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| ==== Past week report ==== | ==== Report for the week 6/3 ==== ===== SRM Inertial Damping and Residual Motion Stuff ===== * See Klog [[http://klog.icrr.u-tokyo.ac.jp/osl/?r=9064|9064]] * SRM IP L and T is blended at ~110 mHz (partially optimized by gradient descent, stopped after 10 iterations, then manually adjusted.) while IP Y is blended at 260 mHz (Lucia's old filter). The stability test was carried over the past weekend with inertial damping and all other stages on. The system seems stable. * To study to performance of the inertial damping, I improvised an OL windshield for SRM. * Another round of diagonalization was carried just because we have better sensitivity. * With IP LVDT damping and other controls on, the residual motion is as follows [[http://klog.icrr.u-tokyo.ac.jp/osl/?r=9086|9086]]: RMS Displacement: || || Requirement || Result || || L || 0.4 µm || 0.1076 µm || || P || 1 µrad || 0.0569 µrad || || Y || 1 µrad || 0.0598 µrad || RMS Velocity: || || Requirement || Result || || L || 0.5 µm || 0.1014 µm/s || || P || / || 0.2165 µrad/s || || Y || / || 0.1776 µrad/s || * I measured the residual motion with inertial damping, inertial damping without LVDT DC, normal damping without LVDT DC. Results are pretty similar. * I modified the optimization algorithm to allow fine learning. The cost plateaued after ~300 iterations and the blending frequency was at 78.6 mHz. I tried implementing this blending filter but the system went unstable. ===== SR3 Inertial Damping ===== * The calibration, diagonalization for IP geophones was done. * I measured and fit noise floor for LVDTs and geophones. * I found that the IP geophones have a much higher noise level than those from SRM. (1 order of magnitude higher, see [[http://klog.icrr.u-tokyo.ac.jp/osl/?r=9088|9088]]) * This explains why the optimization result of the blending filter converges much quicker than that of SRM, because the geophone noise level limits the blending frequency to be at ~ 130 mHz. * However, when the system went unstable when the blending filter was implemented. I should try a higher blending frequency or manually adjusting the blending filter to have a proper shape. |
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| * Help commisioning. * Somehow design better cost functions which could help limiting the blending frequency and changing the shape of the blending filter effectively. * Inertial damping and OL windshield for BS and (SR3, if haven't done already). * Type B Operation Manual. * A more pleasant VIS Status Monitor. |
Agenda/Minutes of the VIS Meeting on 2019/6/7
2019/6/7 13:30 -
Participants:
Progress report
Schedule
Site work schedule: [[|XLSX]]
Type-A (Takahashi)
Past week report
Plan for coming weeks
Type B (Mark)
Report for the week 6/3
SRM Inertial Damping and Residual Motion Stuff
See Klog 9064
- SRM IP L and T is blended at ~110 mHz (partially optimized by gradient descent, stopped after 10 iterations, then manually adjusted.) while IP Y is blended at 260 mHz (Lucia's old filter). The stability test was carried over the past weekend with inertial damping and all other stages on. The system seems stable.
- To study to performance of the inertial damping, I improvised an OL windshield for SRM.
- Another round of diagonalization was carried just because we have better sensitivity.
With IP LVDT damping and other controls on, the residual motion is as follows 9086:
RMS Displacement:
|
Requirement |
Result |
L |
0.4 µm |
0.1076 µm |
P |
1 µrad |
0.0569 µrad |
Y |
1 µrad |
0.0598 µrad |
RMS Velocity:
|
Requirement |
Result |
L |
0.5 µm |
0.1014 µm/s |
P |
/ |
0.2165 µrad/s |
Y |
/ |
0.1776 µrad/s |
- I measured the residual motion with inertial damping, inertial damping without LVDT DC, normal damping without LVDT DC. Results are pretty similar.
- I modified the optimization algorithm to allow fine learning. The cost plateaued after ~300 iterations and the blending frequency was at 78.6 mHz. I tried implementing this blending filter but the system went unstable.
SR3 Inertial Damping
- The calibration, diagonalization for IP geophones was done.
- I measured and fit noise floor for LVDTs and geophones.
I found that the IP geophones have a much higher noise level than those from SRM. (1 order of magnitude higher, see 9088)
- This explains why the optimization result of the blending filter converges much quicker than that of SRM, because the geophone noise level limits the blending frequency to be at ~ 130 mHz.
- However, when the system went unstable when the blending filter was implemented. I should try a higher blending frequency or manually adjusting the blending filter to have a proper shape.
Plan for coming weeks
- Help commisioning.
- Somehow design better cost functions which could help limiting the blending frequency and changing the shape of the blending filter effectively.
- Inertial damping and OL windshield for BS and (SR3, if haven't done already).
- Type B Operation Manual.
- A more pleasant VIS Status Monitor.
Type-Bp (Shoda)
Past week report
Plan for coming weeks
OMMT & OSTM
Past week report
Plan for coming weeks
VIS electronics (Tanaka)
Past week report
Plan for coming weeks
Other site works
Safety
- Incidents:
- Foreseen risks
- Type-A:
- Type-B:
Discussion
- Engineering run on 6/8
Travel Plans
- Travel (Week of 6/10):
- Takahashi:
- Sato:
- Mark:
- Hirata:
- Shoda:
- Fujii:
- Tanioka:
- Tanaka:
- Terrence:
- Travel (Week of 6/17):
- Takahashi:
- Sato:
- Mark:
- Hirata:
- Shoda:
- Fujii:
- Tanioka:
- Tanaka:
- Terrence:
Next meeting
On 2019/6/14(Fri)