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FEMtools Pretest and Correlation

FEMtools Pretest and Correlation

A Complete Solution for Modal Pretest Analysis. FE Model Verification and Validation using Test-Analysis Correlation

FEMtools Pretest and Correlation contains tools for:

  • Pretest Analysis – Planning, simulation and optimization of modal tests.
  • Correlation Analysis – Visual and numerical correlation between two sets of data with model, shapes or functions (FEA-Test, FEA-FEA, Test-Test).

Pretest Analysis

If a baseline finite element model is available, then this model can be used to simulate tests. This provides test engineers with optimal locations and directions to excite the structure, and to position measurement transducers. The FE model can be reduced and converted into a test model.

  • Baseline Finite Element Analysis – Analyze mode shapes in the frequency range of interest. FEA data (model, modes, FRFs) can be imported or computed using FEMtools Framework or external solvers.
  • Target Mode Selection – Select modes in the frequency band of interest based on energy considerations. Methods include: Modal Effective Mass, Kinetic Energy Fraction.
  • Selection of Candidate Sensor Locations – Use criteria like accessibility, cost, geometry (surface, edge or corner nodes) or any other user-defined criteria to select candidate locations. A set of fixed sensors can be added. 
  • Sensor Placement Metrics – These are semi-automatic methods to find optimal exciter, suspension and measurement locations and directions. They are based on the observability of target modes using information on modal displacement or energy (kinetic or strain). Methods include: Normalized Modal Displacements, Modal Participation, Nodal Kinetic Energy.
  • Sensor Elimination Methods – These methods iteratively eliminate sensors from the set of candidates in a way to optimally maintain linear independence or orthogonality between mode shapes. Methods include: Effective Independence Method, Elimination by MAC, Iterative Guyan reduction.
  • Mass Loading Evaluation – This tool evaluates the effect of accelerometer mass on the modal parameters.
  • Creation and Export of Test Model – Truncation of the FE model, conversion to test model and export to a modal test software. Automatic generation of tracelines between retained sensor locations. Directions normal to the surface can be obtained from the FE model.  The measurement directions can be expressed as Euler angles.

Questions that can be answered with pretest analysis include:

  • How many modes can be expected in a given frequency range?
  • What are the optimal location and directions for sensors, exciters and suspensions from a set of candidate locations?
  • Create a test model from a reduced finite element model and export in a format readable by modal test packages.
  • Determine the directions normal to the surface of curved surfaces from the finite element model and use this information for decomposing modal test displacements in Cartesian coordinates.
  • What are the measurement directions expressed as Euler angles?
  • Assess the influence of the accelerometer mass on the modal parameters.

Using the pretest analysis tools it is possible to plan an optimal modal test strategy early in the project and increase quality of modal data for validation and updating of FE models.

Key Features
  • Plan a test strategy early in the project.
  • Easily find optimal location for sensors, exciters and suspension.
  • Fast creation of a test model from a baseline FE model.
  • Increase quality of modal test data for validation and updating of FE models.

Correlation Analysis

Correlation analysis quantitatively and qualitatively compares 2 sets of analysis results data. Usually this is a FEA and a test database that are imported in the FEMtools database. However, the tools can be used for FEA-to-FEA and test-to-test correlation as well.

  • Spatial correlation – Compares location in space between response locations resulting in a table with mapped degrees-of-freedom. This may require changing orientation and scaling of the models, which can be done in a manual way or using automatic tools.
  • Visual shape correlation – Visually compare shapes (static displacement shapes, mode shapes and operational shapes) using side-by-side, overly and animated displays.
  • Global shape correlation – Globally compares shapes using various criteria. The result is used for shape pairing.
  • Local shape correlation – analyzes local spatial correlation between shapes. Results can be interpreted to localize modeling deficiencies and serve as guideline for selecting model updating parameters.
  • Shape pairing – Creates a table of shape pairs (static, modal or operational).
  • FRF pairing – Creates a table of FRF pairs.
  • FRF correlation – Analyzes correlation between FRF functions, either globally between 2 functions or shape and amplitude correlation functions for a set of FRF pairs as function of frequency.
  • Correlation coefficients – Calculates values of error functions from a selection of reference responses. These functions are used in model updating to monitor the distance between the updated model and a reference.

Correlation analysis is used for FE model validation, design of optimal test conditions, evaluate different modeling strategies, identification of modeling errors, damage detection, …

Results from correlation analysis are used to define targets for FE model updating. Similar mode shapes can be identified in the FE and test database thus providing residues in terms of resonance frequency differences, MAC, modal displacements.

Another application is to provide the analyst with information that can only be measured. An example is modal damping, used in modal superposition methods. Modal damping can be obtained experimentally and applied to the analytical mode shape that, using correlation analysis, was found to best match the experimental one.

Modal correlation analysis is also used to scale test mode shapes obtained by output-only modal analysis. The same scaling as used by the analytical mode shapes (e.g. unity modal mass), can be applied to the correlated test modes.

Unlike global correlation analysis, spatial correlation methods are used to identify areas of better or poorer correlation, which when linked to structural information, can be interpreted in terms of ‘modeling error’. Depending on how these tools are used, the results help with the selection of updating variables (parameters), or are used to assess structural damage.

Key Features
  • FEA-Test, FEA-FEA, Test-Test Correlation.
  • DOF pair table definition, ranking and filtering.
  • Automated or manual model mapping.
  • Directional and multi-step pairing.
  • Efficient processing of large data sets (point clouds).
  • Static, modal and operational shape correlation analysis using MAC.
  • Mode shape auto- and cross-orthogonality check using full or reduced system matrices.
  • Automatic mode shape pairing using MAC or ortogonality matrix.
  • Automated support for mode shape pairing in case of double modes (axisymmetric structures).
  • MAC contribution analysis.
  • Spatial shape correlation using Coordinate MAC (CoMAC), Coordinate Orthogonality Check (CORTHOG), Correlated Shape Difference and Modal Force Residue analysis.
  • FRF correlation using SAC, CSAC (= FRAC), CSF.
  • Correlation using local test coordinate systems.

User Interface

  • All definition, editing and analysis accessible via intuitive menus and dialog boxes or using free format commands for batch processing and process automation.
  • Complete electronic documentation.
  • Dedicated graphics viewers for model inspection and results evaluation.
  • Point-and-click interactive selection.
  • Direct access to FEA and test data.
  • Unlimited customization using FEMtools Script.
  • All pretest analysis and correlation tools are programmed in FEMtools Script language and can be easily customized or extended.
  • Customizable user interface.
  • Solver-neutral integration with virtually every FEA and test data.
  • Computing and OS platform-independent solutions.

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