC is 214counts/V.
Gain of the AA board, g1 = 0.1
214 counts/V x 800 V/ms-1 = 13107200 counts/ms-1 -----> 7.6294e-08 ms-1/count
Gain, g2 = 10
Calibration = 7.6294e-08 ms-1/count x g1 x g2 = 7.6294e-08 ms-1/count
214 counts/V x 1500 V/ms-1 = 24576000 counts/ms-1 -----> 4.069e-08 ms-1/count
Gain of the STS electronic breakout box, g3 = 10
Calibration = 4.069e-08 ms-1/count x g1 x g3 = 4.069e-08 ms-1/count
Following is the power spectrum plot (with corrected calibration [see here]) of seismometers Guralp1 and STS2(Bacardi, Serial NR 100151):
The seismometers are placed approximately below the center of the mode cleaner vacuum tube.
We moved the STS2(Bacardi, Serial NR 100151) to his new location and laid his cable from rack 1X7 to ETMX. The seismometer was below the mode cleaner vacuum tube before.
Now, (since 6:05pm PDT) its placed near the ETMX.
I started on the 16th with a very intense lab tour & was fed with a large amount of data (I can't guarantee that I remember everything....)
Then... did some (not much) reading on filters since I'm dealing with seismic noise cancellation this summer with Jenne at the 40m lab.
I'll be using the Streckeisen STS-2 seismometers & I need to use the anti aliasing filter board that has the 4 pin lemo connectors with the seismometers & its boxes that require BNC connectors. I spent most of the time trying to solder the wires properly into the connectors. I was very slow in this as this is the first time I'm soldering anything.... & till now I've soldered 59 wires in the BNC connectors....
This is the new hot air station for the 40m lab.........
The AA board shown in attachment 1 will be used in the seismometer hardware setup. A cartoon of this setup is shown in attachment 2.
BNC connectors are required for the seismometer breakout boxes. So the four-pin LEMO connectors present in the AA board were removed and panel mount BNC connectors were soldered to it. Red and blue colored wires were used to connect the BNC connectors to the board. Red wire connects the center of the BNC connector to a point on the board and that connection leads to the third leg (+IN) of the IC U### and the blue wire connects the shield of the BNC connector to the second leg (-IN) of the IC U###.
All the connections (including BNC to the AA board and in the AA board to all the filters) were tested using a multimeter by the beeping method and it was found that channel 10 (marked as C10) had a wrong connection from the point where the red wire (+ve) was connected to the third leg (+IN) of IC U91 and channel 32 (marked as C32) had opposite connections meaning the blue wire is connected to the third leg (+IN) of IC U311 and red wire is connected to the second leg (-IN) of IC U311.
Steve ordered about two weeks ago a roll of 0.5 mm thick copper foil to be used for the inside of the seismometer cans. The foil was then waterjet cut by someone in Burbank to the right dimensions (in two pieces, a side and a bottom for each of the three cans).
Today, we glued the copper foil (sides only) inside the three seismometer cans. We used HYSOL EE4215/HD3561(Data Sheet) as our glue. It is a "high impact, low viscocity, room temperature cure casting" that offers "improved thermal conductivity and increased resistance to heat and thermal shock." According to Steve, this is used in electronic boards to glue components when you want it to be thermal conductive.
We are going to finish this off tomorrow by gluing the bottom foil to the cans. The step after this involves soldering the side to the bottow and where the side connects. We have realized that the thermal conductivity of the solder that we are using is only ~50. This is 8 times smaller than that of copper and wil probably limit how good a temperature gradient we will have.
Some action shots,
The wasp terminator came in today. He obliterated the known wasp nest.
We discovered a second wasp nest, right next to the previous one...
Jessica wasn't too happy the wasps weren't gone!
Today, I installed the Wilcoxon accelerometers in the table near the end of the mode cleaner. I only set three of them up instead of all six. They were set up just as Rana suggeted we should have them properly set up, i.e. cables being tighten up, and a box on top to prevent any airflow introducing any disturbances. We are planning on running the huddle test on these guys once the upgrade? to the interferometer is done.
The cables were tightly clamped to the table as shown below, I used a thick piece of shock absorbing rubber to do this.
A small piece of thin rubber was used to hold each of the accelerometers tightly to the table in order not to damage them.
We had to borrow Megan's and Kate's piece of black foam in order to seal one of the sides properly, as the cable had to come out through somewhere. We didn't want to mess with drilling any holes into the box!
There was a small crack even after using the foam. I sealed it up with duck tape.
The box isn't perfect, so there were multiple cracks along the bottom and top of it that could potentially allow for air to flow to the inside. Eric suggested that we should be super careful this time and do it right, so every crack was sealed up with ducktape.
Finally, we needed something heavy to be placed on top of the box to hold everything well. We used Rana's baby to accomplish this goal.
Just kidding! Rana's baby is too delicate for our purposes. A layman box of heavy cables was used instead.
Updated: On Thursday/Friday (sorry for late elog) I was messing with Eric's Wilcoxon 731A accelerometer huddle test data that was taken without the box and cables being adjusted properly. Anyways, I performed the three cornered hat analysis as he had done but I also performed a six cornered hat method as well instead of permuting around in pairs of three accelerometers. The following plots of the ASD's show the results,
It is interesting to note the improvement at low frequencies when six accelerometers are used instead of six while at higher frequencies we can clearly see how the results are worst than the three hat results.
I decided to take a mean of all six accelerometers measured ground signal as well as that for their computed selfnoises, this is plotted below,
Notice the obvious improvement along the entire frequency band of the measurements when all accelerometers are used in the data analysis.
I also performed some Wiener filtering of this data. There was an obvious improvement in the results,
The mean of the signals is also plotted below, just as I did with the cornered hat methods,
I also compared the mean self noise of the accelerometers against the manufacturers calculated selfnoise that Rana put up on Github. Both methods are compared against what the manufacturer claims,
As expected the measured noise curves of the Wilcoxon is not as good as what the manufactures stated. This should improve once we redo the huddle test with a better experimental setup. We have some pretty interesting results with the six cornered hat method at around 5 Hz, it is surprisingly accurate given how rough the calculations seemed to be.
I have attached my code for reference: code_accel.zipselfnoise_allsix.png
SEE attachments for better plots of the six accelerometers...
Over the past few days, I've been thinking about how to workout the details conerning Rana's request about a 'map' of the vicinity of the 40m interferometer. This map will take the positions of N randomly placed seismic sensors as well as the signals measured by each one of them and the calculated cross correlations between the sensors and between the sensors and the test mass of interest to give out a displacement vector with new sensor positions that are close to optimum for better seismic (and Newtonian) noise cancellation.
Now, I believe that much of the mathematical details have been already work out by Jenne in her thesis. She explains that the quantity of interest that we wish to minimize in order to find an optimal array is the following,
where is the cross-correlation vector between the seismic detectors and the seismic (or Newtonian) noise, is the cross-correlation matrix between the sensors and is the seismic (or Newtonian) noise variance.
I looked at the paper that Jenne cited from which she obtained the above quantity and noted that it is a bit different as it contains an extra term inside the square root, it is given by
where the new term, is the matrix describing the self noise of the sensors. I think Jenne set this term to zero since we can always perform a huddle test on our detectors and know the self noise, thus effectively subtracting it from the signals of interest that we use to calculate the other cross correlation quantities.
Anyways, the quantity above is a function of the positions of the sensors. In order to apply it to our situation, I'm planning on:
1) Performing the huddle tests on our sensors, redoing it for the accelerometers and then the seismometers (once the data aquisition system is working... )
2) Randomly (well not randomly, there are some assumptions we can make as to what might work best in terms of sensor placement) place the sensors around the interferometer. I'm planning on using all six Wilcoxon 731A accelerometers, the two Guralps and the STS seismometer (any more?).
3) Measure the ground signals and use wiener filtering in order to cancel out their self noises.
4) From the measured signals and their present positions we should be able to figure out where to move the sensors in order to optimize subtraction.
i have also been messing around with Jenne's code on seismic field simulations with the hopes of simulating a version of the seismic field around the 40m in order to understand the NN of the site a little better... maybe. While the data aquisition gets back to a working state, I'm planning on using my simulated NN curve as a way to play around with sensor optimization before its done experimentally.
i have as well been thinking and learning a little bit about source characterization through machine learning methods, specially using neural networks as Masha did back in her SURF project on 2012. I have also been looking at Support vector machines. The reasons why I have been looking at machine learning algorithms is because of the nature of the everchanging seismic field around the interferometer. Suppose we find a pretty good sensor array that we like. How do we make sure that this array is any good at some time t after it has been found? If the array mostly deals with the usual seismic background (quiet) of the site of interest, we could incorporate machine learning techniques in order to mitigate any of the more random disturbances that happen around the sites, like delivery trucks, earthquakes, etc.
On Thursday, new huddle test data for the Wilcoxon 731A was aquired by Eric.
The difference between this new data and the previous data, is:
1) We used three accelerometers instead of six this time around.
2) We used a foam box, and clamped cables on the experimental set up as shown in the previous elog, http://nodus.ligo.caltech.edu:8080/40m/11389
I have analyzed the new data. Here I present my results.
The following plot shows the ASD's for the three accelerometers raw outputs as well as their error signals computed using the three cornered hat method,
As before, I computed the mean for the output signals of the accelerometers above as well as their mean self noise to get the following plot
Now, below I compare the new results with the results that I got from the old data,
Did the enclosure and cable clamping do much? Not really, according to the computed three hat results. Also, notice how much better, even if its a small improvement, we get from using six accelerometers and calculating their self noise by the six cornered hat method.
Now, I moved on to analyzing the same data with Wiener Filtering.
Here are again, the raw outputs, and the self noises of each individual accelerometer calculated using Wiener filtering,
The accelerometer in the Y direction is show a kind of funky signal at low frequncies. Why? Anyways, I calculated the mean of the above signals as I did for the three cornered hat method above to get the following, I also show the means of the signals computed with the old data using wiener filtering,
Is the enclosure really doing much? The Wiener filter that I applied to the huddle test old data gave me a much better, by an order of magnitude better self noise curve. Keep in mind that this was using SIX accelerometers, not THREE as we did this time. I want to REDO the huddle test for the WIlcoxon accelerometers using SIX accelerometers with the improved experimental setup to see what I get.
Finally, I compare the computed self noises above with what the manufacturer gives,
As I expected, the self noise using six accelerometers and Wiener filtering is the best I could work out. The three cornered hat method works out pretty well from 1 to 10 Hz, but the noise is just too much anywhere higher than 10 Hz. The enclosed, clamped, 3 accelerometer wiener filter result is an order of magnitude worse than the six accelerometer wiener filtered result, and two orders of magnitude worse than the three cornered hat method in the 1 to 10 Hz frequency band.
As I stated, I think we must performed the huddle test with SIX accelerometers and see what kind of results we get.
We took data for the mode cleaner a while ago, June 30th I believe. This data contained signals from the six accelerometers and the three seismometers. In here I have only focused on the seimometer signals as witnesses in order to construct Wiener filters for each of the three seismometer signals (x,y,z) and for the combined seismometers signal. The following plot showing the ASD's shows the results,
Wiener filtering works beautifully for the seismometers. Note that subtraction is best when we use all three seismometers as the witnesses in the Wiener filter calculation, as can be clearly seen in the first plot above.
Now, I used vectfit to conver the Wiener FIR filters for each seismometer to their IIR versions. The following are the bode plots for the IIR filters,
For the x-direction seismometer,
For the y-direction seismometer
And for the z-direction seismometer,
The IIR filters were computed using 5 zeros and 5 poles using vectfit. That was the maximum number of poles that I could use wihtout running into trouble with matrices being almost singular in Matlab. I still need to figure out how to deal with this issue in more detail as fitting the y-seismometer was a bit problematic. I think having a greater number of poles will make the fitting a bit easier.
(updateAfter Eric gave me feedback on my previous elog post, I went back and fixed some of the silly stuff I stated.
First of all, I have come to realized that it makes zero sense to plot the ASD's of the mode cleaner against the seismometer noise. These measurements are not only quite different, but elementary, they posess different units. I have focused my attention to the MCL being Wiener filtered with the three siesmometer signals.
One of the major improvements that I make in the following analysis is,
1) Prefiltering; a band pass filter from 1 to 5 Hz, in order to emphasize subtraction of the bump shown in the figure below.
2) I have used vectfit exclusively in the 1 to ~5 Hz range, in order to model the FIR filter properly, as in, the kind of subtraction that we care about. Limiting myself to the 1 - 5 Hz range has allowed me to play freeley with the number of poles, hence being able to fit the FIIR filter properly with an IIR rational transfer function properly,
The resulting ASD's are shown below, in blue we show the raw MCL output, in blac the Wiener filter (FIR) result, and finally in black, the resultant data being filtered with the calculated IIR Wiener filter.
Now, in the following plots I show the IIR Wiener filters for each of the three seismometers,
For the Y seismometer,
and for the Z seismometer,
The matlab code for this work is attached: code.zip
I generated the following plots from the two sets of huddle test data we have for the accelerometers.
Old data: 6 accelerometers, no cables clamped, no box, 55 mins worth of data.
New data: 3 accelerometers, cables clamped, foam box put on placed and completely sealed, 20 mins worth of data.
I made sure to use the same Impuse response time (6 sec) and sampling frequency (256 Hz), as well as every other parameter for the calculations.
Top left: The resultant self noise curve using the new data, there is definitely and improvement in the 0.5-2 Hz band.
Top right: Resultant self noise using the old data, for the first set of three accelerometers.
Bottom left: Old data result for the remaining three accelerometers.
Bottom right: Old data result, using all six accelerometers as witnesses instead.
In the last post concerning the self noise of the accelerometers, I mentioned the differences between the two data sets I was playing with. In order to give a more concrete analysis of the accelerometers self noise, we came to the conclusion that data taking time should be the same.
The plots below show the analysis for the following two datasets:
Old Data: 6 accelerometers, no cables clamped, no box, 55 mins worth of data.
Newer data: 3 accelerometers, cables clamped, foam box put on placed and completely sealed, 57.66 mins worth of data, (we had 20 mins of data in the previous data set).
Filter parameters were kept the same in all calculations, the only change that was added to the analysis was the detrending of the signals using the detrend function on Matlab, this improved the results as the plots show. I also plotted the error bars for the Wiener filtered result for reference as well as the manufactures claimed self noise.
After detrending the data and taking a longer dataset we can see the improvement brought upon by the foam box in the low frequency band of 0.5 - 10 Hz, as shown in the bottom left plot. There is a lot of noise that needs to be cancelled out from 10 Hz and on, which brings to our attention the plot on the bottom right corner. This plot uses the old data but uses all six accelerometers as witnesses, it also improved overall after having detrended the data, but what is peculiar about this plot is the fact that it manages to mitigate the higher frequency 10 - ~100 Hz band noise.
I have moved the MC1 accelerators and cable to the huddle test set up, in order to see how a six witness huddle test with the improved set up will do.
Here is a picture of the accelerometer set up,
Our motivation for doing this is to see if more witness signals used in the Wiener filter really does indeed improve subtraction, as it was seen from previous huddle results, specially in the region above 10 Hz.
I've have been talking a little bit with Steve about the seismometer enclosures.
We want to improve on the current stainless steel cans that cover the two Guralps at the end of the arms. In order to do this, we want to cover the interior of the cans with copper foil to improve the thermal conductivity of the enclosure to better control the temperature inside it. Ideally, we would want to copper plate the cans, but cost and difficulty has been an issue.
I have done some rough calculations and it seems that we need a copper layer of thickness being about a third that of the stainless steel can. This happens to be around 0.5-0.6 mm since we have 16 gauge (~1.6 mm) stainless steel cans.
After wrapping the cans interior with copper, we will insulate them with foam in order to improve its thermal inertia. We want to probably use the same foam that Megan has been using for her seismometer enclosure. I have yet to think about a heater, but something similar to Megans resistor thing would work only smaller. I would be placed inside the can, right on the center of its bottom in order to ditribute heat evenly.
I downloaded new accelerometer huddle test data from last night and analyzed it. This new data set is ~55 mins and uses the same Wiener filter parameters as previous huddle test analysis, the main difference being six accelerometers used in the Wiener filter and the improved experimental set up.
After computing the ASD for the self noise for each of the six accelerometers, (being witnessed by the remaining five), we get,
Now computing the mean of the above signals and the corresponding error bars gives the following result,
Comparing to prevoius huddle tests, I can note two trends on the Wiener subtraction:
1) When using six accelerometers, the subtraction above ~8 Hz drastically improves.
2) When using three accelerometers, there is better cancellation in the 1-5 Hz region, see http://nodus.ligo.caltech.edu:8080/40m/11442. This might have to do with how much more closer the accelerometers are to each other?
Jessica and I took 45 mins (GPS times from 1122099200 to 1122101950) worth of data from the following channels:
C1:IOO-MC_L_DQ (mode cleaner)
C1:LSC-XARM_IN1_DQ (X arm length)
C1:LSC-YARM_IN1_DQ (Y arm length)
and for the STS, GUR1, and GUR2 seismometer signals.
The PSD for MCL and the arm length signals is shown below,
I looked at the coherence between the arm length and each of the three seismometers, plot overload incoming below,
For the coherence between STS and XARM and YARM,
Finally for GUR2,
A few remarks:
1) From the coherence plots, we can see that the arm length signals are coherent with the seismometer signals the most from 0.5 - 50 Hz. This is most evident in the coherence with STS. I think subtraction will be most useful in this range. This agrees with what we see in the PSD of the arm length signals, the magnitude of the PSD starts increasing from 1 Hz and reaches a maximum at about 30 Hz. This is indicative of which frequencies most of the noise is present.
2) Eric did not remember which of GUR1 and GUR2 corresponded to the ends of XARM and YARM. So, I went to the end of XARM, and jumped for a couple seconds to disturb whatever Gurald was in there. Using dataviewer I determined it was GUR1. Anyways, my point is, why is GUR1 less coherent with both arms and not just XARM? Since it is at the end of XARM, I was expecting GUR1 to be more coherent with XARM. Is it because, though different arms, the PSD's of both arms are roughly the same?
3) Similarly, GUR2 shows about the same levels of coherence for both arms, but it is more coherent. Is GUR2 noisier because of its location?
We are done taking accelerator huddle test data. So I moved back all six accelerometers and cables to MC1 and MC2. I also relabel each of the accelerometers properly since the labels on them were confusing.