Q-SERIES ANALYSIS, VISUALISATION AND DATA CONVERSION

OmmH5Viewer:nQ-Series data analysis and conversion

Open Q-Series HDF5 measurements, isolate the response that matters and prepare a handoff your engineering team can use. OmmH5Viewer keeps spectra, spatial views and modal analysis tied to the recorded test data.

Captured with Atelier. Reviewed, validated and exported with OmmH5Viewer.

PROCESS THE Q-SERIES DATASET

Start with the measurement record

Browse the recorded frames and metadata, select an analysis view and save the resulting output from the same desktop workspace.

Open structured datasets

Open current and legacy Q-Series HDF5 datasets, then browse frames, channels and associated metadata in the HDF5 Explorer.

Run a repeatable pipeline

Run defined processing steps on the recorded measurement instead of rebuilding the analysis from screenshots or manual calculations.

Prepare a usable handoff

Save processed results and export UFF when the next modal-data workflow requires a compatible exchange format.

MOVE FROM SPECTRUM TO SPATIAL RESPONSE

Inspect frequency content, then map the response

Use spectra and peak detection to select frequencies of interest. Mode maps, waveforms, STFT and cross-correlation views then show how the response varies through time, channels and space.

Use mode animation and point-cloud-aware views when the result needs to be interpreted or communicated as a spatial response.

OmmH5Viewer is the analysis stage after Atelier data capture: open the recorded dataset, validate the result and prepare the next engineering handoff.

ANALYSIS VIEWS

Choose the view that fits the question

Move between spectral, temporal and spatial views without separating the analysis from the source dataset.

Spectrum and peak review

Inspect velocity spectra, set peak-detection parameters and isolate frequencies that require engineering review.

Mode maps and animation

Display amplitude, phase and related spatial response maps across the selected frames and channels.

Fusion and validation

Review measurement results with point clouds and validation views before exporting or sharing them.

DATA FORMATS AND HANDOFF

Keep the dataset usable beyond the desktop

Q-Series measurements use HDF5, a self-describing format for data and metadata. OmmH5Viewer exposes that structure for laser-vibrometry review and processing.

Export UFF when a modal-data workflow needs geometry and vibrometry together. To plan the full route from capture to handoff, see the Q-Series software workflow or talk to an Ommatidia engineer.

Export results with their measurement context

Choose the exchange format that fits the next engineering task while retaining the measurement context needed to interpret it.

CSV for flexible tabular use

Export selected channels, spectral results and derived values as tables for reports, calculations and custom scripts.

UFF with geometry and vibrometry together

Export geometry and vibrometry response together in a UFF handoff, preserving coordinate, channel and motion relationships for downstream modal workflows.

HDF5 for the full Q-Series record

Retain the Q-Series HDF5 dataset when the next team needs recorded frames, metadata, raw measurements and processed results together.

Visualise the behaviour behind the dataset

Select the view that answers the analysis question, while keeping the result associated with the recorded measurement.

STFT

Track changing frequency content through time when a single spectrum cannot describe the response.

PSD, ASD and FFT

Compare spectral energy, amplitude density and frequency peaks using the representation appropriate to the analysis.

Intensity diagnostics

Use intensity information to check signal quality, scan coverage and regions that need attention.

Mode animation

Animate a selected response or mode shape to make spatial behaviour easier to interpret and discuss.

Operational modal analysis with PyOMA2

Use the beta PyOMA2 workspace for operational modal analysis without moving the dataset into an unrelated toolchain.

The current beta workflow supports Frequency Domain Decomposition: choose a frame and frequency range, set segment length and overlap, review singular values and peaks, then inspect the resulting shape or mesh. See PyOMA2 documentation.

From candidate peak to mode shape

Review detected peaks as mode candidates against the measured channels. Animate the selected result while retaining its relationship to the original data and geometry.