Transforming Industrial Diagnostics: Ommatidia LiDAR at WEG with the Q2 Laser RADAR
In a recent hands-on collaboration between Ommatidia LiDAR and WEG, a global leader in electric engineering solutions, our Q2 Laser RADAR tackled four real-world industrial challenges. These on-site demonstrations didn’t occur in pristine labs but in live environments filled with strong electromagnetic interference (EMI), mechanical noise, and real operational constraints.
In every scenario, the Q2 delivered clear, actionable data. It proved how fast, contactless vibrometry can change the way we handle noise and vibration in electric machines. Let’s walk through each case and see how the Q2 supported smarter maintenance and design.
Real-World Application of the Q2 Laser RADAR
The Q2 Laser RADAR from Ommatidia LiDAR demonstrates how advanced interferometric technology can be deployed directly in the field to tackle real industrial challenges. Designed for high-resolution, multi-channel vibrometry, the Q2 enables precise, non-contact measurement of vibrations in complex machinery such as motors and transformers. In collaboration with WEG, one of the world’s leading manufacturers of electric motors and automation systems, Ommatidia LiDAR showcased how this sensor delivers actionable diagnostic data under real operating conditions — revealing subtle vibration patterns and mechanical behaviors that traditional tools often miss.
Case Study 1: Ommatidia LiDAR at WEG – Investigating a Buzzing Transformer in Operation
The first case centered on a transformer making a loud buzzing sound during service. The conditions were harsh: the equipment was surrounded by EMI, vibration noise, and difficult access.
The goal was to find the source of the noise and help guide a precise intervention. In just 30 minutes, the Q2 was deployed and streaming data. Using its array of laser beams, it captured the full vibration spectrum and mapped how energy spread across the transformer’s surface.
The result? The Q2 revealed a series of 50 Hz harmonics extending up to 1000 Hz. These patterns pointed to internal electromagnetic sources. The device also pinpointed where the vibration was strongest, even in areas difficult to reach with traditional sensors. This allowed engineers to act quickly, without disassembling the system.
By working in real time, the Q2 offered a unique mix of spectral and spatial insight—turning a noisy problem into a clear, solvable issue.
Vibration maps: full view (0-500Hz)
Vibration maps: full view (500-800Hz)
Case Study 2: Ommatidia LiDAR at WEG – Measuring Vibration in a 3.5 MVA Generator
The second test took place on a 3.5 MVA generator connected to a drag motor at WEG’s Workbench A05. The equipment was running throughout the test.
Our goals were to measure vibration, identify stress points, and support maintenance planning. Like before, the Q2 was set up in under 30 minutes and began delivering full-field data instantly.
3.5 MVA WSW Generator, connected to a drag motor at workbench A05
The device detected strong vibration peaks at 30, 60, and 120 Hz. These are common in machines experiencing mechanical imbalance or misalignment. Without touching the equipment or stopping it, the Q2 gave engineers a live view of where vibration was building up.
This made it easier to decide where to focus preventive maintenance and avoid potential failure. The ability to visualize stress in real time gave teams more confidence and control.
Vibration maps for detected peak frequencies
Case Study 3: Ommatidia LiDAR at WEG – Analyzing the Coupled Drag Motor
For the third test, the focus shifted to the drag motor paired with the WSW generator. This allowed us to assess the interaction between the two machines under real working conditions.
Despite strong EMI and mechanical noise, the Q2 delivered high-resolution results. It uncovered several vibration harmonics between 30 and 720 Hz. The most prominent one appeared at 120 Hz, showing a recurring issue across the coupled system.
Drag motor at workbench A05, connected to 3.5 MVA WSW Generator
Using 3D vibration maps, engineers could see where energy was concentrated and how the motor reacted under load. This direct, visual insight replaced guesswork and supported smarter design and maintenance decisions.
Again, the Q2 proved it can scale easily between machine types and setups.
Vibration maps for detected peak frequencies
Case Study 4: Ommatidia LiDAR at WEG – Detecting High-Frequency Magnetic Noise in the W22Xdb Motor
The final test looked at the W22Xdb motor. The goal was to find sources of magnetic noise that contribute to high-frequency vibration and unwanted sound.
The Q2 ran a wide-spectrum scan from 0 to 3.6 kHz. This is a range where conventional sensors struggle, especially in noisy industrial settings.
RMS average over the whole scene, with background removal.
It worked flawlessly. The system revealed vibration modes caused by magnetic forces in the motor’s stator and rotor. These high-frequency signals were previously hard to detect and interpret. Now, WEG had detailed maps showing exactly where this energy was located.
By spotting these subtle patterns, engineers could better understand how magnetic effects turn into sound. This helps with both product design and noise control.
Vibration maps: full view (1216-3647Hz)
Vibration maps: full view (0-1166Hz)
Final Takeaways: Ommatidia LiDAR at WEG – Bringing NVH Engineering into the Field
Through these four demonstrations, the Q2 Laser RADAR showed how advanced vibrometry can work outside the lab. It wasn’t just precise—it was portable, fast, and easy to use.
Key benefits include:
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128 simultaneous laser beams cover large areas in one shot.
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Micron-level precision detects even tiny movements.
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Setup in under 30 minutes with battery compatibility.
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No impact from EMI or ambient lighting.
More importantly, it changes how engineers work:
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Find and fix vibration issues before they become failures.
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See how design choices affect real-world behavior.
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Link mechanical data to acoustic noise more clearly.
For WEG and similar companies, tools like the Q2 offer a smarter way forward. They help engineers stay ahead of problems and deliver quieter, more reliable machines.
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