Back Share
 

Correlation

 
LMS Virtual.Lab Correlation offers tools to ensure that high-quality FE models are used in a CAE environment and that correct sensor and excitation locations are employed in a dynamic physical structure test environment. It interactively creates a test wireframe on top of the FE mesh and quantifies its quality according to relevant mode capturing and modal excitation.
 

LMS Virtual.Lab Correlation

VL Correlation 04 Correlation.jpg
LMS Virtual.Lab Correlation offers tools to ensure that high-quality FE models are used in a CAE environment and that correct sensor and excitation locations are employed in a dynamic physical structure test environment.

For pre-test analysis, users can create an optimal test geometry from an existing FE model. LMS Virtual.Lab Correlation interactively creates a test wireframe on top of the FE mesh and directly quantifies its quality ccording to relevant mode capturing and modal excitation. In case of poor sensor location set quality, LMS Virtual.Lab Correlation provides an easy way to analyze why the model was off-target. Users can easily change the test geometry and directly assess new quality levels using the MAC (Modal Assurance Criterion). The DPR (Driving Point Residue) criterion is used for the excitation point set.

LMS Virtual.Lab Correlation also lets users easily and quickly compare the dynamic behavior of two models and deal with incompatible meshes (test and/or FE). It helps users to quantitatively articulate the degree of shape correlation using a MAC matrix. If the MAC values are too low to subjectively correlate the modes, the MAC Contribution (MACCo) criterion points out the differences to be examined. In this way, users can verify different modeling assumptions by comparing reference or measurement data. This improves model and simulation reliability. An orthogonality check between two models adds a degree of correlation accuracy by using the mass matrix to compare system dynamics. For this, LMS Virtual.Lab Correlation sets up the Nastran DMIG Solution to obtain reduced system mass matrices required for orthogonality checks between test and FE modes. The FRAC (Frequency Response Assurance Criterion) compares transfer functions between two models and provides information about global stiffness and mass modeling errors.



Features

  • Universal access to test and FE data for models, modes and frequency spectra
  • Modal Assurance Criterion (MAC) and MAC Contribution (MACco) support error localization
  • Visual Shape correlation for side-byside model animation (FE or Test)
  • Frequency Response Assurance Criterion (FRAC)
  • Orthogonality check for better dynamic correlation
  • Driving Point Residue (DPR) for shaker location identification
  • Export data to LMS Test.Lab or a universal file format


 Benefits

  • Maximum test information with minimized excitation and measurement locations
  • Increase measurement productivity with direct LMS Test.Lab integration
  • Confirm FE simulation model validity using measurements
  • Identify modeling errors or evaluate modeling strategies
  • Improve simulation model reliability



    Covering a range of industries, LMS application cases let you discover how LMS solutions help our customers solve their real-life engineering challenges.




    Brochures
    Download the LMS Virtual.Lab Introduction Brochure
    Download the LMS Virtual.Lab Correlation Brochure

    Demo Movie
    Correlation

    Images

    VL Correlation Correlation 01.jpg VL Correlation Correlation 02.jpg VL Correlation Correlation 04.jpg
    Animation of preliminary FE models helps understand which locations to include in a physical test. Interactive creation of the wireframe of measurement points. Localize problem areas using MAC Contribution.


    Please fill in all required fields (marked with an asterisk).





     

    Do you have a technical or commercial question?