An Open-source Supported Guide to High-speed Camera Based Structural Dynamics Identification

Code repository for the tutorial paper published in Mechanical Systems and Signal Processing.

D. Gorjup, K. Zaletelj, J. Slavič, An Open-source Supported Tutorial to High-speed Camera Based Structural Dynamics Identification, Mechanical Systems and Signal Processing, TODO (TODO). DOI: TODO

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Setup

Python 3.11+ is required.

# Clone (videos are stored with Git LFS — install LFS first)
git lfs install
git clone git@github.com:domengorjup/mssp-image-tutorial.git
cd mssp-image-tutorial

# Create virtual environment and install dependencies
python -m venv .venv
source .venv/bin/activate        # Windows: .venv\Scripts\activate
pip install -r requirements.txt

# Register the kernel and launch the notebook
python -m ipykernel install --user --name=mssp-tutorial
jupyter notebook image_based_dynamics_tutorial.ipynb

No git? Use the Download ZIP button on GitHub — it includes the real video files.
No LFS? If you cloned without LFS, fetch video files with git lfs pull.

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Repository structure

image_based_dynamics_tutorial.ipynb   # main tutorial notebook
methods/                              # reusable Python modules
    calibration.py                    # intrinsic and extrinsic camera calibration
    triangulation.py                  # DLT point triangulation and ODS reconstruction
    modal.py                          # FRF estimation and modal analysis utilities
    visualization.py                  # plotting and animation helpers
    utils.py                          # general utilities (I/O, image loading)
data/
    calibration/                      # checkerboard calibration images
    mraw_downsized/                   # downsampled Photron videos (two views, Git LFS)
    mraw/                             # full-resolution videos (Git LFS, available on request)
    measured_signals/                 # force and acceleration signals (HDF5)
    results/image_displacements/      # precomputed LK optical-flow displacements (HDF5)
    plate_speckle.png                 # speckle pattern image for visualization

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Measurement

The example dataset consists of a sine-sweep excitation experiment on a thin plate with a speckle pattern, recorded sequentially from two camera views.

• Excitation: swept-sine, 60–500 Hz
• Views: 2 (multi-view for 3-D displacement reconstruction using frequency-domain triangulation)
• Repetitions: 4 (view 0) / 1 (view 1) — used for ensemble-averaged FRF estimation
• Camera: Photron high-speed, downsampled to 384×384 px at 1000 fps for the provided example data
• Force and acceleration sampled at 25600 Hz (DAQ), clipped to camera Nyquist (500 Hz) during analysis

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Provided data (HDF5)

All precomputed data is stored in HDF5 format, readable without any proprietary software. Load with methods.utils.load_hdf5 or directly with h5py.

data/measured_signals/view_0[_02|_03|_04].hdf5

Force and acceleration time series for the 4 view-0 repetitions.

InputTask/
    data          float64 (51200, 3)   columns: force [N], acceleration [m/s²], trigger
    time          float64 (51200,)     time axis [s]
    channel_names str list             ['force', 'acc', 'trigger']
    sample_rate   int                  25600 [Hz]

data/measured_signals/view_1.hdf5

Same structure, single repetition for view 1.

data/results/image_displacements/idi_lk_displacements[_02|_03|_04].hdf5

Lucas–Kanade optical-flow displacements for each measurement repetition.

view 0    float64 (100, 2000, 2)   displacements [px] — axes: (point, frame, [v, u])
view 1    float64 (100, 2000, 2)

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Citation

@article{gorjup2026tutorial,
  author  = {Gorjup, Domen and Zaletelj, Klemen and Slavi\v{c}, Janko},
  title   = {An Open-source Supported Guide to High-speed Camera Based Structural Dynamics Identification},
  journal = {Mechanical Systems and Signal Processing},
  year    = {TODO},
  volume  = {TODO},
  pages   = {TODO},
  doi     = {TODO},
}

Authors

• Domen Gorjup — University of Ljubljana, Faculty of Mechanical Engineering
• Klemen Zaletelj — University of Ljubljana, Faculty of Mechanical Engineering
• Janko Slavič — University of Ljubljana, Faculty of Mechanical Engineering