I did a simulation of linear quadratic gaussian (LQG) controller applied to local damping. The cost function was frequency shaped to have a peak at 1 Hz. This technique prevents the controller from adding sensor noise at high and very low frequencies.

Noise was simulated to have 1/f spectrum (seismic) multiplied by stack with a resonance at 4 Hz with Q=5.

 I tweaked the alignment of ITMX and ETMX a teeny bit to get the TEM00 flashes back (the work in the previous elog was pre-dinner, so it had been a few hours), then took a screenshot of the error signal and refl dc power on the photodiode for the green xend setup.

The error signal is certainly noisy, although I think when Jamie and I were looking at it earlier this evening, the SNR was a little better.

I need to look at the modulation depth, to see if it's correct, ... maybe lock the Xarm on IR and scan the green laser PZT to check the sideband heights.

I should also check to make sure that the PD is powered, and the gain is high enough (currently the PD gain is set to 20dB).  Earlier today, when I set the gain to 30dB, Jamie said that it was saturating, so I put it back down to the 20dB where we found it.

Still no lock of the green though :(

Edit: realized I was bad and didn't label the traces on the plot:  green is refl dc power, blue is demodulated error signal.

[Koji Rana]

The FSS Slow DC servo was turned off.

As MCL stabilizes the MC_F (Fast PZT), we no longer need to use the laser temp to do so.

In other word, if you like to turn off the MCL servo for some reason, we need to turn it on in order to keep the MC locked.

[Koji Rana]

MC Autolocker was updated. (i.e. mcup and mcdown were updated)

mcup:

• Turn on the MCL input and output switches
• Change the MCL gain from 0 to -300 with nominal ramp time of 5sec
• Turn on FM2, FM5, MF7 after a sleep of 5sec. Note: FM1 FM8 FM9 are always on.
• Set the offset of 42 counts
• Turn on the offset

# Turn on MCL servo loop
echo mcup: Turning on MCL servo loop...
date
ezcaswitch C1:SUS-MC2_MCL INPUT OUTPUT ON
ezcawrite C1:SUS-MC2_MCL_GAIN -300
sleep 5
ezcaswitch C1:SUS-MC2_MCL FM2 FM5 FM7 ON
# Offset to take off the ADC offset of MC_F
ezcawrite C1:SUS-MC2_MCL_OFFSET 42
ezcaswitch C1:SUS-MC2_MCL OFFSET ON


This offset of 42 count is applied in order to compensate the ADC offset of MC_F channel.
The MCL servo squishes the MC_F signal. i.e. The DC component of MC_F goes to zero.
However, if the ADC of MC_F has an offset, the actual analog MC_F signal, which is fed to FSS BOX,
still keep some offset. This analog offset causes deviation from the operating point of the FSS (i.e. 5V).

mcdown:

• Basically the revese process of mcup.
• This script keeps FM1 FM8 FM9 turned on.

# Turn off MCL servo loop
echo mcdown: Turning off MCL servo loop...
date
ezcawrite C1:SUS-MC2_MCL_GAIN 0
ezcaswitch C1:SUS-MC2_MCL INPUT OUTPUT OFFSET FMALL OFF FM1 FM8 FM9 ON
# Remove Offset to take off the ADC offset of MC_F
ezcawrite C1:SUS-MC2_MCL_OFFSET 0

I turned on some filters and gain in the SUS-MC2_MCL filter bank tonight so as suppress the seismic noise influence on MC_F. This may help the MC stay in lock in the daytime.

Koji updated the mcdown and mcup scripts to turn the MCL path on and off and to engage the Boost filters at the right time.

The attached PNG shows the MCL screen with the filters all ON. In this state the crossover frequency is ~45 Hz. MC_F at low frequencies is reduced by more than 10x.

I also think that this may help the X-Arm lock. The number of fringes per second should be 2-3x less.

The MC1 accelerometer cube (3 accelerometers arranged in x,y,z) is under the PSL table, as I found it at the beginning of the summer.

The MC2 accelerometer cube is on the table where I worked on the STACIS, right when you walk into the lab from the main entrance. Their cables are dangling near the end of the mode cleaner, so the accelerometers are ready to be placed there if wanted.

All accelerometers are also plugged into their ADC channels.

[Jenne, Jamie]

We took a look at the Xend green, and we weren't able to make it lock.  We improved the alignment a little bit, and when we looked at the error signal, it looked nice and PDH-y, but for whatever reason, the cavity won't catch lock.

While aligning the green to the arm, Jamie noticed that the reflection from the intracavity power (not the prompt reflection) was not overlapping with the input beam or prompt reflection.  This means that the cavity axis and the input green beam were not co-linear.  I adjusted the BS and ITMX to get the IR transmitted beam (which had been near clipping on the top edge of the first (2 inch) optic it sees out of the vacuum) back near the input green beam spot on the combining beam splitter.  Then we continued tweaking the green alignment until we saw nice TEM00 flashes in the cavity.  The SNR of the error signal increased significantly after this work, since the cavity buildup was much higher.  But alas, still no lock. 

The huge kick observed in the MC sus sensors seem to last for ~10usec; almost matching the observed ringdown decay time. We should find a way to record the ringdown and the MC sus sensor data simultaneously to know when the mirrors are exactly moving during the measurement process. It could also be that the moving mirrors were responsible for the ripples observed later during the ringdown as well.

* How fast do the WFS respond to the frequency switching (time taken by WFS to turn off)? I think this information will help in narrowing down the many possible explanations to a few.

I cleaned up my directory (/users/masha) today. A lot of the files are just code that I experimented with, but the important files for training the classification neural network are in "neural_network_classification". The "EarthquakeData" subdirectory contains my entire dataset. Files of the form "GenerateRNNInput" are used to create input vector sets to the network, while files of the "*NeuralNetworkClassification* actually run the code that generates the neural network vectors for the classification code block in the c1pem model.

Also, the folder "feed_c", which can also be found in Den's directory, contains the neural network controller code we played around with.

 I found this entry in the old 40m ilog which describes the STACIS performance. It shows that even though the STACIS is bad for the differential arm motion below 3 Hz. It has quite a big and positive effect at 10-30 Hz. The OSEMs show a bigger effect than what the single arm does. I think this is because the single arm is limited by the MC frequency noise above 10 Hz.

We should figure out how to turn on the STACIS but set the lower UGF to be ~5 Hz.

 It is HIGHLY unlikely that the IMC mirrors are having any effect on the ringdown. The ringdowns take ~20 usec to happen. The mirrors are 0.25 kg and you can calculate that its very hard to get enough force to move them any appreciable distance in that time.

The ringdown measurements are in progress. But it seems that the MC mirrors are getting kicked everytime the cavity is unlocked by either changing the frequency at the MC servo or by shutting down the input to the MC. This means what we've been observing is not the ringdown of the IMC alone. Attached are MC sus sensor data and the observed ringdown on the oscilloscope.  I think we need to find a way to unlock the cavity without the mirrors getting kicked....in which case we should think about including an AOM or using a fast shutter before the IMC.

P.S. The origin of the ripples at the end of the ringdown still are of unknown origin. As of now, I don't think it is because of the mirrors moving but something else that should figured out.

 Bob is back. Cleaning and baking all our posts and clamps. They will be ready for use Tuesday next week. Therefore beam dumps will be available for installation.

Atm1,  I'm not sure about the seismic data.   Baja earthquake magnitude 3.0 at  yesterday morning.Seismometers do not see them !

Atm2,  No posted seismic activity.  Someone is jump walking in the lab? Why are there time delays between the suspensions?

Jenne and I did adaptive filtering of MC_L and measured how X and Y ARM control signals change compared to non-filtered MC_L. We did the test during 1.5 Hz seismic noise activity and adaptive filter was able to subtract it. However, it adds noise at high frequencies, It is not seen in MC_L but it is present in the ARMs control signals.

I'll investigate this problem. May be we need to reduce adaptation gain. In this experiment it was 0.1 and adaptive filter convergence time was equal to 1-2 mins.

It seems as though there is something funny going on around ~1.5 Hz, starting a little over an hour ago.

We see it in the BLRMS channels, the raw seismometer time series, as well as in various suspensions and LSC control signals.  It's also pretty easy to see on the camera views of all the spots (MC, arms, transmissions....AS is a little harder to tell since it's flashing, but it's there too).

The plots I'm attaching are only for ~10min after the jump happened, but there has been no change in the BLRMS since it started.  Usually, we'd see an earthquake in all the channels, and even big ones ring down after a little while.  This is concentrated at a pretty narrow frequency (some of Den's plots for later have this peak), and it's not ringing down, so it's not clear what is going on.

Here is a whole pile of plots.  Recall that the T-240 is plugged into the "STS_3" channels, and we don't have BLRMS for it, so you can look at the time series, but not any frequency specific stuff.

Last week, Rana changed the integrators in the arm LSC servo filters to be double integrators with complex poles. 

Yesterday, I found that using the "timeout" feature of Foton (at filter ON/OFF request, waits for zero crossing, or T seconds, whichever comes first) is useful for turning on the integrators, but bad for turning them off.  When we're locked, the error signal is oscillating around zero, so there is often a zero crossing.  When we lose lock, we want to turn off the filter immediately.  But, as soon as lock is lost, the input signal gets large, and doesn't often cross zero, so the filter waits 8 seconds until actually turning off.  If the arm flashes any time during that 8 sec, we send a big kick to the optics.

An alternative option could be ramping the filter on.  However, since the double integrator has -180deg phase at low frequencies (until the poles at ~5Hz), the transition between no filter (0deg phase) and integrator on could be problematic.  I simulated this, and find that for the very beginning of the ramping process, we would have a problem. 

The filter is defined as:  NoFilter * (1 - R) + Integrator * (R), so for R=0, the integrator is off, and for R=1, the integrator is fully on.  R can be any value [0,1]. 

The first figure is the time series (1 second, 16kHz), ramp goes from 0->1 or 1->0 in 1 second:

The second figure is bode plots for selected values of R:

As R gets smaller and smaller, the notch goes to lower frequency, and becomes higher Q.  So perhaps ramping is not a good answer here. 

What if we go for single or triple integrator, to get rid of the (+1) + (-1) problem?

We are discussing venting first thing next week, with the goal of
diagnosing what's going on in the PRC.

Reminder of the overall vent plan:

https://wiki-40m.ligo.caltech.edu/vent

Since we won't be prepared for tip-tilt installation (item 2), we should
focus most of the effort on diagnosing what's going on in the PRC.  Of
the other planned activities:

(1) dichroic mirror replacement for PR3 and SR3

  Given that we'll be working on the PRC, we might consider going ahead
  with this replacement, especially if the folding mirror becomes
  suspect for whatever reason.  In any case we should have the new
  mirrors ready to install, which means we should get the phase map
  measurements asap.

(3) black glass beam dumps:

  Install as time and manpower permits.  We need to make sure all needed
  components are baked and ready to install.

(4) OSEM mount screws:

  Delay until next vent.

(5) new periscope plate:

  Delay until next vent.

(6) cavity scattering measurement setup

  Delay until next vent.

Reinforced concrete grout plate for existing carbon steel stands at the ends.

While meditating on other things, I have noticed / found the following today:

YARM ASS works okay.  Yesterday I measured the sensing matrix for the ASS for both arms (although I forgot to copy one of the matrix elements to my text file for Xarm - needs remeasuring).  I put the Yarm matrix in (after appropriate inversion, only non-zero pitch-to-pitch, yaw-to-yaw elements).  I turned on the Yarm ASS, and  the yaw converged pretty quickly (couple of minutes), with gains of -1 in the servos, overall gain of anywhere between 0.005 and 0.010.  The pitch took much longer, and I had to 'pause' several times by turning off the overall gain for the yarm ass when the MC lost lock (which has happened several times tonight - unknown cause).  Eventually, the pitch settled out, and quit changing, but the lockin outputs weren't zero, even though the error signal for the servos were almost zero (gains for the pitch servos were -0.5, overall gain ~0.005 was better than 0.01 - higher gain caused oscillations in the lockin outputs).  I think this means that I need to remeasure the yarm pitch ass matrix.  It's still much, much faster to just turn on the dithers, watch the striptool of the lockin outputs, and align the cavity by hand.

I think the ETMX Trans camera view is clipped a little bit.  I went down there, and it doesn't seem to be on the last optic before the camera, and moving the spot on the camera doesn't change the shape of the image, so I don't think it's on the camera.  We should look into this, since it's either clipping on the BS that separates some camera beam from the TRX beam, or TRX is getting a clipped beam too.  If the clipping is any earlier in the Trans path, the Trans QPD could also have some clipping.  This requires investigation.  The xarm trigger needs to be reset/disabled so we don't lose lock every time we block the TRX beam (as was happening to me).

XARM really doesn't like to relock unless the POX whitening is turned off.  Good flashes, doesn't really catch (10+ min waiting (while working on Yarm stuff) ).  After turning off the whitening, it catches almost immediately. Even though it's on the to-do list to rethink the tuning of our whitening, we should probably implement the whitening triggering now anyway.  It'll make things easier.

The double integrator that Rana implemented in the X and Y arm servo filters last week take 8 seconds to turn off (due to Foton settings), so even though they are triggered to turn off immediately upon lockloss, they sit around and integrate for 8 seconds, so have huge signals.  If the cavity flashes and the locking trigger engages during that 8 seconds, we send a huge kick to the ETMs.  I'm modeling the response of the filters to an impulse and noise, particularly in the case of ramping on the double integrators.  The problem is that a flat filter has 0deg phase, but the double integrator has 180deg phase at low frequencies, so there's some weird sign flipping that can happen as we ramp - this is part of what I'm modeling.

MC is losing lock unusually often tonight.  Everything on the servo board screen looks normal (which is good since that's all set by the autolocker).  I just disabled the test exc in, but that's been left enabled for a while now, and it hasn't (I think?) been a problem since there shouldn't be anything connected to the board there.  PMC transmission is a little low, 0.816, and FSS is starting to get near -1 on the slow actuator adjust, but we've seen locking of the PMC problems around -1.5 or -2 of the FSS, and the adjust value was at -0.8 earlier tonight and we still had MC locking problems.  I have had the seismic channels open on Dataviewer for the last several hours, and I'm not seeing any spikes in any of the Guralp channels which correspond to the times that the MC loses lock.  BLRMS don't seem particularly high, so MC lockloss cause is still a mystery for today.

The ETMX monitor selector on the VIDEO screen seems not to be switching the actual camera that's shown on the monitor.  Using the script command itself works, so my screen is wrong.

POY was looking funny, and the YARM wasn't locking.  It looked like POY wasn't seeing any light at all.  I went to check, and it looks like a beam dump got accidentally placed in the POY path during oplev adjustments this morning.  POY is back, locking continues.

Optical layout of the current endtable at ETMX has been updated in the svn repository (directory: 40M_Optical Layout). This layout will help in redesigning the table for the proposed replacement.

Some part numbers of mounts/optics are missing and will be updated once I find them. If you find anything wrong with the layout, do let me know.

Temperature sensor for vacuum. How many : 2 or 3 ?  $350 each

Glass encapsulated thermistor #55007  with Ceramabond 835-m glued onto spade connector and hooked up to controller DP25-TH-A with analoge output.

This zero to 10Vdc can go to ADC

I installed pyepics version 3 (http://cars9.uchicago.edu/software/python/pyepics3/overview.html) in ..../scripts/pylibs    .   I also added an "epics.conf" file to /etc/ld.so.conf.d/ , which points to the place in /ligo/apps/epics/base/lib/linux-x86_64/ where the DLLs live.  All .conf files in /etc/ld.so.conf.d/   get included in the path, so python should always automatically be able to use epics now, after you "import epics" in a script.

This is supposed to give us direct channel access to all epics channels, rather than using Yuta's wrapper scripts for ezca stuff.  I was going to write a tdsavg equivalent using camonitor, since it's unclear whether tds tools are being supported anymore.

However, I'm not getting it to connect to the server that serves epics, so I can't get the values of any channels.  All of the info in the link above assumes that you automatically get a connection, and I'm out of ideas right now of things to try.  Does anyone else have any ideas?

Oplevs centered in flashing condition, except PRM and SRM.  IP POS centered also,

I like this new summing screen of Jenne.

The green beam for the Xarm is flashing a pretty nice 00 mode, but isn't catching lock.

The green beam for the Yarm isn't flashing at all that I can tell from just the camera views.  I don't have energy to start this sometimes monumental task tonight, so I leave it for Future Jenne to work on.

I (for the first time personally) locked the FPMI.  I have data for the POX11I, POY11I, AS55Q error signals for each arm and the Michelson (JenneLockingDTT/FPMI_error_signals.xml), but I haven't calibrated the data yet - Self: do this!  FPMI with arms locked using IR has been happily locked for a long time now - this is good.

From elogs / my old MICH calibration script, I have the plant calibrations of:

POY:  1.4e12 cts/m

POX: 3.8e12 cts/m

AS55: 9.4e9 cts/m

MICH has FM 5 on, Xarm has FM4-10 all on, Yarm has FM3-10 all on. 

Post note: FM 3 - the integrator - for Xarm wasn't triggered.  It turns on just fine, so I've got it triggered just like Yarm.

Also, just remembered - I turned off the XARM TRX power normalization, since it was causing crazy numbers in the xarm servo.  The XARM locked pretty easily after that.

MC and PMC vis:

MC REFL Unlocked    = 4.4

MC REFL Locked      = 0.67

 1 - Locked/Unlocked = 85%

PMC REFL Unlocked   = 0.270

PMC REFL Locked     = 0.013

 1 - Locked/Unlocked = 95%

I checked (by looking through recent trends) that the zero level is zero on both channels. I tried to do a proper mode scan, but we have lost the PSL fast channels during the upgrade sadly. Also, the DC signal for the PMC REFL needs some gain. Unlocked level should be more like 3-5 V.

Also used the instructions from this page to add Google's sources to rosalba's apt-get list and then installed Chrome.

 I've noticed that we're experiencing this bug which was previously seen at LHO. We cannot enter 10 digit GPS times into the time fields for DTT due to a limit in TLGEntry.cc, which Jim Batch fixed in September of last year. Seems like we're running an old version of the GDS tools.

I checked the Lidax tool (which you can get from the GDS Mainmenu). It does, in fact, allow 10 digit entries.

Rana points out that we haven't had fast channels for PMC (trans, refl, pzt), input laser things, more FSS things since the upgrade.  Bad.

The videocapture.py script is now in ...../scripts/general/ , along with the videoswitch. 

Also, there's a button gui on the VIDEO medm screen to capture different camera views.

We tracked this down to the power normalization stuff that Yoichi added over the weekend.

With a non-zero normalization factor, and a small TRX transmission, the input the XARM controller gets really big.  When XARM is then triggered, a huge impulse is sent into the SUS_ETMX_LSC input, which causes the Vio2 filter in FM0 to ring like crazy.  This probably also explains why Yoichi was seeing trouble locking the arm when the normalization is on

The solution, as Yoichi also mentions, is probably to trigger the normalization like we trigger the rest of the boost filters.

Static filter was adjusted to filter 1 Hz resonance in MCL and it could do it. Stack is not great in this experiment due to the phase mismatch. I'll fix it.

ETMX has some periodic oscillation. It's damping was found tripped this morning. 

 Atm1, condition: all oplev lasers are off or blocked, green shutters are closed at the ends, PSL out put shutter is closed, all outside LED illuminating are off, all room lights are off

                         Only the OSEMs are on. ETMY and ITMX are still look like illuminated.

Atm2, condition: open PSL shutter. ETMY at 11 o'clock  and ETMX 1 o'clock bright scattered spot of 1064 nm are visible

Atm3, condition: closed PSL shutter and restored all oplev He/Ne lasers, it is visible at ETMY

Next: I will disconnect power to OSEMs at ETMY

I made the signal box as described in eLog 7210. It adds the geophone signal and an external signal.

It has six switches, for x, y, and z signals from both an external and local (geophone) source. The x signals add if both x switches are flipped down (and the same for the other directions). For example, if you want to feed in only an external signal in the x direction, flip down the external x direction switch (it's labeled on the box), leaving all others flipped up.

The x, y, and z outputs are wired to the pins from the preamplifier that go to the high voltage board. These I disconnected from the preamplifier by cutting at their base (there are spare connectors if this wants to be undone, or, a wire can just be soldered from the pin to its old spot on the board). The power (plus/minus) and ground are wired to the respective pins from the geophone preamplifier (naturally, the STACIS must be turned on for the box to work since the box shares its power source). Below, the front (switches and geophone/external inputs) and back (power, ground, outputs) of the box are shown:

The preamplifier can plug into its regular connectors- the x,y,and z signals will all be redirected to the signal box with these modifications. The box sits outside the STACIS, there is room to feed the wires out from underneath the STACIS platform.

NOTE: The geophone z switch is a little different than the others, just make sure it's flipped all the way down if you want that signal to be seen in the z output.

Data from PEM now goes directly to OAF without using RFM. Transmission RFM -> OAF errors are gone as RFM has to read 30 channels less now.

Again kernel "protection error" occured as before with PEM model so OAF model could not start. I changed optimization flag to -02, this fixed the problem.

There was a 5.6 Earthquake that occurred near Tofino, Canada about 30 minutes ago. It showed up rather strongly on the BLRMS.

The neural network classification system also picked up on it, but oscillated from Earthquake (1.0) to Quiet (0.5) perhaps due to the filters we currently have installed. Here is a shot of the GUR1X classification channel at the time of the EQ:

Since the classification finally works (or seems to work..), I wrote triangulation scripts in Python which triangulate the signals, and a plotting script in Matlab which generates a heat map of seismic noise source locations. I switched the ADC Streckeisen and Trillium connections in order to better triangulate with the current channels, and will return them either tomorrow, or when I come back from Livingston so that we can have weekday data as well.

 NVM. Figured out that I can just look in dataviewer for the channels. It looks like there aren't any channels for ADC0...I'll try reinstalling the model and restarting the framebuilder.

I've put EM 172 microphones inside Steve's isolation box to measure their noise. I've attached mics to each other and aligned them using the tape.

At low frequencies (below 1 Hz) the noise is limited by ADC as there is a 10 Hz high-pass filter inside mic readout box.

ADC noise is measured by splitting the signal from 1 mic into 2 ADC channels.

C1LSP has been added to the site map. I'll work on filling in the structure some more today and tomorrow (as well as putting up PDH and REFL/AS MEDM screens).

NOTE: Does anyone know how to access channels (or if they're even there) for straight Simulink inputs and outputs (i.e. I have some sort of input, do something to it in the simulink model, then get some output)? I've been trying to add ADC MEDM screens to c1lsp, but channels along the lines of C1LSP-ADC0_0_Analog_Input or C1LSP-ADC0_A0 don't seem to exist.

Tonight, I worked on the X-arm locking again. I did not have any significant progress, but observed several issues and will give some suggestions for future work here.

What I did tonight was basically re-alignment of the X-arm (because Rana touched the PZT mirrors for the Y-arm alignment, the X-arm alignment was screwed up). Then I measured the open loop gain. Of course it was almost identical to the one posted in this entry. It reminded myself of how small the phase bubble is. This means we have to finely adjust the gain to set the UGF at the right frequency, i.e. 100Hz. So I decided to do the signal normalization using the TRX power. Using the MC path method described here,  the appropriate normalization coefficient was determined to be 1.6, when the XARM gain is set to 0.05. Using burtgooey, I updated the burt snapshot used by the X-arm restore script.

Now I observed the following things:

When the normalization is used, the lock itself is stable, but the lock acquisition takes loner (i.e. fails more often).

I don't know the exact reason, but here is my guess: Usually, the error signal is divided by the square root of the transmitted power to widen the linear range of the PDH error signal. However, what I'm doing here is dividing the error signal with the power itself, not the sqrt. This might distort the error signal in a not-friendly-for-lock way ? I don't know.

I checked the c1lsc FE code. There seems to be the sqrt(TRX) and sqrt(TRY) signals computed in the code. However, these are not used for the normalization. 

Now, there are two requirements. When dragging the mirrors into the resonance, we want to normalize the error signal with sqrt(TRX). When the mirrors reach the resonance, the gain of the loop must be normalized by TRX. How do we smoothly connect those two states ? Someone should spend some time on this. Maybe I will work on this in Japan.  

We really need a time delay in the filter trigger

The automatic filter trigger is awesome. However, the [0^2:5^2] filter, which is an integrator, takes time to switch on and off. Every time the cavity passes by a resonance, this filter gets turned on and off slowly, giving some large transients. This transient combined with the bad coil balance of ETMX sometimes made the optical lever of ETMX crazy. This can be avoided by turning on this filter a few seconds after the power reaches the threshold. As Rana suggested, we should be able to put an arbitrary time delay to the filter trigger.

Someone should balance the coils

The coil balance of ETMX is bad and causing the above mentioned problem. I tweaked the coil balance by injecting a sinusoidal signal (10Hz) into ETMX pos and trying to minimizing the spectral peak in the optical lever signals. Of course, this is a cheesy work. Someone should put more serious effort on this.

A civilized interferometer should have an auto-alignment capability

After my alignment work, the X-arm power got to about 0.7. (This is probably because the MC transmission power has been low for the past 5 hours or so (attachment 1)).

In anyway, after the cavity locked to the TEM00 mode, the alignment has to be automatically improved by dithering. It is anachronism to sit down and click on the MEDM screen until the power gets big enough.

I added a widget to the C1PEM_OVERVIEW MEDM screen. The screen shows the nine seismometer channels (GUR1, GUR2, and STS1 X, Y, and Z), the current signal class in dark red, and the overall confidence in the classification, as Rana suggested. The confidence indication thresholds range from 0.1 to 0.9, in intervals of 0.1. Basically, if a signal class is completely dark red, and the other two classes show only white, or, better yet, nothing at all, this means that we have a clear classification. If, however, the other regions have some yellow, or even red indicators, this means that we are not very confident in our signal classification.

This is a screenshot of the widget. The nine seismometer channels are classifying the signal as quiet, which is good both because it's the middle of the night, and because the nine seismometer signals somehow agree (I'd use the word correspond with one another, but that implies a strong level of coherence..). The confidence is high, seeing as there's little indication in the truck and earthquake regions (none whatsoever in the truck, meaning that the signal, given our classification method, could not possibly be a truck, and some in the earthquake region (below 0.1 of the quiet signal classification strength, however), possibly due to low seismic disturbance).

Changes mentioned by Koji and Steve have been updated to the files (except for the cable connector which have been added but whose part number has to be found to match accurately with the current layout). The file in the directory should now match the current setup after the last vent Aug 2011.

Let me know if you find any mismatch between the current setup and the layout.

Plans about new installations/reconfiguration during the new vent will be carried out in a separate file.

As promised in previous e-log, this log is all about the current online seismic noise classification system.

While we had the BLRMS system already in place (which I helped make), Den realized that we would need better filters for the BLRMS channels, as we wanted a strong cut-off, but we also wanted a short step-response so that we could quickly classify seismic signals. Likewise, having a step response which oscillates is also undesirable as this could lead to false classifications of post-truck signal as trucks as a filter adjusts and then dips back down. Thus, after experimenting with many different filters, Den chose to use a combination of

chebyl("LowPass", 1, 1, 0.03)*chebyl("LowPass", 1, 1, 0.03)

as our low-pass filter. The step response and bode plot are below.

 The next step was to write C code that would implement the feedforward neural network with my newly generated weights.

Next, I had to implement the code in the c1pem model, and normalize the inputs. Below is an overview of the model, and a close up of the C block section.

The above close-up includes the process of normalization (dividing by the square of the incoming signal), feeding through the neural network, and classifying.

Each seismometer channel set (GUR1X, GUR1Y, GUR1Z, GUR2X, GUR2Y, GUR2Z, STS1X, STS1Y, STS1Z) now has channels (and corresponding DQ channels) of the following form:

SEIS_CLASS : The class of seismic noise 1.0 means Earthquake, 0.5 means Quiet, and 0.0 means Truck. (There are only these 3 digital values).

SEIS_CLASS_EQ, SEIS_CLASS_TRUCK, SEIS_CLASS_QUIET: These channels represent the confidence of the neural network's classification. The class of the current signal will have an output of 1, where the other two channels will have an output between 0 and 1 representing the ratio of the neural network's output in that class neuron to the output in the classification vector neuron. To simply - suppose the neural network classified an earthquake. Ideally, the neural network output neurons would have the value [1, 0, 0], and SEIS_CLASS would equal 1.0 for earthquake. However, the output neurons probably read something along the lines of [0.9, 0.3, 0.5] - SEIS_CLASS is still 1.0, but SEIS_CLASS_EQ would be 1.0, and SEIS_CLASS_TRUCK would be 0.5 / 0.9 and SEIS_CLASS_QUIET would be 0.3 / 0.9. The lower the other two signals are, the better - this means that we are more confident in our classification.

The MEDM screen for this system (in the RMS system) has the following form for all seismometer channels (this one is GUR1X):

These are the screens I edited earlier in the summer, with modifications. The bottom filter banks represent the norm of the seismometer signal, which we use to normalize the inputs to the neural network.

Here a close-up of the most important part:

The orange meter on the right points to the current signal type. Here it reads truck - this is ok because it's the middle of the day, and there are a lot of trucks around. The left side represents our confidence in the signal - the signal is classified as a truck, so the "Truck" bar is saturated. The quiet signal bar is very low, which is good since it means that the neural network thinks that it's definitely not quiet. The earthquake bar has some magnitude, since earthquake signals and trucks have some degree of linear non-separability.

How has this been performing? Firstly, all of the seismometer channels have the same classification readout, which is good. Last night, all of the classes were "quiet", with an "earthquake" which occurred when Den jumped around GUR1 to simulate an EQ. This morning it was on "truck" as expected. The filters are still not fine enough to detect individual trucks, but I will continue to monitor the performance over the coming days.

If anyone has ideas on how better to represent this information, please let me know. This was the first thing that came into my head that would work with my MEDM monitor options, and I'm open to suggestions!

Den and I decided to try to classify seismic signals in the frequency domain rather than the time domain. We looked at amplitude spectral density plots of all of the data in our set, and noted that there were noticeable differences in the frequency domain for midnight quiet, trucks, and earthquakes.

For example, here is the time series of quiet, midnight seismic noise as compared to the seismic noise at the peak of an earthquake - the earthquake signal is noticeably higher in the 1 - 3 Hz region. Likewise, for the truck signal, there are noticeable bumps that arise at 10 and 30 Hz during the peak of the truck's motion due to the resonant frequency of the truck bouncing on its wheels.

We investigated this potential means of classification further by considering the linear separability of the power of our signals in various frequency bands. Below is a plot of the power of a normalized signal in the 0.1 - 3.0 Hz region vs. the power of the normalized signal in the 3.0 - 30.0 Hz region - calculated by means of fft and separation of the discrete resulting frequencies (in short, an ideal filter).

There is rather clear linear separability of the normalized signals in this case, as two lines could potentially be drawn to separate trucks from quiet and earthquake in this case (with a few misclassified points due to quiet - since the lab isn't actually empty and quiet in the middle of the night, and man-made seismic disturbances to occur). The reason we have to normalize our signals lies in the fact that the data set had different gains for various seismometers at different times. Normalization not only allows us to use our data set for training effectively, but it also assures that the online classification, if the online signals are also normalized, will allow for variable seismometer gains in the future and still be able to classify signals.

I looked at the linear separability of our training set using various combinations of frequency bands, and deduced that the current separation in the BLRMS preforms best (coincidentally, since the BLRMS separations are just decades), which meant that we could use the current BLRMS system we have for online classification of seismic noise.

Thus, I built a neural network which performed classification with the following parameters:

- One hidden layer of 20 neurons

- Gradient descent backpropagation with learning parameter mu = 0.175

- Sigmoidal activation functions for each neuron (computationally achieved by a parametrized hyperbola rather than an actual hyper-tangent in order to save on computation time). 

- 5 inputs - the normalized fft^2 of the signal (since the root of a signal doesn't add linearly to 1) in the following frequency regions: 0.1 - 0.3, 0.3 - 1.0, 1.0 - 3.0, 3.0 - 10.0 and 10.0 - 30.0 Hz. Since this division was done through the (frequency, fft value) return in Matlab, the signal was essentially filtered ideally into these frequency bands.

- 3 output neurons representing an output vector, with desired output vectors of [1, 0, 0] for earthquake, [0, 1, 0] for truck, and [0, 0, 1] for quiet.

- 1,600,000 training epochs (batch backpropagation on all of the data)

Below is the best learning curve for this network, representing the total amount of inputs misclassified out of 224. The best result achieved was 30 misclassified signals out of 224. Obviously this is not ideal, but our data is not totally linearly separable. This could, however, be reduced with further iterations, but given the close to 0 slope of the learning curve between iteration number 1,000,000 and number 1,500,000, this could take a very long time.

Thus, I trained the network, generated the weight vectors and optimal activation function parameters, and was ready to implement a feed-forward neural network (with no online training). My next e-log (Part 2) will be about this system and will be posted shortly.

 The problem with the glow on the ETMY face is due to the red light being scattered off of the optical table from the HeNe laser for the OL. Why is the red light hitting the table?

One way to fix the problem for the camera image is to insert a long pass filter (if Steve can find one).

 Edmund Optics: NT62-874

 Edmund Optics: NT65-731

Edmund Optics: NT32-759 

 Problem with ITMX solved! The ITMX block in c1sup hadn't been tagged as "top_names". I rebuilt and installed the model, and there are no longer lost connections, :D