Plots setup

Data can be analyzed and visualized in the software. Both data analysis and visualization of the processed data is set up in a plot.

The plots setup dialog is launched via “Setup”->”Plots Setup”.
The dialog shows the currently added plots. Each plot can be expanded to reveal the individual settings, which depends on the plot type.
some option

Plots setup dialog

A plot is added by pushing the dropdown “Add plot” and selecting the plot type.
Each plot can be renamed or removed by right clicking the plot title.
The whole plots setup can be cleared via the “Clear setup” button.

A plots setup can be loaded seperately from a (.sava) setup file by selecting “Load setup” in the “Plots Setup”-dialog.

Tip

The plot setup for an individual plot can be opened via the context menu in the plot container.

Common plot settings

All plot types have the following settings in common:

Channels:
The channels processed/plotted in the plot. If a source is setup, the channels names can be selected from a dropdown. Elsewhere an integer array (starting at 0), is used to select channels. An empty array selects all channels.
By right clicking the channel box, one can “select all”, “deselect all” or “reset the order”.
Pre filtering:
Time domain filtering before any other processing is applied. Detrending (remove mean) and N’t Order Butter filter are available.
View settings:
The view settings can be altered while the source is running, without clearing the already processed values.
If the value monitor is checked, the graphical visualization is disabled, and only the latest value(s) are displayed as a float.

Tip

A plots view settings are accessible directly in plot the context menu, see plot container.

External process module:
The software is able to load a custom Python script and use it an external process module. This can be utilized to set up custom processing and/or forward data to external application etc.

Select a file by either entering the path in “External module” or browse for the file, by pushing “Browse modules”. The path can be absolute or relative (to current directory).

Note

Examples of external process modules (“extProcessModule.py” and “extProcessModuleXY.py”) are located at: “Help”->”External Module Examples”.

Plot types

Time Series

For sampled data points vs time plots. Primarily used for displaying raw data.

Settings:

  • Buffer time: Time samples stored in moving buffer and displayed simultaneously

  • Process: Processing of raw data:

    • None: Raw data

    • Order tracking: Filtered raw data via order tracking (see processing types)

Trend

For trending, a downsampled representation, of sampled data vs time plots.

Settings:

  • Trend time: Time samples in each trend bin. Will also be time between samples in the plot.

  • Trend type:

    • Mean: The mean of the samples in the bin

    • Peak-Peak: Difference between larges and smallest value in the bin

    • 0-Peak: Half Peak-Peak

    • Min/Max: The minimum or maximum value in the bin

    • Abs max: The maximum absolute value in the bin

    • RMS: Root Mean Square value of the bin. Also called “Effective value” of “Vibration energy” of a signal. It is often beneficial to detrend the input signal.

    • Variance: A measure of the AC Power of the samples in the bin

    • Kurtosis: A measure of the distribution of the samples in the bin, in relation to normal distribution (Kurtosis==3)

    • Skew: A measure of the distribution symmetry of the samples in the bin.

    • MAD: Mean Absolute Deviation of the bin

    • Tacho: See processing types

    • Order tracking: See processing types

    • Other Trend value:See processing types

Spectrum

For sampled data (magnitude and/or phase) in the frequency domain plots.

Settings:

  • Type: FFT, FRF or Order Spectrum (see processing types)

  • N Lines: Number of samples in each bin

  • Window: Windowing of the sig FFT

  • Overlap: Overlap of bins

  • N Averages: Number of FFT-bins averaged in resulting FFT

  • Integrate: Integration of result (in frequency domain)

  • Plot Type: Magnitude and/or phase results

  • Scaling: Magnitude scaling of the FFT

  • Peak-Hold: Show the peak value of in the spectrum

Special uses

  • Impact testing: This plot can be used for experimental modal analysis (Impulse excitation) by selecting a FRF, with impulse as input channel, and the “Detect trigger” option.

XY

For plotting results vs results. For instance a sensor’s signal vs another sensor’s signal (Time series vs Time series) or Maximum vs a velocity (Trend vs Trend).

Settings:

  • Type: Time series vs Time series or Trend vs Trend

The setup is the same as for the base version (Time series or Trend), but there is a channel and processing setup for both Y and X axis.
The channel order controls which X-channels are combined with which Y-channels.
It is possible to select a single X-channel and multiple Y-channels, but not vise versa.

Special uses

  • Orbit plots: A 2D trajectory plot (Time series) of a rotating component.

  • Bode plots: A filtered (Order tracking) amplitude and phase plot of a rotating component vs the rotation speed.

3 Axis

For Spectral plots vs time in 3 axis plot.

Warning

The 3D plot visualization requires OpenGL graphics support.

For the spectrum setup see spectrum.
Settings:

  • Time: Total time span in the plotted results

  • Layer time: Time between each spectrum

Processing types

Besides the basic processing types, listed under trend plots, the following types are awailable:

FFT:
Fast Fourier Transform: Transformation from time domain to frequency domain.
FRF:
Frequency Response Function: A cross spectrum; FFT of “Channels” vs FFT of an input channel. For instance a tacho pulse or an Impulse excitation.
Tacho:
Calculates rotational speed from time domain pulse signal.
The tacho trigger can be detect pulses based on the following parameters:

  • Single: A simple single pulse threshold. Is noise sensitive.

  • Hysteresis: A “schmitt”-trigger, utilizing a low- and high-threshold, to filter out false triggers due to noise.

  • Auto: Automaically estimates the trigger level based on the current block data.

In general it is often beneficial to detrend the input signal.

Order Tracking:
Domain frequency component of an FFT (magnitude or phase) corresponding to an order of rotational speed (from a tahco).
Order Spectrum:
A spectrum based on data that has been resampled from the time domain to the rotational domain, resulting in a constant angle sampling frequency, thus making the spectrum rotational speed independent.

A tacho is needed as the refrence key-phaser for the resampling.

Other Trend value:
The most recent processed value(s) from another trend plot can be retrieved/reused in a trend plot.
This is handy if a processed value is needed in multiple plots.
This can also be utilized in combination with external process modules.
The “other Trend value(s)” can be retrived directly in an external module, and thereby perform further custom processing and/or cobine processed values across multiple sources.
External process modules can also set “custom trend”-values directly (also from non trend plots), that can then be plottet in a “Other Trend value”-Plot.

Note

The custom trend functionality is illustrated in the demo setup example, with the external process module “extProcessModule_customTrend.py”.