ai-quanton GmbH

What measurement principle does ParticleTensorAI use?

ParticleTensorAI evaluates time-resolved light-scattering signals generated by droplets or particles as they pass through an optical measurement volume. An optical probe illuminates the measurement region. When droplets or particles cross the light beam, they scatter light. Fast optical detectors then record the resulting signals. The underlying optical measurement setup can use the TSTOF measurement principle.

How does ParticleTensorAI analyze the signals?

ParticleTensorAI converts recorded signal sequences into multidimensional data structures called tensors. For example, the system can arrange several detector signals in separate channels. It can then transform a defined time window into an image-like tensor. A neural network analyzes this tensor and searches for characteristic signal patterns.

What does trigger-free analysis mean?

Classical counting methods often require a trigger threshold to identify individual droplet events. However, this can become difficult when signals overlap or when the spray contains many droplets. ParticleTensorAI can analyze complete buffered signal sequences without detecting every signal event separately first.

What can ParticleTensorAI measure?

The available results depend on the optical setup, the recorded training data, and the selected AI model.

What do the optical measurement probes look like?

ai-quanton develops and manufactures the optical measurement probes in-house. We can adapt the probe geometry and optical configuration to the required measurement task. For example, the probes can differ in: working distance, measurement volume, number of detectors, detector arrangement, laser power, optical access, mechanical design, installation position.