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2.2 Identification of modal properties (Id dock)

Identification is the process of estimating a parametric model (poles and modeshapes) that accurately represents measured data. The identification process is typically performed using the dock shown below opened with iicom('dockId').

2.2.1 Opening and description of used data

The following procedure loads data from a .unv file but other way to open and load data are available.

  • Open an empty dock iicom('dockid') and load data from the interface by selecting files (see below). A list of acquisition software from which data have been successfully loaded is described in section 2.2.3.
  • Reopen a dock previously saved in SDT format (.mat).
    • For saving : in idcom figure, use File:Save, chose the data that need to be saved (all selected by default) and then chose the saving file name.
    • For reloading: execute the command iicom('curveLoad File.mat')
  • Load data from variables in the workspace. It is then possible to load data from files directly into variables (see section 2.2.3, which is useful if data customization is required) or to deal with user-built transfers (see section section 2.2.4) and finally pass the result to Id dock.

    When manual assignation is performed, do not forget to click on to refresh the tables (for instance the pole list in idcom). Note that to perform identification, only the transfers are needed: the wireframe allows visualizing the identified mode shapes and the list of poles is helpful if previous identification has been performed.

On top of the Test and IdMain data discussed above, other useful data used throughout the identification process and stored in the iiplotStack are

  • Test contains measured frequency response functions. See section 2.2.3 ways to initialize this data set.
  • IdFrf contains the synthesis of transfers associated with given set of transfers (shown in red in the figure above).
  • IdAlt contains the alternate set of modes (poles and residues). These are listed on the left list of the Ident tab below.
  • IdMain contains the main set of modes (poles and residues). These are listed on the right list of the Ident tab.

Here is a tutorial for interactive data loading in DockId

You will need the garteur example files, which can be found in SDTPath/sdtdemos/gart*.m. If these files are not present, click on the first step on the following tutorial in the HTML version of the documentation or download the patch at the adress https://www.sdtools.com/contrib/garteur.zip and unzip the content in the the folder SDTPath/sdtdemos.

  1. Run Execute the command iicom('dockid') to open an empty dock.

    The dock is divided in three parts:

    • At right, the iiplot figure where are displayed all curves (measured transfers, synthesized transfers, mode indicators...)
    • At the top left hand corner, the idcom figure which is used to interact with the data in iiplot, especially here using the Ident tab to perform the identification process
    • At the bottom left hand corner, the feplot figure where the wireframe is displayed. It lets you animate the identified modeshapes. The feplot('mdl') is accessible behind and lets you visualize the information about the wireframe.
  2. Run The loading of .unv files can be realized from iiplot or feplot. Activate for instance the idcom figure and select File:ImportData...

    Here are the 4 possible menus in this order: iiplot, idcom, feplot and feplot('mdl').

    In the opening window, select the file to load. For this tutorial, the file is located at SDTPath/sdtdemos/gartid.unv.

    Once selected, the Unv tab is displayed in the idcom or the feplot('mdl') figure (depending the chosen menu for ImportData.

    It shows that three types of data are present in the file: a wireframe, transfers and identified mode shapes. Select the three check boxes to load everything.

  3. Run Click on Import (or Import in DockId which is used to build dockId if the loading is performed in a feplot or an iiplot figure outside a dockid).

    The data are loaded: transfers are shown in the iiplot figure, the wireframe in the feplot figure and the list of poles in the tab Ident of the idcom figure.

  4. Run Once an identification is performed, click on Save in the idcom figure.

    A windows pops-up to ask what data must be saved. Save all (by default) to set all the data and info on the dockid in the saving file.

    Close the dock. A pop-up should appear to ask if you really want to close iiplot (this is to ensure that no data is lost if no saving has been performed), click on Close without saving.

  5. Run To reload the saved dock, two possibilities are available:
    • Execute the command iicom('curveload filename')
    • Open an empty iiplot figure and load the saved file with File:Import Data...

2.2.2 General process

The proposed identification process is outlined below. The main steps of the methodology are

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  • Initial pole estimates are placed in IdAlt using advanced pole picking, LSCF (see section 2.3) or any other algorithm outside SDT.
  • A user validated list of poles is kept in IdMain. The arrows between the two list in the interface (which correspond to the ea and er commands) can be used to move poles between the two lists: add missed poles, remove computational or undesired poles .
  • Shapes (pole/residue models, residual terms, modeshapes derived from residues) are then estimated for each pole given in IdMain. Several strategies exist and are more deeply explained at section 2.5
    • Broad band estimation on the whole frequency band : est command/button
    • Narrow band estimation on the selected band : estlocal command/button
    • Iterative local estimation around each pole : estlocalpole command/button
  • Optimizing poles (and residues) of the current model depending on the quality obtained by the previous passes. As for the estimation of shapes, there three strategies for the optimization:
    • Broad band update : eup for high number of poles and eopt for up to 2-3 poles
    • Narrow band update on the selected band: euplocal and eoptlocal
    • Iterative local updates around each pole: eoptSeq
Figure 2.7: Modal identification process with links to corresponding sections

This process is handled through the Ident tab opened with iicom('InitIdent') or with the interface by clicking on Tab : Ident from the iiplot or idcom figure.

The main steps, associated with level 1 lines in the GUI tree are the topics of specific sections of the documentation:

  • AddPoles : use an initial algorithm to estimate poles (single pole estimator or selection in a stabilization diagram LSCF).
  • IDopt : select frequency range and possibly define properties of transfers (displacement, velocity, acceleration, MIMO,...)
  • Estimate shapes using a frequency domain output error method that builds a model in the pole residue form (see section 5.6). Theoretical details about the underlying algorithm are given in section 2.6.5. Section 2.5.3 addresses its typical shortcomings.
  • Adjust poles using one of the non-linear optimization algorithms.
  • Transform the output to a format dealing with MIMO constraints, reciprocity, ...

The gartid script gives real data and an identification result for the GARTEUR example. The demo_id script analyses a simple identification example.

2.2.3 Importing FRF data

SDT stores transfer functions in the Response data (.w,.xf fields) or curve (.X,.Y fields) formats. The following table gives a partial list of systems with which the SDT has been successfully interfaced.


VendorProcedure used
Bruel & KjaerExport data from Pulse to the UFF and read into SDT with ufread or use the Bridge To Matlab software and pulse2sdt.
LMSExport data from LMS CADA-X to UFF or MATLAB format.
PolytecInstall the Polytec File Access library on your computer and use the polytec function to import .svd files directly. Alternatively, export data from PSV software to UFF.
DactronExport data from RT-Pro software to the UFF. Use the Active-X API to drive the Photon from MATLAB see photon.
MathWorksUse Data Acquisition and Signal Processing toolboxes to estimate FRFs and create a script to fill in SDT information (see section 2.2.3).
MTSExport data from IDEAS-Pro software to UFF.
Spectral DynamicsCreate a Matlab script to format data from SigLab to SDT format.


  • Universal files are easiest if generated by your acquisition system. Writing of an import script defining fields used by SDT is also fairly simple and described below (you can then use ufwrite to generate universal files for export).

    The ufread and ufwrite functions allow conversions between the xf format and files in the Universal File Format which is supported by most measurement systems. A typical call would be

    where you read the database wrapperUFS (see xfopt), initialize the idcom figure, assign dataset 2 of UFS to dataset 'Test' 1 of ci (assuming that dataset two represents frequency response functions of interest).

    Note that some acquisition systems write many universal files for a set of measurements (one file per channel). This is supported by ufread with a stared file name UFS=ufread('FileRoot*.unv');

  • Polytec files need many options to extract data (Time/Transfers, Estimator H1/H2, Velocity/Force...). Please read the dedicated polytec documentation to adapt the example below to your needs. Note that the code below needs Polytec File Access to be installed.

    To avoid the manual filling of the reading options, it is also possible to simply load data from the interface : follow the tutorial in section section 2.2.1) but select the .svd file instead of the .unv file and do right-click+Read selected on the line you want to read. Loaded transfers can then be stored to variables with the command ci=iiplot;xf=ci.Stack{'Test'};

2.2.4 Write a script to build a transfer structure

When writing your own script to transcript data to xfstruct format, you must have a MATLAB structure composed at minimum of the fields

  • .w : a column vector of frequencies
  • .xf : a matrix of measured frequency responses (one row per frequency, one column per measurement channel).

Other fields may be required to specify the type of data and the type of model to use for identification. Two main optional fields are presented here:

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  • .dof field can be used to specify the meaning of each transfer (input and output DOF).

    This field should be set for title/legend generation (this is a label).
    For correct display of shapes in feplot, the .dof may be a direct specification of direction in simple cases where the sensors are really oriented in global axes, but in general is just a label for the sensor orientation map stored in a sens.tdof field. See section 2.7 for details on geometry declaration.
    In the example below one considers a MIMO test with 2 inputs and 4 outputs stored as columns of field .xf with the rows corresponding to frequencies stored in field .w. You script will look like

You can check these values in the iicom('InitChannel') tab.

  • .idopt field should also be filled for correct identification using id_rc,. For the main data set called Test the .idopt field is that of the figure which is more easily accessed from ci.IDopt. These correspond to the IDopt part of the Ident tab (see section 2.4). You can also edit these values in a script. For correct identification, you should set

For correct transformations using id_rm, you should also verify ci.IDopt.NSNA (number of sensors/actuators), ci.IDopt.Reciprocity and ci.IDopt.Collocated.

For

For correct labels using iiplot you should set the abscissa, and ordinate numerator/denominator types in the data base wrapper. You can edit these values using the iiplot properties:channel tab. A typical script would declare frequencies, acceleration, and force using (see list with xfopt _datatype)

2.2.5 Data acquisition

The SDT does not intend to support the acquisition of test data since tight integration of acquisition hardware and software is mandatory. A number of signal processing tools are gradually being introduced in iiplot (see ii_mmifFFT or fe_curveh1h2). But the current intent is not to use SDT as an acquisition driver. The following example generates transfers from time domain data

You can find theoretical information on data acquisition for modal analysis in Refs. [2][3][4][5][6].


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