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The complete experimental modal analysis procedure.

Define geometry

Geometry builder lets you create your models from nodes with specified coordinates and coordinate systems. It supports 2D and 3D primitives such as lines, planes, cylinders and boxes of different shapes. Large node patterns can be generated automatically by using the geometry wizard.

Measure signals

Data can be acquired in experiments or imported from uff. Operational and experimental modal analysis are supported through the options of different excitations signals, such as impulse or random. National Instruments hardware is supported out of the box.

Modal analysis

Modal parameters are identified by a process of curve fitting that is used to estimate the poles (natural frequencies and damping ratios). The LSCF and LSCE methods are available.


Measured and analyzed data can be visualized and animated revealing information about the dynamics of the structure. Each identified or measured mode is visualized based on the frequency-response spectrum.


Easy to extend.

OpenModal is built using established libraries such as Numpy, pandas, pyqtgraph, scipy and others. All the data, from measurement and analysis, is kept in pandas dataframes, which can be read and modified freely. New analysis methods can be implemented with ease to take the advantage of the visualization, measurement and analysis framework. In this way, OpenModal can be used a platform for fast implementation of latest state-of-art routines.


Available through pip and on Github.

The OpenModal project spawned the development of Python libraries that may be useful for other projects related to signal processing, structural analysis and measurement. We will continue to provide standalone libraries when parts of OpenModal grow mature enough. So far, the following Python libraries have been made available on PyPI and on Gihtub.


Defines a Python object for manipulating with the UFF (Universal File Format) files. Implements multiple fields for storing geometry, coordinate systems, measured frequency-response functions and experimental modal analysis results.

Github / PyPI


Implements a parser for reading text-type LabView Measurement files. It reads the header data and supports files that are split into multiple sections.

Github / PyPI


Frequency-response functions, can be defined using the pyFRF object. Different window and averaging options are available. The library can be used with impulse as well as random excitation.

Github / PyPI


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