Hi Marina,
I understand that you are trying to use modalfit function to find the "Modal Assurance Criterion". The Modal Assurance Criterion (MAC) is a measure used to quantify the degree of correlation between mode shapes in structural dynamics. There are differences in results from the modalfit function and the frfp2modes function of Abravive toolbox. Here are some potential reasons for the observed differences:
- Algorithmic Differences: Both functions likely use different algorithms for mode shape estimation. These algorithms may have varying sensitivities to noise, boundary conditions, or other factors.
- Data Preprocessing: Ensure that the input data (frequency-response functions) is properly preprocessed before using either function. Consider filtering, truncating, or removing noisy data points. Incorrect preprocessing can lead to inaccurate mode shapes.
- Model Order Selection: The modalfit function requires specifying the number of modes (mnum). If the chosen value of "mnum" is too high or too low, it can affect the quality of mode shapes.
- Boundary Conditions: Mode shape estimation is sensitive to boundary conditions. Ensure that the boundary conditions used during data acquisition match those assumed by the function. Inconsistent boundary conditions can lead to discrepancies.
- Measurement Noise: Noise in the frequency-response measurements can impact mode shape estimation. Consider the signal-to-noise ratio and measurement accuracy. Robust algorithms handle noise better.
- Function-Specific Parameters: Check if there are additional parameters specific to modalfit function (e.g., regularization terms, optimization settings) like "FitMethod". Adjust these parameters to improve results.
For more information on the modalfit function, follow this MATLAB R2024a documentation link: https://www.mathworks.com/help/signal/ref/modalfit.html#bvkw6bh-2
