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Supporting Multi-Sensor Ring Layouts with 3D Laser Line Profilers

Supporting Multi-Sensor Ring Layouts with 3D Laser Line Profilers

Many scanning applications require shape data for 360º of a part, while others only need one view that captures a specific feature of a part. For 360º support, a multi-sensor ring layout is an ideal solution. In this setup, the sensors are positioned around a part to capture its entire circumference.


360º Ring Layout
Fig. 1 Ring layout with 360º scan view using Gocator’s Profile Closed Area tool.

As the part moves through the sensor ring, data is “stitched” into a complete 3D model to provide accurate volume measurement. Protein portioning is an example of an application that requires this type of layout.

Protein Portioning

A slab of protein (e.g., meat, cheese) moves through a ring of laser line profile sensors. Each scan is used to calculate the cross-sectional area. Combining the areas provides you with the volume measurement of the protein slab. If you wanted to cut the slab into smaller portions with a specified target weight, all you would have to do is multiply the volume data by the average density of the protein, then set the cutter to activate upon reaching the threshold weight value.

Protein portioning process
Fig. 2 A slab of protein is scanned to determine total volume and communicate optimal downstream cutting decisions.

Aligning to a Common Coordinate System

In supporting multi-sensor ring layouts, all sensors in the network must first be aligned to a common coordinate system in order to determine relative position. This is usually accomplished by introducing a known shape (such as a 4-sided polygon) into the scan plane. Each sensor “sees” one of the vertices of the polygon. A smart sensor can then calculate each sensor’s position and transform data into a common coordinate system. This transformation is carried out automatically for every 3D point produced by the sensor.

Sensor calibration to a common coordinate system
Fig. 3 Sensor alignment using a four-sided polygon, with four sensors looking at each vertex.

The transformed data from the sensors form a 3D point cloud. This point cloud requires processing to calculate measurements such as cross-sectional area. Scripting can be used to accumulate areas and trigger downstream control decisions to activate cutters upon reaching target weights.

Gocator Firmware 5.0

Ring layouts will be fully supported in our upcoming Gocator firmware 5.0 public release, including alignment and cross-sectional area measurement to build a smart portioning sensor out-of-the-box!

We invite you to subscribe to our Digital Hub to receive updates on the Gocator firmware 5.0 release. You can also subscribe to our YouTube channel to receive notification when the new Gocator 5.0 firmware videos are available. These videos showcase 5.0's new features including ring layout, a new High-definition 3D data visualizer, expanded alignment with 6 degrees of freedom (DoF), and more!

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