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ID Date Author Type Categoryup Subject
  15988   Thu Apr 1 21:13:54 2021 AnchalUpdateSUSMatrix results, new measurement set to trigger
New Input matrix used for MC2 (C1:SUS-MC2_INMATRIX_ii_jj
  UL UR LR LL SIDE
POS 0.2464 0.2591 0.2676 0.2548 -0.1312
PIT 1.7342 0.7594 -2.494 -1.5192 -0.0905
YAW 1.2672 -2.0309 -0.9625 2.3356 -0.2926
SIDE 0.1243 -0.1512 -0.1691 0.1064 0.9962

New output matrix for MC2 (C1:SUS-MC2_TO_COIL_ii_jj_GAIN)
  POS PIT YAW
UL 1 1.022 0.6554
UR 1 0.9776 -1.2532
LL 1 -0.9775 1.2532
LR 1 -1.0219 -0.6554

Measured Sensing Matrix (Cross Coupling) (Sensed DOF x Excited DOF)
  Excited POS Excited PIT Excited YAW
Sensed POS 1 1.9750e-5 -3.5615e-6
Sensed PIT 0 1 -6.93550e-2
Sensed YAW 0 -2.4429e-4 1

A longer measurement is set to trigger at 5:00 tomorrow on April 2nd, 2021. This measurement will run for 35 iterations with an excitation duration of 120s and bandwidth for CSD measurement set to 0.1 Hz. The script is set to trigger in a tmux session named 'cB' on pianosa.

  15991   Fri Apr 2 14:51:20 2021 AnchalUpdateSUSBug found, need to redo the balancing

Last run gave similar results as the quick run we did earlier. The code has been unable to strike out couplings with POS. We found the bug which is causing this. This was because the sampling rate of MC_F channel is different from the test-point channels used for PIT and YAW. Even though we were aware of it, we made an error in handling it while calculating CSD. Due to this, CSD calculation with POS data was performed by the code with zero padding which made it think that no PIT/YAW <-> POS coupling exist. blushHence our code was only able to fix PIT <-> YAW couplings.

We'll need to do another run with this bug fixed. I'll update this post with details of the new measurement.

 

  15993   Fri Apr 2 15:22:54 2021 gautamUpdateSUSMatrix results, new measurement set to trigger

How should I try to understand why PIT and YAW are so different? 

Quote:
New output matrix for MC2 (C1:SUS-MC2_TO_COIL_ii_jj_GAIN)
  POS PIT YAW
UL 1 1.022 0.6554
UR 1 0.9776 -1.2532
LL 1 -0.9775 1.2532
LR 1 -1.0219 -0.6554
  16001   Tue Apr 6 18:46:36 2021 Anchal, PacoUpdateSUSUpdates on recent efforts

As mentioned in last post, we earlier made an error in making sure that all time series arrays go in with same sampling rate in CSD calculation. When we fixed that, our recursive method just blew out in all the efforts since then.


We suspect a major issue is how our measured sensing matrix (the cross-coupling matrix between different degrees of freedom on excitation) has significant imaginary parts in it. We discard the imaginary vaues and only use real parts for iterative method, but we think this is not the solution.

Here we present cross-spectral density of different channels representing the three sensed DOFs (normalized by ASD of no excitation data for each involved component) and the sensing matrix (TF estimate) calculated by normalizing the first cross spectral density plots column wise by the diagonal values. These are measured with existing ideal output matrix but with the new input matrix. This is to get an idea of how these elements look when we use them.

Note, that we used only 10 seconds of data in this run and used binwidth of 0.25Hz. When we used binwidth of 0.1 Hz, we found that the peaks were broad and highest at 13.1 Hz instead of 13 Hz which is the excitation frequency used in these measurements.


How should we proceed?

  • We feel that we should figure out a way to use the imaginary value of the sensing matrix, either directly or as weights representing noise in that particular data point.
  • Should we increase the excitation amplitude? We are currently using 500 counts of excitation on coil output.
  • Are there any other iterative methods for finding the inverse of the matrix that we should be aware of? Our current method is rudimentary and converges linearly.
  • Should we use the absolute value of the sensing matrix instead? In our experience, that is equivalent to simply taking ratios of the PSD of each channel and does not work as well as the TF estimate method.
  16003   Wed Apr 7 02:50:49 2021 KojiUpdateSUSFlange Inspections

Basically I went around all the chambers and all the DB25 flanges to check the invac cable configurations. Also took more time to check the coil Rs and Ls.

Exceptions are the TTs. To avoid unexpected misalignment of the TTs, I didn't try to disconnect the TT cables from the flanges.

Upon the disconnection of the SOS cables, the following steps are taken to avoid large impact to the SOSs

  • The alignment biases were saved or recorded.
  • Gradually moved the biases to 0
  • Turned off the watchdogs (thus damping)

After the measurement, IMC was lock and aligned. The two arms were locked and aligned with ASS. And the PRM alignment (when "misalign" was disengaged) was checked with the REFL CCD.
So I believe the SOSs are functioning as before, but if you find anything, please let me know.
 

  16004   Wed Apr 7 13:07:03 2021 JordanUpdateSUSCoM on 3"->2" Adapter Ring for SOS

Adding the chamfer around the edge of the optic ring did not change the center of mass relative to the plane from the suspension wires.

The CoM was .0003" away from the plane. Adding the chamfer moved it closer by .0001". See the attached photo.

I've also attached the list of the Moments of Inertia of the SOS Assembly.

  16005   Wed Apr 7 17:38:51 2021 AnchalUpdateSUSTrying to uncouple only PIT and YAW first

To test if our method is working at all, we went for the simpler case of just uncoupling PIT and YAW. This is also because the sensor used for these two degrees of freedom is similar (the MC Trans WFS).

We saw a successful decrease in cross-coupling between PIT and YAW over the first 50 iterations that we tried. Here are some results:


Final output matrix:

Output matrix for uncoupling PIT and YAW from eachother
PIT YAW COILS
1.01858 1.16820 UL
0.98107 -0.79706 UR
-0.98107 0.79706 LL
-1.01858 -1.16820 LR

Plots:

  • Attachment 1 shows distance of sensing matrix from identity as iterations go.
  • Attachment 2 shows the off-diagonal elements of sensing matrix as the iterations increase.
    • It is worth noting that PIT -> YAW coupling was the main element that was reduced successfully while the YAW -> PIT was reducing but much more slowly.
    • Most of the remaining cross coupling in the end was from YAW -> PIT.
  • Attachment 3 shows first 10 oscillations in the time series data during excitation of some of the iterations.
  • Attachment 4 shows the cross spectral density of the sensed data during excitation with each other. This has been normalized by reference PSD data (taken with no excitation) of the sensed DOFs involved in the CSD calculation.
  • Attachment 5 shows the TF estimate made by normalizing CSD data column wise by the diagonal elements. The excitation frequency point in these plots become the Sensing matrix in the calculation.
    • One can notice how the PIT -> YAW element is going down in these plots.
    • Even though we are using only the real value of the sensing matrix, the imaginary values are also going down.

Next, tried uncoupling POS and PIT:

  • Next, we tried to uncouple POS and PIT. We expect them to be more coupled than with YAW.
  • At the time of writing this post, 15 iterations of this attempt have been completed and it is not looking good sad.
  • The distance of the sensing matrix from identity is growing at an accelerated rate.
  • The POS output matrix column seems to be trying to go towards the negative of PIT output matrix column! Why? We don't know.
  • We have seen in the past that once POS transforms into PIT or YAW, it just makes the output matrix worse as no feedback actually goes into the POS column. Eventually, the IMC will cease to remain locked.
  • So, I'm cancelling this attempt for now. Will consider more alternatives later.
  16007   Thu Apr 8 17:04:43 2021 Anchal, PacoUpdateSUSFirst Successful Coil Balancing

Today, we finally crossed the last hurdle and got a successful converging coil balancing run. laugh


What was the issue with POS?

  • Position of the MC2 mirror is being sensed using C1:IOO-MC_F_DQ channel which is proportional to the resonant frequency of the locked IMC.
  • However, this sensor is always 180 degrees out of phase of our actuator, the coils.
  • When the coils push the mirror forward, the length of the cavity actually decreases.
  • We added an extra option of providing a sign to the sensors such that -1 will be multiplied to sensed values for sensors which measure in opposite direction to the actuation.
  • This is important, because the feedback is applied to the coil output matrix assuming a particular direction of acctuation.
  • When we gave negative sign for the position sensor, it all started making sense and the algorithm started converging.

First run parameters:

  • We used binwidth of 0.25 Hz and duration of excitation as 41s. This would give welch and csd averaging of 19. We used median averaging to ignore outliers.
  • This iteration was run after PIT and YAW were separetly uncoupled before. We'll post a clean start to end run results in near future.
  • The iteration works in following manner:
    • Define a constant coil matrix C = [[1, 1, 1], [1, 1, -1], [1, -1, 1], [1, -1, -1]] which is ideal coil output matrix.
    • In each iteration, the output matrix Ok is defined as (note @ is the matmul operator):
      Ok = C @ Ak
      where Ak is a 3x3 matrix. A-1 is identity matrix.
    • At the end of each iteration, a sensing matrix is calculated in dimensions sensedDOF x excitedDOF, Sk
    • For next iteration, Ak+1 is calcualted by:
      Ak+1 = Ak - b * (Sk - I)
      where I is the identity matrix.
    • At convergence, the sensing matrix would become same as identity and matrix A will stop updating.
  • For this run, we kept the parameter b to be 0.05. This is similar to the KP parameter in PID loops. It should be between 0 and 1.
  • Since b value was small enough to allow for convergence from the inital point, but later it slowed down the process a lot.
  • Ideally, we should figure out a way to increase this paramter when the coil has been balanced somewhat, to increase the speed of the algorithm.
  • Secondly, we have a code which excites all DOFs at different frequencies directly using excitation channels in coil output matrix using awg.py. But for some reason, the excitation channel for 4th row in the output matrix column only connects intermittantly. Because of this, we can't use this method reliably yet. We can investigate more into it if suggested.

Balancing characteristics:

  • Attachment 1 shows how the distance of sensing matrix falls as iterations increase. We only ran for 50 iterations.
  • Attachment 2 shows how different off-diagonal terms of sensing matrix decreased.
    • Note that POS -> PIT, POS -> YAW and PIT-YAW have settled down to the noise floor.
    • The noise floor can be improved by increasing the excitation amplitude and/or increasing the duration of measurement.
  • Attachment 3 shows the evolution of sensing matrix as iterations move.

Final balanced output matrix:

Final balanced output coil matrix for MC2
POS PIT YAW COILS
1.02956 1.13053 1.19116 UL
1.01210 1.09188 -0.74832 UR
0.98737 -0.85502 0.70485 LR
0.96991 -0.89366 -1.23463 LR
Final Sensing Matrix
  Exc POS Exc PIT Exc YAW
Sens POS 1 -2.96e-2 8.00e-3
Sens PIT 8.58e-4 1 -4.84e-3
Sens YAW 5.97e-4 -1.15e-3 1

Code features and next:

  • Majority of the code is in two files: scripts/SUS/OutMatCalc/MC2crossCoupleTest.py and scripts/SUS/OutMatCalc/crossCoupleTest.py .
  • The code runs from start to end without human involevement and restores the state of channels in any case (error, kyboard interrupt, end of code) using finally statement.
  • Currently, each excitation is done one at a time through LockIn1. As mentioned above, this can be sped up 3 times if we get the awg.py to work reliably.
  • The complete code is in python3 and currently is run through native python3 on allegra (a new debian10 workstation with latest cds-workstation installed).
  • The code can be easily generalized for balancing any optic. Please let us know if we should work on making the generalized optic.
  • We're also working on thinking about increasing b as iterations move forward and the error signal becomes smaller.
  • We can also include the uncertainty in the Sensing matrix measurement to provide a weighted feedback. That way, we can probably increase b more.
  16009   Fri Apr 9 13:13:00 2021 Anchal, PacoUpdateSUSFaster coil balancing

We ran again this method but with the 'b' parameter as a matrix instead. This provides more gain on some off-diagonal terms than others. This gave us a better convergence with the code reaching to the tolerance level provided (0.01 distance of S matrix from identity) within 16 iterations (~17 mins).


Attachment 1 again shows how the off-diagonal terms go down and how the overall distance of sensing matrix from identity goes down. This is 'Cross coupling budget' of the coils as iterations move forward.


Jumping to near zero-crossing:

  • Rana mentioned a ezlockin code which first makes 5 step changes in output matrix without using feedback and calculates the changes required to reach zero-crossing in the behavior of the off-diagonal terms during these steps.
  • This is similar to what we did above by hand where we increased the value of b for slowly converging off-diagonal elements.
  • We plan to implement this 'jump' to near zero-crossing method next. Aim is to get a coil balancing code that does the job in ~5 min.
  • We have been throwing away imaginary part of sensing matrix so far. We wanted to get to some owrking solution before we try more complex stuff. We have to figure out global phases in each transfer function estimate to rotate the measured transfer function appropriately.
  16010   Fri Apr 9 17:41:12 2021 ranaUpdateSUSFaster coil balancing

convergence is great.

Next we wanna get the F2A filters made since most of the IMC control happens at f < 3 Hz. Once you have the SUS state space model, you should be able to see how this can be done using only the free'swinging eigenfrequencies. Then you should get the closed loop model including the F2A filters and the damping filters to see what the closed loop behavior is like.

 

  16014   Sat Apr 10 10:07:47 2021 ranaUpdateSUSFaster coil balancing

I think I mis-spoke about the balancing channels before. The ~20 Hz balancing could go into either the COIL banks or the SUS output matrix.

I believe its more conceptually clean to do this as gains in the outputmatrix, and leave the coil gains as +/- 1. i.e. we would only use the coil gains to compensate for coil/magnet actuation strength.

Then the high frequency balance goes into the outputmatrix. The F2A and A2L decoupling filters would then be generated having a high frequency gain = 1.

  16017   Mon Apr 12 10:07:35 2021 AnchalUpdateSUSWhat's F2A??

I'm not sure I understand what F2A is? I couldn't find a description of this filter anywhere and don't remember if you have already explained it. Can you describe what is needed to be done again, please? We would keep SUS state space model and seismic transfer functions calculation ready meanwhile.

Quote:

Next we wanna get the F2A filters made since most of the IMC control happens at f < 3 Hz. Once you have the SUS state space model, you should be able to see how this can be done using only the free'swinging eigenfrequencies. Then you should get the closed loop model including the F2A filters and the damping filters to see what the closed loop behavior is like.

 

  16020   Tue Apr 13 09:51:22 2021 ranaUpdateSUSWhat's F2A??

Force to Angle. It just means the filters that are in the POS OUTPUT matrix. I think in the past sometimes they are called F2P or F2A.

These filters account for the frequency dependent coupling of the DOFs around the suspension resonance. Take a look at what Bhavini is doing for the plots.

 

  16031   Wed Apr 14 17:53:38 2021 AnchalUpdateSUSPlan for calculating filter banks for output matrix aka F2A aka F2P

Plan of action

  • Get the transfer functions of the suspension plant from actuated DOF to sensed DOF. We'll verify Bhavini's state-space model and get these transfer functions. Use the model TFs, not measured.
  • For each of POS->POS, PIT->PIT, and YAW->YAW, we'll get the resonant frequency and Q of the resonance from these models. No, forget about the Q.
  • We can correct the resonant frequencies from the measured ones in our free swinging data.
  • Now, we'll repeat the following for each column of output matrix filters (inspired from scripts/SUS/F2Pcalc.py, but not fully understood how/why):
    • Select col (eg. POS)
    • Set f0 to the resonant frequency.
    • Calculate \large f_{UL} = f_0 * \sqrt{G_{UL}} where GUL is the corrected DC gain we got after output matrix optimization earlier. (Not sure how, why?). No, use the SS model.
    • Calculate fUR, fLL, and fLR like above.
    • Set \large Q_{UL} = \sqrt{G_{UL}}   (This just seems like a way of keeping some approximately low Q, ideally we should keep this same to what we got above but that might cause saturation issues like Rana mentioned in the meeting)
    • Then, set the following filter in the output matrix element for UL:
                            G_{UL}\frac{1 + i\frac{f}{f_{UL}Q_{UL}} - \frac{f^2}{f_{UL}^2}}{1 + i\frac{f}{f_{0}} - \frac{f^2}{f_{0}^2}}
      which is in zpk form equivalent to:
                            z: \frac{f_0}{2 Q_{UL}} +/- i f_0 \sqrt{1 - \frac{1}{4Q_{UL}}} \quad, \quad p: \frac{f_0}{2} +/- i f_0 \frac{\sqrt{3}}{2} \quad, \quad k: G_{UL}
    • Repeat the above for UR, LL, LR.
    • Note that this filter function takes values GUL at DC and at high frequencies while it would dip at the resonant frequency for POS with depth and narrowness directly proportional to QUL. No, the DC gain is different from the AC gain.
  • However, the F2P filter plots we found in several places on elog look a bit different. Like here: 40m/4719. One important difference is that the filter magnitude always become 1 after the resonance at higher frequencies. Yes, this is  what we want, since you already did the balancing at high frequencies.
  • A preliminary plot of the above calculation for the 1,1 output matrix filter bank (POS -> UL) is attached in Attachment 1.

Discussion:

  • We can make 12 such filters for the 12 numbers we got for the optimized output matrix. Is that the aim or should we do it only for the POS column as has been done in past?
  • We are not sure how the choice of Q is made in setting the above filter function. We'll think more about it to understand this.
  • We are also not sure how the choice of fUL is made above. It looks like depending on the correction gain, we want to slide the zero positions with respect to the pole positions which are fixed at the resonant frequency as expected. This seems to have some complex explanation.
  • Please let us know if we are planning this right before we dive into these calculations/script writing. Thanks.

Edit Thu Apr 15 08:32:58 2021 :

Comments are from Rana.

Corrected the plot in the attachment. It shows the correct behavior at high frequencies now.

  16035   Thu Apr 15 11:41:43 2021 AnchalUpdateSUSProposed filters for output matrix aka F2A aka F2P

Here' s aquick update before we leave for lunch. We have managed to calculate some filter that would go on the POS column in MC2 output matrix filter banks aka F2A aka F2P filters. In the afternoon if we can come and work on the IMC, we'll try to load them on the output matrix. We have never done that so it might take some time for us to understand on how to do that. Attached is the bode plot for these proposed filters. Let us know if you have any comments.

  16042   Fri Apr 16 11:36:36 2021 Anchal, PacoUpdateSUSTested proposed filters for POS colum in MC2 output matrix

We tried two sets of filters on the output matrix POS column in MC2. Both versions failed. Following are some details.


How test was done:

  • PSL shutter was closed and autolocker was switch off.
  • Turned off damping on POS, PIT, and YAW using C1:SUS-MC2_SUSPOS_SW2, C1:SUS-MC2_SUSPIT_SW2, and C1:SUS-MC2_SUSYAW_SW2.
  • Reference data was taken with no excitation to get relative increase at excitation.
  • Channels C1:SUS-MC2_SUSPIT_IN1, C1:SUS-MC2_SUSPOS_IN1, and C1:SUS-MC2_SUSYAW_IN1.
  • Frist we sent an excitation through LOCKIN1 at 0.11 Hz and 500 counts amplitude.
  • LOCKIN column in MC2 output matrix was kept identical to POS column, so all ones.
  • This formed our reference data set when no filters were used. Attachment 1.
  • Note that the peak at 0.03 Hz is due to LOCKIN2 that was left switched on due to autolocker.
  • Then the calculated filters were loaded using foton. Procedure:
    • Right click on filter bank med. Got to Execute-> Foton.
    • Go to File and uncheck 'Read Only'.
    • Find the filter module name in Module drop down.
    • Select an empty module section in Sections.
    • Write a name for the filter. We used DCcoupF2A and DCcouF2A2 for the two version respectively.
    • Paste the zpk foton format in Command.
    • Check with Bode plot if these are correct filters. Then click on Save. It will take about 30s to become responsive again.
    • GO back to filter bank medm screen and click on 'Load Coefficients'. This should start displaying your new filter module.
    • To switch on the module, click on the button below its name.
  • Once fitlers were loaded, we realized we can not use the LOCKIn to excite anymore as it comes as separate excitation.
  • So we used awggui to excite C1:SUS-MC2_LSCEXC at 0.11 Hz and 500 counts.
  • Then we retook the data and checked if the peaks are visible on PIT and YAW channels and how high they are.

Filer version 1

  • This was calculated by starting from ideal output matrix elements as they are currently loaded. All 1's for POS and so on.
  • The calculations were done in scripts/SUS/OutMatCalc/coilBalanceDC.py.
  • This file uses a state space model of the suspension and calculated the cross-coupling. Then the cross coupling is inverted and applied to the current output matrix elements to get correction DC gains.
  • These corrected DC gains are then used to create the filters as described in last post.
  • Attachment 2 shows the filter transfer functions and Attachment 3 shows the test results. Failed :(.
  • There was practivally no change in cross coupling that we can see.

Filter version 2:

  • In this version we used the output matrix optimized at high frequencies earlier (16009).
  • While testing this version, we also uploaded this optimised output amtrix at high frequency.
  • In this test, we realized the LOCKIN2 was on and switched it off manually. All excitations were done through awggui.
  • Attachment 4 shows the filter transfer functions and Attachment 5 shows the test results. Failed :(.
  • There was again practivally no change in cross coupling that we can see.

Forgot to upload new MC2 input matrix:

  • In hindsight, we should have uploaded our diagonalized suspension input matrix in MC2.
  • Without it, there was cross-coupling the in the sensor data to begin with.
  • But this can only be part of the reason why all our filters failed miserably.
  • Because the output matrix was not diagonalized earlier but it was not so bad. Onyl a fresh test can tell if it was the culprit.
  16043   Fri Apr 16 15:47:58 2021 ranaUpdateSUSTested proposed filters for POS colum in MC2 output matrix

Looks mostly right, but you used the OSEM sensors as readbacks. We are diagonalizing using the cavity sensors. Using the diagonalized input matrix is also good since that will reduce the cross-coupling due to the damping loops.

Its sort of a subtle issue:

  1. The sensors are are diagonalized into the eigenmode basis, not the Cartesian basis of the mirror motion.
  2. What the cavity cares about is the Cartesian motion.
  3. Q1: in the model, how much Cartesian pitch motion is there at the POS eigenfrequency in the free-swinging case?
  4. Q2: should we somehow diag the input matrix into the Cartesian basis?
  5. Q3: if so, How?
  6. Q4: and why?
  16049   Mon Apr 19 12:18:19 2021 Anchal, PacoUpdateSUSTested proposed filters for POS colum in MC2 output matrix

The filters were somewhat successful, how much we can see in attachment 1. The tip about difference between eigenmode basis and cartesian basis was the main thing that helped us take data properly. We still used OSEM data but rotated the output from POS, PIT, YAW to x, theta, phi (cartesian basis where x is also measured as angle projected by suspension length).


Eigenmode basis and Cartesian basis:

  • It is important to understand the difference between these two and what channels/sensors read what.
  • Eigenmode basis as the name suggests is the natural basis for the suspended pendulum.
    • It signifies the motion along three independent and orthogonal modes of motion: POS (longitudinal pendulum oscillation), PIT, and YAW.
    • The position of optic can be written in eigenmode basis as three numbers:
      • POS: Angle made by the center of mass of optic with verticle line from suspension point.
      • PIT: Angle made by the optic face with the suspension wires (this is important to note).
      • YAW: Angle made by optic surface with the nominal plane of suspension wires. (the yaw angle basically).
  • Cartesian basis is the lab reference frame.
    • Here we define three variables that can also represent an optic positioned and orientation:
      • x: Angle made by the center of mass of optic with verticle line from suspension point. (Same as POS)
      • \large \theta: Angle made by the optic surface with absolute verticle (z-axis) in lab frame.
      • \large \phi: Twist of the optic around the z-axis. Same as YAW angle above.
  • We want to apply the feedback gains and filters in eigenmode basis because they are a set of known independent modes. (RXA: NOOO!!!!!! read me elog entry on this topic)
  • Hence, the output from input matrix of suspensions comes out at POS, PIT and YAW in the eigenmode basis.
  • However, the sensors of optic positional, and orientation such at MC_F, wave front sensors and optical levers measure it in lab frame and thus in cartesian basis.
  • Essentially, the \large \theta measured by these sensors is different from the PIT calculated using the OSEM sensor data and is related by:
    • \large \theta = PIT - POS, where PIT and POS both are in radians as defined above.
  • When we optimized the cross-coupling in output matrix at high frequencies using the MC_F and WFS data, we actually optimized it In cartesian basis.
  • The three feedback filters from POS, PIT and YAW which carry data in the eigenmode basis need to be rotated into the cartesian basis in the output matrix before application to the coils.
  • The so-called F2A and A2L filters are essentially doing this rotation.
  • Above the resonant frequencies, the PIT and \large \theta become identical. Hence we want our filters to go to unity

The two filter sets:

  • The filters are named Eg2Ctv1 and Eg2Ctv2 on the POS column of MC2 output matrix.
  • This is to signify that these filters convert the POS, PIT, and YAW basis data (eigenmode basis data) into the cartesian basis (x, theta, phi) in which the output matrix is already optimized at higher frequencies.
  • v1 filter used an ideal output matrix during the calculation of filter as described in 16042 (script at scripts/SUS/OutMatCalc/coilBalanceDC.py).
  • Attachment 2 shows these filter transfer functions.
  • v2 filter use the output matrix optimized to reduce cross-coupling amount cartesian basis modes (MC_F, WFS_PIT and WFS_YAW) in 16009.
  • Attachment 3 shows these filter transfer funcitons.
  • Because of this, the v2 filter is different among right and left coils as well. We do see in Attachment 1 that this version of filter helps in reducing POS->YAW coupling too.

Test procedure:

  • We uploaded both the diagonalized input matrix and the diagonalized output matrix as calculated earlier.
  • We measured channels C1:SUS-MC2_SUSPOS_IN1_DQ, C1:SUS-MC2_SUSPIT_IN1_DQ, and C1:SUS-MC2_SUSYAW_IN1_DQ throughout this test.
  • These channels give output in an eigenmode basis (POS, PIT, and YAW) and the rows of the input matrix have some arbitrary normalization.
  • We normalize these channels to have same input matrix normalization as would be for ideal matrix (2 in each row).
  • Then, assuming the UL_SENS, UR_SENS, LR_SENS, and LL_SENS channels that come at input of the input matrix are calibrated in units of um, we calculate the cartesian angles x, theta, phi. for this calculation, we used the distance between coils as 49.4 mm (got it from Koji) and length of suspension as 0.2489 m and offset of suspension points from COM, b = 0.9 mm.
  • Now that we have true measures of angles in cartesian basis, we can use them to understand the effect on cross coupling from the filters we used.
  • PSL shutter is closed and autolocker is disabled. During all data measurements, we switched of suspension damping loops. This would ensure that our low frequency excitation survives for measurement at the measurement channels.
  • We first took reference data with no excitation and no filters for getting a baseline on each channel (dotted curves in Attachment 1).
  • We then send excitation of 0.03 Hz with 500 counts amplitude at C1:SUS-MC2_LSC_EXC and switched on LSC output.
  • One set of data is taken with no filters active (dashed curve in attachment 1).
  • Then two sets of data are taken with the two filters. Each data set was of 500s in length.
  • Welch function is used to take the PSD of data with bin widht of  0.01Hz and 9 averages.

Results:

  • Filter v1 was the most successful in reducing \large x \rightarrow \theta coupling by factor of 17.5.
    • The reduction in \large x \rightarrow \phi coupling was less. By a factor of 1.4.
  • Filter v2 was worse but still did a reduction of \large x \rightarrow \theta coupling by factor of 7.8.
    • The reduction in \large x \rightarrow \phi coupling was better. By a factor of 3.3.

Next, filters in PIT columns too

  • We do have filters calculated for PIT as well.
  • Now that we know how to test these properly, we can test them tomorrow fairly quickly.
  • For the YAW column though, the filters would probably just undo the output matrix optimization as they are derived from ideal transfer function models and ideally there is no coupling between YAW and other DOFs. So maybe, we should skip putting these on.
  16054   Tue Apr 20 10:52:49 2021 Anchal, PacoUpdateSUSAC gain coil output balancing for IMC

[Paco, Anchal]

  • We adopted the following procedure to balance the coil output gains using a high-frequency (> 10 Hz) excitation on "C1:SUS-MCX_ASCPIT_EXC", "C1:SUS-MCX_ASCYAW_EXC", and "C1:SUS-MCX_LSC_EXC", where X is one of {1, 2, 3} for the three IMC optics, and the cavity sensors (MC_F, and MC_TRANS);
    1. We load the new input matrix found on March-23rd.
    2. Using awggui, we launch a single 23.17 Hz sine with 500 - 1000 counts amplitude on the aforementioned channels.
      • We are still unable to launch multiple excitations simultaneously through either API (python-awg or dtt-awggui) devilno
    3. Using our built-in hominid neural networks, we look at the "C1:IOO-MC_F", "C1:IOO-MC_TRANS_PIT_IN", and "C1:IOO-MC_TRANS_YAW_IN" exponentially averaging power spectra, on and about the excitation frequency, and identify the amount of cross-coupling going into angular or longitudinal motion depending on the excited degree of freedom.
    4. We step the "C1:SUS-MCX_URCOIL_GAIN", "C1:SUS-MCX_ULCOIL_GAIN", "C1:SUS-MCX_LRCOIL_GAIN", "C1:SUS-MCX_LLCOIL_GAIN" coil output gains by hand in the presence of an excitation (e.g. "LSC") along a given degree of freedom (e.g. along "PIT") to try and minimize the coupling.
    5. We iterate step (4) until we find an optimum gain set, and move on to another optic.

Results

  • For MC2 the optimal gains changed from: [1.0, -1.0, 1.0, -1.0] → [1.05, -1.05, 0.995, -1.03] **
    • Here we were able to first decouple PIT and YAW from a POS excitation almost entirely (see Attachment #1), but weren't as successful in decoupling YAW and POS from PIT, or PIT and POS from YAW excitations (Attachment #2).
  • For MC1 the optimal gains changed from: [1.0, 1.0, 1.0, 1.0] → [0.282, 0.035, 0.302, 2.46] **
    • Here we mostly succeeded in decoupling POS from YAW and PIT excitations (see Attachments #3 - 4).
  • For MC3 the optimal gains changed from: [1.0, -1.0, 1.0, -1.0] → [0.126, -0.123, 0.298, -0.306] **
    • Here the LSC_EXC didn't show up on MC_F (??), and the PIT/YAW excitations decouple by virtue of seemingly low gains, so maybe the optimum is an artifact of the lower coil gains...
    • Plots are to follow up for this one.

** The notation here is [UL, UR, LR, LL]


  16055   Tue Apr 20 18:19:30 2021 AnchalUpdateSUSMC2 coil balanced at DC

Following up from morning's work, I balanced the coils at DC as well. Attachment 1 is screenshot of striptool in which blue and red traces show ASCYAW and ASCPIT outputs when C1:SUS-MC2_LSC_OFFSET was switched by 500 counts. We see very slight disturbance but no real DC offset shown on PIT and YAW due to position step. This data was taken while nominal F2A filter calculated to balance coils at DC was uploaded


I have uploaded the filters on filter banks 7-10 where FM7 is the nominal filter with Q close to 1 and 8-10 are filters with Q 3, 7 and 10 respectively. The transfer function of these filters can be seen in Attachment 2. Note, that the high frequency gain drops a lot when higher Q filters are used.

These filters are designed such that the total DC gain after the application of coil outputs gains for high frequency balancing (as done in morning 16054) balances the coils at DC.


Since I had access to the complete output matrix that balances the coils to less than 1% cross coupling at high frequencies from 16009, I also did a quick test of DC coil balancing with this kind of high frequency balancing. In this case, I uploaded another set of filters which were made at Q close to 1 and gain such that effective DC gain matrix becomes what I got by balancing in the above case. This set of filter also worked as good as the above filters. This completes the proof that we can also use complete matrix for high frequency coil balancing which can be calculated by a script in 20min and works with DC coil balancing as well. In my opinion, this method is more clear and much faster than toggling values in coil output gains where we have only 4 values to optimize 6 cross-coupling parameters. But don't worry, I'm not wasting time on this and will abandon this effort for now, to be taken up in future.


Next up:

  • Tomorrow, we'll finish DC balancing for MC1 and MC3 with the method I practiced today. This should not take much time and should be completed before the meeting.
  • I'll also, calculate and upload the F2A filters for MC1 and MC3.
  • Next, we'll optimize gains in the suspension damping loops by doing step response test (with TRAMP = 0s). We'll look for decaying response (at MC_F, and WFS sensors) with a few oscillations for each step in POS, PIT, and YAW.

Edit Tue Apr 20 21:25:46 2021 :

Corrected the calculation of filters in case of Q different than \large \sqrt{G_{DC}}. There was a bug in the code which I overlooked. I'll correct the filter bank modules tomorrow.


Edit Wed Apr 21 11:06:42 2021 :

I have uploaded the corrected foton filters. Please see attachment 3 for the transfer functions calculated by foton. They match the filters we intended to upload. Only after uploading and closing the foton filter, I realized that the X=7 filter plot (bottom left in attachment 3) does not have dB units on y-axis. It is plotted in linear y-scale (this plot in foton is for phase by default to I guess I forgot to change the scaling when repurposing it for my plot).

  16063   Wed Apr 21 11:38:27 2021 Anchal, PacoUpdateSUSMC2 Damping Gains Optimized

We did a step response test with MC2 Suspensoin Damping Gains and optimized them to get <5 oscillations in ringdown.


Procedure:

  • We uploaded the diagonalized input matrix.
  • We uploaded the coil balancing gains at high frequencies found in 16054.
  • We applied Eg2CtQ1 filter module for DC gain balancing foun inf 16055.
  • We set TRAMP to 0 in C1:SUS-MC2_SUSPOS_TRAMP, C1:SUS-MC2_SUSPIT_TRAMP, and C1:SUS-MC2_SUSYAW_TRAMP.
  • We played with offsets to get a good step height. Finally we used:
    • C1:SUS-MC2_SUSPOS_OFFSET: 3000
    • C1:SUS-MC2_SUSPIT_OFFSET: 100
    • C1:SUS-MC2_SUSYAW_OFFSET: 100
  • We looked at channels C1:SUS-MC2_SUSPOS_INMON, C1:SUS-MC2_SUSPIT_INMON, and C1:SUS-MC2_SUSYAW_INMON on a striptool screen to see the step response of the switching on/off of the offsets.
  • We tried to decrease/increase gain to get <5 oscillations during ringdown due to the step inputs.
  • Restored everything back to old values at the end.

Results:

  • Gain in POS was found to be already good. In PIT and YAW we changed the gains from 10 -> 30.
  • Attachment 1 shows the striptool screen when offset was switched ON/Off in POS, PIT and YAW respectively after appling the optimized gains.
  • Attachment 2 shows the same test with old gains for comparison.

In the afternoon, we'll complete doing the above steps for MC1 and MC3. Their coil balancing has not been done on DC so, it is bit non-ideal right now. We'll look into scripting this process as well.

  16066   Wed Apr 21 15:50:01 2021 Anchal, PacoUpdateSUSMC2 Suspension Optimization summary
MC2 Coil Balancing DC and AC Gains
  POS PIT YAW COIL_GAIN (AC balancing)

UL

1.038 1 1 1.05
UR 1.009 1 -1 -1.05
LL 0.913 -1 1 -1.030
LR 0.915 -1 -1 0.995

MC2 Diagonalized input matrix
  UL UR LR LL SIDE
POS 0.2464 0.2591 0.2676 0.2548 -0.1312
PIT 1.7342 0.7594 -2.494 -1.5192 -0.0905
YAW 1.2672 -2.0309 -0.9625 2.3356 -0.2926
SIDE 0.1243 -0.1512 -0.1691 0.1064 0.9962

MC2 Suspension Gains
  Old gain New Gain
SUSPOS 150 150
SUSPIT 10 30
SUSYAW 10 30

 

  16067   Wed Apr 21 18:49:29 2021 ranaUpdateSUSMC2 Suspension Optimization summary

the POS column should be all 1 for the AC balancing. Where did those non-1 numbers come from?

  16071   Thu Apr 22 08:50:21 2021 AnchalUpdateSUSMC2 Suspension Optimization summary

Yes, during the AC balancing, POS column was set to all 1. This table shows the final values after all the steps. The first 3 columns are DC balancing results when output matrix was changed. While the last column is for AC balancing. During AC balancing, the output matrix was kept to ideal position as you suggested.

Quote:

the POS column should be all 1 for the AC balancing. Where did those non-1 numbers come from?

 

  16072   Thu Apr 22 12:17:23 2021 Anchal, PacoUpdateSUSMC1 and MC3 Suspension Optimization Summary
MC1 Coil Balancing DC and AC Gains
  POS (DC coil Gain) PIT (DC coil Gain) YAW (DC coil Gain) Coil Output Gains (AC)
UL 0.6613 1 1 0.5885
UR 0.7557 1 -1 0.1636
LL 1.3354 -1 1 1.8348
LR 1.0992 -1 -1 0.5101

Note: The AC gains were measured by keeping output matrix to ideal values of 1s. When optimizing DC gains, the AC gains were uploaded in coil ouput gains.


MC1 Diagonalized input matrix
  UL UR LR LL SIDE
POS 0.1700 0.1125 0.0725 0.1300 0.4416
PIT 0.1229 0.1671 -0.1021 -0.1463 0.1567
YAW 0.2438 -0.1671 -0.2543 0.1566 -0.0216
SIDE 0.0023 0.0010 0.0002 0.0015 0.0360

MC1 Suspension Damping Gains
  Old gains New Gains
SUSPOS 120 270
SUSPIT 60 180
SUSYAW 60 180


MC3 Coil Balancing DC and AC Gains
  POS (DC coil Gain) PIT (DC coil Gain) YAW (DC coil Gain) Coil Output Gains (AC)
UL 1.1034 1 1 0.8554
UR 1.1034 1 -1 -0.9994
LL 0.8845 -1 1 -0.9809
LR 0.8845 -1 -1 1.1434

Note: The AC gains were measured by keeping output matrix to ideal values of 1s. When optimizing DC gains, the AC gains were uploaded in coil ouput gains.


MC3 Input matrix (Unchanged from previous values)
  UL UR LR LL SIDE
POS 0.28799 0.28374 0.21201 0.21626 -0.40599
PIT 2.65780 0.04096 -3.2910 -0.67420 -0.72122
YAW 0.60461 -2.7138 0.01363 3.33200 0.66647
SIDE 0.16601 0.19725 0.10520 0.07397 1.00000

MC3 Suspension Damping Gains
  Old gains New Gains
SUSPOS 200 500
SUSPIT 12 35
SUSYAW 8 12
  16073   Thu Apr 22 14:22:39 2021 gautamUpdateSUSSettings restored

The MC / WFS stability seemed off to me. Trending some channels at random, I saw that the MC3 PIT/YAW gains were restored mixed up (PIT was restored to YAW and vice versa) in the last day sometime - I wasn't sure what other settings are off so I did a global burtrestore from the last time I had the interferometer locked since those were settings that at least allow locking (I am not claiming they are optimal).

How are these settings being restored after the suspension optimization? If the burtrestore is randomly mixing up channels, seems like something we should be worried about and look into. I guess it'd also be helpful to make sure we are recording snapshots of all the channels we are changing - I'm not sure if the .req file gets updated automatically / if it really records every EPICS record. It'd be painful to lose some setting because it isn't recorded.


Unconnected to this work - the lights in the BS/PRM chamber were ON, so I turned them OFF. Also unconnected to this work, the summary pages job that updates the "live" plots every half hour seem to be dead again. There is a separate job whose real purpose is to wait for the data from EOD to be transferred to LDAS before filling in the last couple of hours of timeseries data, but seems to me like that is what is covering the entire day now.

  16078   Thu Apr 22 15:36:54 2021 AnchalUpdateSUSSettings restored

The mix up was my fault I think. I restored the channels manually instead of using burt restore. Your message suggests that we can set burt to start noticing channel changes at home point and create a .req file that can be used to restore later. We'll try to learn how to do that. Right now, we only know how to burt restore using the existing snapshots from the autoburt directory, but they touch more things than we work on, I think. Or can we just always burt restore it to morning time? If yes, what snapshot files should we use?

  16079   Thu Apr 22 17:04:17 2021 gautamUpdateSUSSettings restored

Indeed, you can make your own snapshot by specifying the channels to snap in a .req file. But what I meant was, we should confirm that all the channels that we modify are already in the existing snapshot files in the autoburt dir. If it isn't, we should consider adding it. I think the whole burt system needs some cleaning up - a single day of burt snapshots occupies ~400MB (!) of disk space, but I think we're recording a ton of channels which don't exist anymore. One day...

Quote:

Your message suggests that we can set burt to start noticing channel changes at home point and create a .req file that can be used to restore later. We'll try to learn how to do that. Right now, we only know how to burt restore using the existing snapshots from the autoburt directory, but they touch more things than we work on, I think. Or can we just always burt restore it to morning time? If yes, what snapshot files should we use?

  16086   Mon Apr 26 18:55:39 2021 Anchal, PacoUpdateSUSMC2 F2A Filters Tested

Today we tested the F2A filters created from the DC gain values listed in 16066.


Filters:

  • For a DC gain G_{DC} required for balancing the coil at DC and f_0 being the resonance frequency of the mode (POS in this case), we calculate the filter using:
    \frac{1 + i \frac{f_z}{f Q} - \frac{f_z^2}{f^2}}{1 + \frac{f_0}{f} - \frac{f_0^2}{f^2}}where f_z = f_0 \sqrt{G_{DC}}.
  • Attachment 1 shows the motivation for choosing the resonant frequency in the formula above. It makes gain at DC as G_{DC} while keeping AC gain as 1.
  • Attachment 2 shows the transfer functions of the filters uploaded.
  • Filters are named Eg2CtQ3, Eg2CtQ7 and Eg2CtQ10 for Q=3,7,10 filters respectively. (Named for Eigenmode Basis to Cartesian Basis conversion filters, aka F2A filters).

Testing procedure:

  • We uploaded the new input matrix listed in 16066.
  • We then uploaded the coil output gains (AC gains) that are also listed in 16066.
  • Then we reduced the C1:IOO-WFS_GAIN to 0.05 (by a factor of 20).
    • Rana asked us to test the WFS sensors' impulse response to observe a minimum 10s decay to ensure that the UGF of WFS control loops is at or below 0.1 Hz.
    • We were unable to have any effect on this decay actually. We tried setting offsets without tramps in multiple places but whenever we were able to excite this loop, it will always damp down in about 5-6s regardless of the value of C1:IOO-WFS_GAIN.
    • So we moved on.
  • Then, with MC locked we took reference data with no excitation or filters uploaded. (dotted curves)
  • We took cross spectral density from C1:IOO-MC_F to C1:IOO-MC_TRANS_PIT_IN1, C1:IOO-MC_TRANS_YAW_IN1, C1:IOO-WFS1_PIT_IN1, C1:IOO-WFS1_PIT_IN1, C1:IOO-WFS2_PIT_IN1, and C1:IOO-WFS2_PIT_IN1.
  • We were also looking at the power spectral density of these channels.
  • Then using awggui (after the fix we did as in 16085), we added noise in C1:SUS-MC2_LSC_EXC as uniform noise between 0.05 Hz to 3.5 Hz with amplitude of 100 and gain of 100.
  • We took a set of data without switching on the filters to have a comparison later. (Dash-dort curves)
  • We then took data after switching on the filters. (Solid curves)

Next:

  • Tomorrow we'll repeat this for MC1 and MC3 if we get a favourable grade in our work here.
  • Even if not, we'll jsut conclude the suspension optimization work tomorrow morning and get into main interferometer.
  16087   Tue Apr 27 10:05:28 2021 Anchal, PacoUpdateSUSMC1 and MC3 F2A Filters Tested

We extended the f2a filter implementation and diagnostics as summarized in 16086 to MC1 and MC3.


MC1

Attachment 1 shows the filters with Q=3, 7, 10. We diagnosed using Q=3.

Attachment 2 shows the test summary, exciting with broadband noise on the LSC_EXC and measuring the CSD to estimate the transfer functions.


MC3

Attachment 3 shows the filters with Q=3, 7, 10. We diagnosed using Q=3.

Attachment 4 shows the test summary, exciting with broadband noise on the LSC_EXC and measuring the CSD to estimate the transfer functions.


Our main observation (and difference) with respect to MC2 is the filters have relative success for the PIT cross-coupling and not so much for YAW. We already observed this when we tuned the DC output gains to compute the filters.

  16089   Wed Apr 28 10:56:10 2021 Anchal, PacoUpdateSUSIMC Filters diagnosed

Good morning!

We ran the f2a filter test for MC1, MC2, and MC3.


Filters

The new filters differ from previous versions by a adding non-unity Q factor for the pole pairs as well.

\frac{f^2 - i \frac{f_z}{Q}f + f_z^2}{f^2 - i \frac{f_0}{Q}f + f_0^2}
This in terms of zpk is: [ [zr + i zi, zr - i zi], [pr + i pi, pr - i pi], 1] where
z_r = -\frac{f_z}{2Q}, \quad z_i = f_z \sqrt{1 - \frac{1}{4Q^2}}, \quad p_r = -\frac{f_0}{2Q}, \quad p_i = f_0 \sqrt{1 - \frac{1}{4Q^2}}, \quad f_z = f_0 \sqrt{G_{DC}}

  • Attachment #1 shows the filters for MC1 evaluated for Q=3, 7,and 10.
  • Attachment #2 shows the filters for MC2 evaluated for Q=3, 7, and 10.
  • Attachment #3 shows the filters for MC3 evaluated for Q=3, 7, and 10.
  • Attachment #4 shows the bode plots generated by foton after uploading for Q=3 case.

We uploaded all these filters using foton, into the three last FM slots on the POS output gain coil.


Tests

We ran tests on all suspended optics using the following (nominal) procedure:

  1. Upload new input matrix
  2. Lower the C1:IOO-WFS_GAIN to 0.05.
  3. Upload AC coil balancing gains.
  4. Take ASD for the following channels:
    • C1:IOO-MC_TRANS_PIT_IN1
    • C1:IOO-MC_TRANS_YAW_IN1
    • C1:IOO-MC_WFS1_PIT_IN1
    • C1:IOO-MC_WFS1_YAW_IN1
    • C1:IOO-MC_WFS2_PIT_IN1
    • C1:IOO-MC_WFS2_YAW_IN1
  5. For the following combinations:
    • No excitation** + no filter
    • No excitation + filter
    • Excitation + no filter
    • Excitation + filter

** Excitation = 0.05 - 3.5 Hz uniform noise, 100 amplitude, 100 gain


Plots

  • Attachment 5-7 give the test results for MC1, MC2 and MC3.
  • In each pdf, the three pages show ASD of TRANS QPD, WFS1 and WFS2 channels' PIT and YAW, respectively.
  • Red/blue correspond to data taken while F2A filters were on. Pink/Cyan correspond to data taken with filters off.
  • Solid curves were taken with excitation ON and dashed curves were taken with excitation off.
  • We see good suppression of POS-> PIT coupling in MC2 and MC3. POS->YAw is minimally affected in all cases.
  • MC1 is clearly not doing good with the filters and probably needs readjustement. Something to do later in the future.
  16091   Wed Apr 28 17:09:11 2021 AnchalUpdateSUSTuned Suspension Parameters uploaded for long term behavior monitoring

I have uploaded all the new settings mentioned in 16066 and 16072. The settings were uploaded through a single script present at anchal/20210428_IMC_Tuned_Suspension/uploadNewConfigIMC.py. The settings can be reverted back to old settings through anchal/20210428_IMC_Tuned_Suspension/restoreOldConfigIMC.py. Both these scripts can be run only through python3 in donatella or allegra.


GPSTIME of new settings: 1303690144


New settings include:

  • New input matrices for MC1 and MC2.
  • New Output coil gains for AC balancing on all three optics.
  • Switching ON the FM8 filter modulae (Q=3 F2A filter) in POS column on output matrix of all optics.

We'll wait and watch the performance through summary pages and check back the performance on Monday.

  16094   Thu Apr 29 10:52:56 2021 AnchalUpdateSUSIMC Trans QPD and WFS loops step response test

In 16087 we mentioned that we were unable to do a step response test for WFS loop to get an estimate of their UGF. The primary issue there was that we were not putting the step at the right place. It should go into the actuator directly, in this case, on C1:SUS-MC2_PIT_COMM and C1:SUS-MC2_YAW_COMM. These channels directly set an offset in the control loop and we can see how the error signals first jump up and then decay back to zero. The 'half-time' of this decay would be the inverse of the estimated UGF of the loop. For this test, the overall WFS loops gain,  C1:IOO-WFS_GAIN was set to full value 1. This test is performed in the changed settings uploaded in 16091.

I did this test twice, once giving a step in PIT and once in YAW.

Attachment 1 is the striptool screenshot for when PIT was given a step up and then step down by 0.01.

  • Here we can see that the half-time is roughly 10s for TRANS_PIT and WFS1_PIT corresponding to roughly 0.1 Hz UGF.
  • Note that WFS2 channels were not disturbed significantly.
  • You can also notice that third most significant disturbance was to TRANS_YAW actually followed by WF1 YAW.

Attachment 2 is the striptool screenshot when YAW was given a step up and down by 0.01. Note the difference in x-scale in this plot.

  • Here, TRANS YAW got there greatest hit and it took it around 2 minutes to decay to half value. This gives UGF estimate of about 10 mHz!
  • Then, weirdly, TRANS PIT first went slowly up for about a minutes and then slowly came dome in a half time of 2 minutes again. Why was PIT signal so much disturbed by the YAW offset in the first place?
  • Next, WFS1 YAW can be seen decaying relatively fast with half-life of about 20s or so.
  • Nothing else was disturbed much.

  • So maybe we never needed to reduce WFS gain in our measurement in 16089 as the UGF everywhere were already very low.
  • What other interesting things can we infer from this?
  • Should I sometime repeat this test with steps given to MC1 or MC3 optics?
  16102   Thu Apr 29 18:53:33 2021 AnchalUpdateSUSIMC Suspension Damping Gains Test

With the input matrix, coil ouput gains and F2A filters loaded as in 16091, I tested the suspension loops' step response to offsets in LSC, ASCPIT and ASCYAW channels, before and after applying the "new damping gains" mentioned in 16066 and 16072. If these look better, we should upload the new (higher) damping gains as well. This was not done in 16091.


Note that in the plots, I have added offsets in the different channels to plot them together, hence the units are "au".

  16110   Mon May 3 16:24:14 2021 AnchalUpdateSUSIMC Suspension Damping Gains Test Repeated with IMC unlocked

We repeated the same test with IMC unlocked. We had found these gains when IMC was unlocked and their characterization needs to be done with no light in the cavity. attached are the results. Everything else is same as before.

Quote:

With the input matrix, coil ouput gains and F2A filters loaded as in 16091, I tested the suspension loops' step response to offsets in LSC, ASCPIT and ASCYAW channels, before and after applying the "new damping gains" mentioned in 16066 and 16072. If these look better, we should upload the new (higher) damping gains as well. This was not done in 16091.


Note that in the plots, I have added offsets in the different channels to plot them together, hence the units are "au".


Edit Tue May 4 14:43:48 2021 :

  • Adding zoomed in plots to show first 25s after the step.
  • MC1:
    • Our improvements by new gains are only modest.
    • This optic needs a more careful coil balancing first.
    • Still the ring time is reduced to about 5s for all step responses as opposed to 10s at old gains.
  • MC2:
    • The first page of MC2 might be bit misleading. We have not changed the damping gain for SUSPOS channel, so the longer ringing is probably just an artifact of somthing else. We didn't retake data.
    • In PIT and YAW where we increased the gain by a factor of 3, we see a reduction in ringing lifetime by about half.
  • MC3:
    • We saw the most optimistic improvement on this optic.
    • The gains were unusually low in this optic, not sure why.
    • By increasing SUSPOS gain from 200 to 500, we saw a reduction of ringing halftime from 7-8s to about 2s. Improvements are seen in other DOFs as well.
    • You can notice rightaway that YAW of MC3 keeps oscillating near resonance (about 1 Hz). Maybe more careful feedback shaping is required here.
    • In SUSPIT, we increased gain from 12 to 35 and saw a good reduction in both ringing time and initial amplitude of ringing.
    • In SUSYAW, we only increased the gain to 12 from 8, which still helped a lot in reducing big ringing step response to below 5s from about 12s.

Overall, I would recommend setting the new gains in the suspension loops as well to observe long term effects too.

  16120   Wed May 5 09:04:47 2021 AnchalUpdateSUSNew IMC Suspension Damping Gains uploaded for long term testing

We have uploaded the new damping gains on all the suspensions of IMC. This completes changing all the configuration to as mentioned in 16066 and 16072. The old setting can be restored by running python3 /users/anchal/20210505_IMC_Tuned_SUS_with_Gains/restoreOldConfigIMC.py from allegra or donatella.

GPSTIME: 1304265872

UTC May 05, 2021 16:04:14 UTC
Central May 05, 2021 11:04:14 CDT
Pacific May 05, 2021 09:04:14 PDT

 

  16133   Wed May 12 11:45:13 2021 Anchal, PacoSummarySUSNew IMC Settings are miserable

We picked a few parameters from 40m summary page and plotted them to see the effect of new settings. On April 4th, old settings were present. On April 28th (16091), new input matrices and F2A filters were uploaded but suspension gains remained the same. On May 5th (16120), we uploaded new (higher) suspension gains. We chose Sundays on UTC so that it lies on weekends for us. Most probably nobody entered 40m and it was calmer in the institute as well.

  • On MC_F spectrum, we see that that noise decreased in 0.3-0.7 Hz but there is more noise from 1-1.5 Hz.
  • On MC_TRANS_QPD, we see that both TRANS PIT and YAW signals were almost twice as noisy.
  • On MC_REFL_DC too, we see that the noise during the locked state seems to be higher in the new configuration.

We can download data and plot comparisons ourselves and maybe calculate the spectrums of MC_TRANS_PIT/YAW and MC_REFL_DC when IMC was locked. But we want to know if anyone has better ways of characterizing the settings that we should know of before we get into this large data handling which might be time-consuming. From this preliminary 40m summary page plots, maybe it is already clear that we should go back to old settings. Awaiting orders.

 

  16135   Wed May 12 14:23:20 2021 JordanUpdateSUSMass Properties of SOS Assembly with 3"->2" Optic sleeve, in SI units
  16136   Wed May 12 16:53:59 2021 KojiUpdateSUSMass Properties of SOS Assembly with 3"->2" Optic sleeve, in SI units

No, this is the property of the suspension assembly. The mass says 10kg

Could you do the same for the testmass assembly (only the suspended part)? The units are good, but I expect that the values will be small. I want to keep at least three significant digits.

  16137   Wed May 12 17:06:52 2021 JordanUpdateSUSMass Properties of SOS Assembly with 3"->2" Optic sleeve, in SI units

Here are the mass properties for the only the test mass assembly (optic, 3" ring, and wire block). (Updated with g*mm^2)

Quote:

No, this is the property of the suspension assembly. The mass says 10kg

Could you do the same for the testmass assembly (only the suspended part)? The units are good, but I expect that the values will be small. I want to keep at least three significant digits.

 

  16138   Thu May 13 11:55:04 2021 Anchal, PacoUpdateSUSMC1 suspension misbehaving

We came in the morning with the following scene on the zita monitor:

The MC1 watchdog was tripped and seemed like IMC struggled all night with misconfigured WFS offsets. After restoring the MC1 WD, clearing the WFS offsets, and seeing the suspension damp, the MC caught lock. It wasn't long before the MC unlocked, and the MC1 WD tripped again.

We tried few things, not sure what order we tried them in:

  • Letting suspension loops damp without the WFS switched on.
  • Letting suspension loops damp with PSL shutter closed.
  • Restoring old settings of MC suspension.
  • Doing burt restore with command:
    burtwb -f /opt/rtcds/caltech/c1/burt/autoburt/snapshots/2021/May/12/08:19/c1mcsepics.snap -l /tmp/controls_1210513_083437_0.write.log -o /tmp/controls_1210513_083437_0.nowrite.snap -v <

Nothing worked. We kept seeing that ULPD var on MC1 keeps showing kicks every few minutes which jolts the suspension loops. So we decided to record some data with PSL shutter closed and just suspension loops on. Then we switched off the loops and recorded some data with freely swinging optic. Even when optic was freely swinging, we could see impulses in the MC1 OSEM UL PD var which were completely uncorrelated with any seismic activity. Infact, last night was one fo teh calmer nights seismically speaking. See attachment 2 for the time series of OSEM PD variance. Red region is when the coil outputs were disabled.

Inference:

  • We think something is wrong with the UL OSEM of MC1.
  • It seems to show false spikes of motion when there is no such spike present in any other OSEM PD or the seismic data itself.
  • Currently, this is still the case. We sometimes get 10-20 min of "Good behavior" when everything works.
  • But then the impulses start occuring again and overwhelmes the suspension loops and WFS loops.
  • Note, that other optic in IMC behaved perfectly normally throughout this time.
  • In the past, it seems like satellite box has been the culprit for such glitches.
  • We should look into debugging this as ifo is at standstill because of this issue.
  • Earlier, Gautum would post Vmon signals of coil outputs only to show the glitches. We wanted to see if switching off the loops help, so we recorded OSEM PD this time.
  • In hindsight, we should probably look at the OSEM sensor outputs directly too rather than looking at the variance data only. I can do this if people are interested in looking at that too.
  • We've disabled the coil ouputs in MC1 and PSL shutter is off.

Edit Thu May 13 14:47:25 2021 :

Added OSEM Sensor timeseries data on the plots as well. The UL OSEM sensor data is the only channel which is jumping hapazardly (even during free swinging time) and varying by +/- 30. Other sensors only show some noise around a stable position as should be the case for a freely suspended optic.

  16139   Thu May 13 19:38:54 2021 AnchalUpdateSUSMC1 Satellite Amplifier Debugged

[Anchal Koji]

Koji and I did a few tests with an OSEM emulator on the satellite amplifier box used for MC1 which is housed on 1X4. This sat box unit is S2100029 D1002812 that was recently characterized by me 15803. We found that the differential output driver chip AD8672ARZ U2A section for the UL PD was not working properly and had a fluctuating offset at no input current from the PD. This was the cause of the ordeal of the morning. The chip was replaced with a new one from our stock. The preliminary test with the OSEM emulator showed that the channel has the correct DC value.

In further testing of the board, we found that the channel 8 LED driver was not working properly. Although this channel is never used in our current cable convention, it might be used later in the future. In the quest of debugging the issue there, we replaced AD8672ARZ at U1 on channel 8. This did not solve the issue. So we opened the front panel and as we flipped the board, we found that the solder blob shorted the legs of the transistor Q1 2N3904. This was replaced and the test with the LED out and GND shorted indicated that the channel is now properly providing a constant current of 35mA (5V at the monitor out).


After the debugging, the UL channel became the least noisy among the OSEM channels! Mode cleaner was able to lock and maintain it.

We should redo the MC1 input matrix optimization and the coil balancing afterward as we did everything based on the noisy UL OSEM values.

  16143   Sat May 15 14:54:24 2021 gautamUpdateSUSIMC settings reverted

I want to work on the IFO this weekend, so I reverted the IMC suspension settings just now to what I know work (until the new settings are shown quantitatively to be superior). There isn't any instruction here on how to upload the new settings, so after my work, I will just restore from a burt-snapshot from before I changed settings.

In the process, I found something odd in the MC2 coil output filter banks. Attachment #1 shows what it it is today. This weird undetermined state of FM9 isn't great - I guess this flew under the radar because there isn't really any POS actuation on MC2. Where did the gain1 filter I installed go? Some foton filter file corruption? Eventually, we should migrate FM7,FM8-->FM9,FM10 but this isn't on my scope of things to do for today so I am just putting the gain1 filter back so as to have a clean FM9 switched on.

Quote:

The old setting can be restored by running python3 /users/anchal/20210505_IMC_Tuned_SUS_with_Gains/restoreOldConfigIMC.py from allegra or donatella.

 

I wrote the values from the c1mcs burt snapshot from ~1400 Saturday May 15, at ~1600 Sunday May 16. I believe this undoes all my changes to the IMC suspension settings.

  16146   Wed May 19 18:29:41 2021 KojiUpdateSUSMass Properties of SOS Assembly with 3"->2" Optic sleeve, in SI units

Calculation for the SOS POS/PIT/YAW resonant frequencies

- Nominal height gap between the CoM and the wire clamping point is 0.9mm (cf T970135)

- To have the similar res freq for the optic with the 3" metal sleeve is 1.0~1.1mm.
As the previous elog does not specify this number for the current configuration, we need to asses this value and the make the adjustment of the CoM height.

  16147   Thu May 20 10:35:57 2021 AnchalUpdateSUSIMC settings reverted

For future reference, the new settings can be upoaded from a script in the same directory. Run python /users/anchal/20210505_IMC_Tuned_SUS_with_Gains/uploadNewConfigIMC.py from allegra.

Quote:

There isn't any instruction here on how to upload the new settings

  16149   Fri May 21 00:05:45 2021 KojiUpdateSUSNew electronics: Sat Amp / Coil Drivers

11 new Satellite Amps were picked up from Downs. 7 more are coming from there. I have one spare unit I made. 1 sat amp has already been used at MC1.

We had 8 HAM-A coil drivers delivered from the assembling company. We also have two coil drivers delivered from Downs (Anchal tested)

  16157   Mon May 24 19:14:15 2021 Anchal, PacoSummarySUSMC1 Free Swing Test set to trigger

We've set a free swing test to trigger at 3:30 am tomorrow for MC1. The script for tests is running on tmux session named 'freeSwingMC1' on rossa. The script will run for about 4.5 hrs and we'll correct the input matrix tomorrow from the results. If anyone wants to work during this time (3:30 am to 8:00 am), you can just kill the script by killing tmux session on rossa. ssh into rossa and type tmux kill-session -t freeSwingMC1.

Quote:
 

We should redo the MC1 input matrix optimization and the coil balancing afterward as we did everything based on the noisy UL OSEM values.

 

  16159   Tue May 25 10:22:16 2021 Anchal, PacoSummarySUSMC1 new input matrix calculated and uploaded

The test was succesful and brought back the IMC to lock point at the end.

We calculated new input matrix using same code in scripts/SUS/InMatCalc/sus_diagonalization.py . Attachment 1 shows the results.

The calculations are present in scripts/SUS/InMatCalc/MC1.


We uploaded the new MC1 input matrix at:

Unix Time = 1621963200

UTC May 25, 2021 17:20:00 UTC
Central May 25, 2021 12:20:00 CDT
Pacific May 25, 2021 10:20:00 PDT

GPS Time = 1305998418

This was done by running python scripts/SUS/general/20210525_NewMC1Settings/uploadNewConfigIMC.py on allegra. Old IMC settings (before Paco and I started workin on 40m) can be restored by running python scripts/SUS/general/20210525_NewMC1Settings/restoreOldConfigIMC.py on allegra.

Everything looks as stable as before. We'll look into long term trends in a week to see if this helped at all.

  16165   Thu May 27 14:11:15 2021 JordanUpdateSUSCoM to Clamping Point Measurement for 3" Adapter Ring

The current vertical distance between the CoM and the wire clamping point on the 3" Ring assembly is 0.33mm. That is the CoM is .33 mm below the clamping point of the wire. I took the clamping point to be the top edge of the wire clamp piece. see the below attachments.

I am now modifying the dumbell mechanism at the bottom of the ring to move the CoM to the target distance of 1.1mm.

  16169   Tue Jun 1 14:26:23 2021 JordanUpdateSUSCoM to Clamping Point Measurement for 3" Adapter Ring

After changing the material of the Balance Mass from 6061 Al to 304 Steel, and changing the thickness to 0.21" from 0.25". The CoM is now 1.11mm below the clamping point.

Koji expected a mass change of ~ 4g to move the mass to 1.1mm. The 6061 mass weighed ~1.31g and the 304 mass weighs 4.1g.

A potential issue with this is the screw used the adjust the position of these balance masses, threads through both the aluminum ring and this now 304 steel mass. A non silver plated screw could cold weld at the mass, but a silver plated screw will gall in the aluminum threads.

Quote:

The current vertical distance between the CoM and the wire clamping point on the 3" Ring assembly is 0.33mm. That is the CoM is .33 mm below the clamping point of the wire. I took the clamping point to be the top edge of the wire clamp piece. see the below attachments.

I am now modifying the dumbell mechanism at the bottom of the ring to move the CoM to the target distance of 1.1mm.

 

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