nass-micro-station-measurements/slip-ring-test/index.org

Measurements On the Slip-Ring

• Effect of the Slip-Ring on the signal
  • Experimental Setup
  • Load data
  • Analysis - Time Domain
  • Analysis - Frequency Domain
  • Conclusion
• Effect of the rotation of the Slip-Ring
  • Measurement Description
  • Load data
  • Analysis
  • Conclusion
• Measure of the noise induced by the Slip-Ring
  • Measurement Description
  • Load data
  • Time Domain
  • Frequency Domain
  • Conclusion
• Measure of the noise induced by the slip ring when using a geophone
  • First Measurement without LPF
    • Measurement Description
    • Load data
    • Time Domain
    • Frequency Domain
    • Conclusion
  • Measurement using an oscilloscope
    • Measurement Setup
    • Observations
    • Conclusion
  • New measurements with a LPF before the Voltage Amplifiers
    • Setup description
    • Load data
    • Time Domain
    • Frequency Domain
    • Comparison of with and without LPF
    • Conclusion

Effect of the Slip-Ring on the signal

<<sec:meas_slip_ring_geophone>>

All the files (data and Matlab scripts) are accessible here.

Experimental Setup

Two measurements are made with the control systems of all the stages turned OFF.

One geophone is located on the marble while the other is located at the sample location (figure fig:setup_slipring).

Experimental Setup

The two measurements are:

Measurement File	Description
meas_018.mat	Signal from the top geophone does not goes through the Slip-ring
meas_019.mat	Signal goes through the Slip-ring (as shown on the figure above)

Each of the measurement mat file contains one data array with 3 columns:

Column number	Description
1	Geophone - Marble
2	Geophone - Sample
3	Time

Load data

We load the data of the z axis of two geophones.

  d8 = load('mat/data_018.mat', 'data'); d8 = d8.data;
  d9 = load('mat/data_019.mat', 'data'); d9 = d9.data;

Analysis - Time Domain

First, we compare the time domain signals for the two experiments (figure fig:slipring_time).

  figure;
  hold on;
  plot(d9(:, 3), d9(:, 2), 'DisplayName', 'Slip-Ring');
  plot(d8(:, 3), d8(:, 2), 'DisplayName', 'Wire');
  hold off;
  xlabel('Time [s]'); ylabel('Voltage [V]');
  xlim([0, 50]);
  legend('location', 'northeast');

  <<plt-matlab>>

Effect of the Slip-Ring on the measured signal - Time domain

Analysis - Frequency Domain

We then compute the Power Spectral Density of the two signals and we compare them (figure fig:slipring_asd).

  dt = d8(2, 3) - d8(1, 3);
  Fs = 1/dt;

  win = hanning(ceil(1*Fs));

  [pxx8, f] = pwelch(d8(:, 2), win, [], [], Fs);
  [pxx9, ~] = pwelch(d9(:, 2), win, [], [], Fs);

  figure;
  hold on;
  plot(f, sqrt(pxx9), 'DisplayName', 'Slip-Ring');
  plot(f, sqrt(pxx8), 'DisplayName', 'Wire');
  hold off;
  set(gca, 'xscale', 'log');
  set(gca, 'yscale', 'log');
  xlabel('Frequency [Hz]'); ylabel('Amplitude Spectral Density $\left[\frac{V}{\sqrt{Hz}}\right]$')
  xlim([1, 500]);
  legend('Location', 'southwest');

  <<plt-matlab>>

Effect of the Slip-Ring on the measured signal - Frequency domain

Conclusion

• Connecting the geophone through the Slip-Ring seems to induce a lot of noise.

Remaining questions to answer:

• Why is there a sharp peak at 300Hz?
• Why the use of the Slip-Ring does induce a noise?
• Can the capacitive/inductive properties of the wires in the Slip-ring does not play well with the geophone? (resonant RLC circuit)

Effect of the rotation of the Slip-Ring

<<sec:meas_effect_sr>>

All the files (data and Matlab scripts) are accessible here.

Measurement Description

Random Signal is generated by one DAC of the SpeedGoat.

The signal going out of the DAC is split into two:

• one BNC cable is directly connected to one ADC of the SpeedGoat
• one BNC cable goes two times in the Slip-Ring (from bottom to top and then from top to bottom) and then is connected to one ADC of the SpeedGoat

Two measurements are done.

Data File	Description
mat/data_001.mat	Slip-ring not turning
mat/data_002.mat	Slip-ring turning

For each measurement, the measured signals are:

Data File	Description
t	Time vector
x1	Direct signal
x2	Signal going through the Slip-Ring

The goal is to determine is the signal is altered when the spindle is rotating.

Here, the rotation speed of the Slip-Ring is set to 1rpm.

Load data

We load the data of the z axis of two geophones.

  sr_off = load('mat/data_001.mat', 't', 'x1', 'x2');
  sr_on  = load('mat/data_002.mat', 't', 'x1', 'x2');

Analysis

Let's first look at the signal produced by the DAC (figure fig:random_signal).

  figure;
  hold on;
  plot(sr_on.t,  sr_on.x1);
  hold off;
  xlabel('Time [s]'); ylabel('Voltage [V]');
  xlim([0 10]);

  <<plt-matlab>>

Random signal produced by the DAC

We now look at the difference between the signal directly measured by the ADC and the signal that goes through the slip-ring (figure fig:slipring_comp_signals).

  figure;
  hold on;
  plot(sr_on.t,  sr_on.x1  -  sr_on.x2,  'DisplayName', 'Slip-Ring - $\omega = 1rpm$');
  plot(sr_off.t, sr_off.x1 - sr_off.x2,'DisplayName', 'Slip-Ring off');
  hold off;
  xlabel('Time [s]'); ylabel('Voltage [V]');
  xlim([0 10]);
  legend('Location', 'northeast');

  <<plt-matlab>>

Alteration of the signal when the slip-ring is turning

  dt = sr_on.t(2) - sr_on.t(1);
  Fs = 1/dt; % [Hz]

  win = hanning(ceil(1*Fs));

  [pxx_on,  f] = pwelch(sr_on.x1  - sr_on.x2,  win, [], [], Fs);
  [pxx_off, ~] = pwelch(sr_off.x1 - sr_off.x2, win, [], [], Fs);

  <<plt-matlab>>

ASD of the measured noise

Conclusion

Remaining questions:

• Should the measurement be redone using voltage amplifiers?
• Use higher rotation speed and measure for longer periods (to have multiple revolutions) ?

Measure of the noise induced by the Slip-Ring

<<sec:meas_slip_ring>>

All the files (data and Matlab scripts) are accessible here.

Measurement Description

Goal:

• Determine the noise induced by the slip-ring

Setup:

• 0V is generated by the DAC of the Speedgoat
• Using a T, one part goes directly to the ADC
• The other part goes to the slip-ring 2 times and then to the ADC
• The parameters of the Voltage Amplifier are: 80dB, AC, 1kHz
• Every stage of the station is OFF

First column: Direct measure Second column: Slip-ring measure

Measurements:

• data_008: Slip-Ring OFF
• data_009: Slip-Ring ON
• data_010: Slip-Ring ON and omega=6rpm
• data_011: Slip-Ring ON and omega=60rpm

Slip-Ring rotating at 6rpm

Slip-Ring rotating at 60rpm

Load data

We load the data of the z axis of two geophones.

  sr_off = load('mat/data_008.mat', 'data'); sr_off = sr_off.data;
  sr_on  = load('mat/data_009.mat', 'data'); sr_on  = sr_on.data;
  sr_6r  = load('mat/data_010.mat', 'data'); sr_6r  = sr_6r.data;
  sr_60r = load('mat/data_011.mat', 'data'); sr_60r = sr_60r.data;

Time Domain

We plot the time domain data for the direct measurement (figure fig:sr_direct_time) and for the signal going through the slip-ring (figure fig:sr_slipring_time);

  <<plt-matlab>>

Direct measurement

  <<plt-matlab>>

Measurement of the signal going through the Slip-Ring

Frequency Domain

We first compute some parameters that will be used for the PSD computation.

  dt = sr_off(2, 3)-sr_off(1, 3);

  Fs = 1/dt; % [Hz]

  win = hanning(ceil(10*Fs));

Then we compute the Power Spectral Density using pwelch function.

  [pxdir, f] = pwelch(sr_off(:, 1), win, [], [], Fs);
  [pxoff, ~] = pwelch(sr_off(:, 2), win, [], [], Fs);
  [pxon,  ~] = pwelch(sr_on(:, 2),  win, [], [], Fs);
  [px6r,  ~] = pwelch(sr_6r(:, 2),  win, [], [], Fs);
  [px60r, ~] = pwelch(sr_60r(:, 2), win, [], [], Fs);

And we plot the ASD of the measured signals (figure fig:sr_psd_compare);

  figure;
  hold on;
  plot(f, sqrt(pxoff), 'DisplayName', 'OFF');
  plot(f, sqrt(pxon),  'DisplayName', 'ON');
  plot(f, sqrt(px6r),  'DisplayName', '6rpm');
  plot(f, sqrt(px60r), 'DisplayName', '60rpm');
  plot(f, sqrt(pxdir), 'k-', 'DisplayName', 'Direct');
  hold off;
  set(gca, 'xscale', 'log');
  set(gca, 'yscale', 'log');
  xlabel('Frequency [Hz]'); ylabel('ASD of the measured Voltage $\left[\frac{V}{\sqrt{Hz}}\right]$')
  legend('Location', 'northeast');
  xlim([0.1, 500]);

  <<plt-matlab>>

Comparison of the ASD of the measured signals when the slip-ring is ON, OFF and turning

Conclusion

Questions:

• Why is there some sharp peaks? Can this be due to aliasing?
• It is possible that the amplifiers were saturating during the measurements => should redo the measurements with a low pass filter before the voltage amplifier

Measure of the noise induced by the slip ring when using a geophone

<<sec:meas_sr_geophone>>

All the files (data and Matlab scripts) are accessible here.

First Measurement without LPF

Measurement Description

Goal:

• Determine if the noise induced by the slip-ring is a limiting factor when measuring the signal coming from a geophone

Setup:

• The geophone is located at the sample location

• The two Voltage amplifiers have the same following settings:

  • AC
  • 60dB
  • 1kHz

• The signal from the geophone is split into two using a T-BNC:

  • One part goes directly to the voltage amplifier and then to the ADC.
  • The other part goes to the slip-ring=>voltage amplifier=>ADC.

First column: Direct measure Second column: Slip-ring measure

Measurements:

• data_012: Slip-Ring OFF
• data_013: Slip-Ring ON

Load data

We load the data of the z axis of two geophones.

  sr_off = load('mat/data_012.mat', 'data'); sr_off = sr_off.data;
  sr_on  = load('mat/data_013.mat', 'data'); sr_on  = sr_on.data;

Time Domain

We compare the signal when the Slip-Ring is OFF (figure fig:sr_geophone_time_off) and when it is ON (figure fig:sr_geophone_time_on).

  <<plt-matlab>>

Comparison of the time domain signals when the slip-ring is OFF

  <<plt-matlab>>

Comparison of the time domain signals when the slip-ring is ON

Frequency Domain

We first compute some parameters that will be used for the PSD computation.

  dt = sr_off(2, 3)-sr_off(1, 3);

  Fs = 1/dt; % [Hz]

  win = hanning(ceil(10*Fs));

Then we compute the Power Spectral Density using pwelch function.

  % Direct measure
  [pxdoff, ~] = pwelch(sr_off(:, 1), win, [], [], Fs);
  [pxdon,  ~] = pwelch(sr_on(:, 1),  win, [], [], Fs);

  % Slip-Ring measure
  [pxsroff, f] = pwelch(sr_off(:, 2), win, [], [], Fs);
  [pxsron,  ~] = pwelch(sr_on(:, 2),  win, [], [], Fs);

Finally, we compare the Amplitude Spectral Density of the signals (figure fig:sr_geophone_asd);

  figure;
  hold on;
  plot(f, sqrt(pxdoff), 'DisplayName', 'Direct - OFF');
  plot(f, sqrt(pxsroff), 'DisplayName', 'Slip-Ring - OFF');
  plot(f, sqrt(pxdon),  'DisplayName', 'Direct - ON');
  plot(f, sqrt(pxsron),  'DisplayName', 'Slip-Ring - ON');
  hold off;
  set(gca, 'xscale', 'log');
  set(gca, 'yscale', 'log');
  xlabel('Frequency [Hz]'); ylabel('ASD of the measured Voltage $\left[\frac{V}{\sqrt{Hz}}\right]$')
  legend('Location', 'northeast');
  xlim([0.1, 500]);

  <<plt-matlab>>

Comparison of the Amplitude Spectral Sensity

  <<plt-matlab>>

Comparison of the Amplitude Spectral Sensity - Zoom

Conclusion

• The fact that the Slip-Ring is turned ON adds some noise to the signal.
• The signal going through the Slip-Ring is less noisy than the one going directly to the ADC.
• This could be due to less good electromagnetic isolation.

Questions:

• Can the sharp peak on figure fig:sr_geophone_asd_zoom be due to the Aliasing?

Measurement using an oscilloscope

Measurement Setup

Know we are measuring the same signals but using an oscilloscope instead of the Speedgoat ADC.

Observations

Then the Slip-Ring is ON (figure fig:oscilloscope_sr_on), we observe a signal at 40kHz with a peak-to-peak amplitude of 200mV for the direct measure and 100mV for the signal going through the Slip-Ring.

Then the Slip-Ring is OFF, we don't observe this 40kHz anymore (figure fig:oscilloscope_sr_off).

Signals measured by the oscilloscope - Slip-Ring ON - Yellow: Direct measure - Blue: Through Slip-Ring

Signals measured by the oscilloscope - Slip-Ring OFF - Yellow: Direct measure - Blue: Through Slip-Ring

Conclusion

• By looking at the signals using an oscilloscope, there is a lot of high frequency noise when turning on the Slip-Ring
• This can eventually saturate the voltage amplifiers (seen by a led indicating saturation)
• The choice is to add a Low pass filter before the voltage amplifiers to not saturate them and filter the noise.

New measurements with a LPF before the Voltage Amplifiers

Setup description

A first order low pass filter is added before the Voltage Amplifiers with the following values:

\begin{aligned} R &= 1k\Omega \\ C &= 1\mu F \end{aligned}

And we have a cut-off frequency of $f_c = \frac{1}{RC} = 160Hz$.

We are measuring the signal from a geophone put on the marble with and without the added LPF:

• with the slip ring OFF: mat/data_016.mat
• with the slip ring ON: mat/data_017.mat

Load data

We load the data of the z axis of two geophones.

  sr_lpf_off = load('mat/data_016.mat', 'data'); sr_lpf_off = sr_lpf_off.data;
  sr_lpf_on  = load('mat/data_017.mat', 'data'); sr_lpf_on  = sr_lpf_on.data;

Time Domain

We compare the signal when the Slip-Ring is OFF (figure fig:sr_lpf_geophone_time_off) and when it is ON (figure fig:sr_lpf_geophone_time_on).

  <<plt-matlab>>

Comparison of the time domain signals when the slip-ring is OFF

  <<plt-matlab>>

Comparison of the time domain signals when the slip-ring is ON

Frequency Domain

We first compute some parameters that will be used for the PSD computation.

  dt = sr_lpf_off(2, 3)-sr_lpf_off(1, 3);

  Fs = 1/dt; % [Hz]

  win = hanning(ceil(10*Fs));

Then we compute the Power Spectral Density using pwelch function.

  % Direct measure
  [pxd_lpf_off, ~] = pwelch(sr_lpf_off(:, 1), win, [], [], Fs);
  [pxd_lpf_on,  ~] = pwelch(sr_lpf_on(:, 1),  win, [], [], Fs);

  % Slip-Ring measure
  [pxsr_lpf_off, f] = pwelch(sr_lpf_off(:, 2), win, [], [], Fs);
  [pxsr_lpf_on,  ~] = pwelch(sr_lpf_on(:, 2),  win, [], [], Fs);

Finally, we compare the Amplitude Spectral Density of the signals (figure fig:sr_lpf_geophone_asd);

  figure;
  hold on;
  plot(f, sqrt(pxd_lpf_off), 'DisplayName', 'Direct - OFF');
  plot(f, sqrt(pxsr_lpf_off), 'DisplayName', 'Slip-Ring - OFF');
  plot(f, sqrt(pxd_lpf_on),  'DisplayName', 'Direct - ON');
  plot(f, sqrt(pxsr_lpf_on),  'DisplayName', 'Slip-Ring - ON');
  hold off;
  set(gca, 'xscale', 'log');
  set(gca, 'yscale', 'log');
  xlabel('Frequency [Hz]'); ylabel('ASD of the measured Voltage $\left[\frac{V}{\sqrt{Hz}}\right]$')
  legend('Location', 'northeast');
  xlim([0.1, 500]);

  <<plt-matlab>>

Comparison of the Amplitude Spectral Sensity

  <<plt-matlab>>

Comparison of the Amplitude Spectral Sensity - Zoom

Comparison of with and without LPF

  figure;
  hold on;
  plot(f, sqrt(pxdon),  'DisplayName', 'Direct - ON');
  plot(f, sqrt(pxsron),  'DisplayName', 'Slip-Ring - ON');
  plot(f, sqrt(pxd_lpf_on),  'DisplayName', 'Direct - ON - LPF');
  plot(f, sqrt(pxsr_lpf_on),  'DisplayName', 'Slip-Ring - ON - LPF');
  hold off;
  set(gca, 'xscale', 'log');
  set(gca, 'yscale', 'log');
  xlabel('Frequency [Hz]'); ylabel('ASD of the measured Voltage $\left[\frac{V}{\sqrt{Hz}}\right]$')
  legend('Location', 'northeast');
  xlim([0.1, 500]);

  <<plt-matlab>>

Comparison of the measured signals with and without LPF

Conclusion

• Using the LPF, we don't have any perturbation coming from the slip-ring when it is on.
• However, we should use a smaller value of the capacitor to have a cut-off frequency at $1kHz$.