3D Vibrometry Made simple
Ommatidia Q2 reconstructs full field 3D velocity vectors from multiple views using one parallel scanning Laser RADAR. Achieve modal analysis, ODS, and strain ready outputs with a compact, deployable setup that preserves a clear evidence chain from raw data to engineering deliverables
Application overview
LDV measures velocity along the beam; a single view is a projection and can misrepresent true motion on curved or complex structures.
Multi-view observations make vector components observable across shells, lightweight panels, blades, vehicle parts, civil elements, and lab test articles where motion includes out-of-plane, in-plane, and local rotations.
Up until now, the only way to achieve this was by using multi-head setups with robotic rigs. This was expensive, time consuming, rigid and limiting for many applications.
How Data Is Acquired to Reconstruct the 3D Velocity Vector
Part 2: 3D Vibrometry Data Processing Workflow
Part 2 follows the reconstruction workflow after acquisition: multiple point clouds are imported and filtered to the region of interest, then spherical fiducials register the scans in a shared coordinate system. The individual line-of-sight measurements are resolved into X, Y and Z velocity components, creating a full-field 3D vibration dataset ready for export to modal-analysis software such as Siemens Testlab.
Key advantages
Simple: One single Q2 recovers a complete 3D velocity field.
- Compact & affordable: Avoid multi-LDV rigs, robotic arms, and heavy lab integration.
- Fast: No per-point calibration campaigns; the same instrument provides metrology and vibrometry.
- Versatile: Deployable in labs, factories, and field sites without dedicated installations.
How it works
Ommatidia Q2 extends Laser Doppler Vibrometry from directional, line-of-sight measurements to full-field 3D velocity vectors—using one single parallel-scanning Laser RADAR. By acquiring multiple Q2 views, registering them via spherical fiducials, and phase-aligning the data, the recovery software estimates the three velocity components at each surface point.
The result is a coherent 3D motion field suitable for FEM correlation, modal analysis, ODS, and strain-ready outputs.
Operational benefits
- Per view, Q2 acquires a point cloud, beam directions, and line-of-sight (LoS) velocity at illuminated points.
- For each surface point seen from three or more independent directions, the 3D velocity vector is solved from the LoS projections; extra views improve robustness via weighted least squares.
- Local quality indicators assess observation count, residuals, and geometric conditioning.
- Export allows advanced visualisation and further processing in commercial FEA/engineering software packages.
Proof points
Plan as a single coordinated campaign, not isolated scans.
- Use Ommatidia planner tools to evaluate spatial coverage, sampling density, geometric consistency, phase consistency, and repeatable signal quality across views.
- Generate synthetic datasets to load in the reconstruction tool.
- Compare agains the ground truth to assess the effect of different experimental protocols, reconstruction algorithms and conditions (sampling, noise, interpolation scheme, etc.).
Webinar: 3D Velocity & Strain Workflow
Talk to Ommatidia
Discuss how this measurement approach could support applications workflows with the Ommatidia team.
Compare platforms for 3D velocity and strain workflows
Q2 is the strongest platform for multi-view 3D velocity reconstruction and strain-ready outputs, while QMini, Q1S and Q1 support related validation, monitoring and field-measurement steps.
Open the Q-series comparison guideOmmatidia Upgrade & Trade-In Program
Upgrade to Ommatidia’s latest Laser RADAR technology and unlock more capability for your next measurement challenge. Whether you are expanding an existing setup or replacing an older system, we offer tailored upgrade options with discounts of up to 40%.
If you are currently using another manufacturer’s system, send us your model and measurement requirements. We will review your trade-in possibilities, identify the best Ommatidia configuration, and outline a practical upgrade path for your team.
