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ARIS Web Position Sensor for Contrast/Line Detection

ARIS Web Position Sensor (WPS) can use either infrared (IR) light or white light (WL) to detect the position of a web material. The ARIS WPS with the WL option uses a revolutionary technology based on fiber optics to accurately determine the position of an edge defined by the contrast between two different web materials irrespective their properties. This sensing principle is unique and provides a true, absolute web position measurement. The working principle of the sensor is as follows. Light from an array of white LEDs is projected on to the web surface. The light that intercepts the web is scattered in all directions, spatially filtered using the fiber optic array within the sensor. The filtered light is then projected on to a camera sensor. The edge position, which is defined by the contrast between the two web layers, is determined by processing the output of the camera sensor using sophisticated digital signal processing algorithms in real-time. The algorithm automatically adjusts for the contrasts and is unaffected by the ambient lighting conditions. Essentially, the web guide sensor calibrates itself continuously.

Sensor Specification

Two sensor widths currently available with the WL option: 16 mm and 48 mm (see Figure 1).

Figure 1: The two sensor options with 16mm and 48 mm web position sensors

The sensor head includes a light diffuser, a spatial optical filter, a camera sensor and white LED light source. The camera sensor has a resolution of 63.5 micron with 256 or 768 pixels based on sensor width. Because of the computational complexity the signal from the camera sensor needs to be processed with a dedicated sensor processing unit, which is located remotely from the sensor head. Up to 5 m long cable can be used with the web guide sensor head enabling remote installation of the sensor head from the sensor processing unit.

Sensor Performance: Experimental Procedure

In this white paper, we shown experiments with six types of composite webs with different substrates (see Figs. 2(a) – 2(f)) to highlight the sensor’s ability to work with different web materials with contrasting properties.

Figure 2: Set of six labels with different substrates.

The composite web consist of a clear carrier film that supports the printed label web. Three substrates with varied optical properties are used for the printed label web. These substrates are white, metallic and clear. The printing on the six labels are also different, and the contrast between labels are substantially different. The sensor measures the position of the die cut edge of the label, which is essentially the edge of the contrast between the clear carrier film and the printed label substrate. Common issues with these substrates on a clear carrier film are mainly the low contrast levels between the substrates, the contrast difference within the labels and the carrier film, and the reflective properties of the substrate. The experimental results show the effectiveness of the signal processing algorithm to overcome these limitations.

An experimental setup (see Figure 3) equipped with a high precision motor stage, which moves the web material back and forth is used to quantify the web guide's sensor performance.

Figure 3: High precision motor stage with a c-shaped fixture to hold the web material. A web guide sensor mount with an option to mount 16 mm and 48 mm web guiding sensor at a working distance of<br />
10 mm.

A set of experiments are done with each sample, where the web on the motor stage is moved back and forth several times (as shown in Figure 4) , recording the motor position and sensor edge position data.

Figure 4: Experimental procedure where the web mounted on the c-shaped fixture is moved back and forth several times with a constant velocity. The abscissa shows time in seconds and ordinate shows the sensor measurement in mm.

Figs. 5 – 10 shows a representative sample of experimental results with 16 mm sensor for the six samples.

 Figure 5: Results with white substrate (Sample 1). Average Slope - 1.00484; Average Bias- 0.04351; Average R2- 99.96%. The results show excellent precision and accuracy of the web guiding sensor.

Figure 6: Results with white substrate (Sample 2). Average Slope - 1.00809; Average Bias- 0.05035; Average R2 - 99.98%. The results show excellent precision and accuracy of the web position sensor.<br />

Figure 7: Results with white substrate (Sample 3). Average Slope - 1.00961; Average Bias- 0.01856; Average R2- 99.98%. The results show excellent precision and accuracy of the web position sensor.

Figure 8: Results with metallized substrate (Sample 1). Average Slope - 0.99834; Average Bias - 0.06170; Average R2- 99.94%. The results show excellent precision and accuracy of the web guiding sensor.

Figure 9: Results with metallized substrate (Sample 2). Average Slope - 0.98202; Average Bias - 0.17654; Average R2- 99.94%. The results show excellent precision and accuracy of the web guiding sensor.

Figure 10: Results with clear substrate. Average Slope - 0.98589; Average Bias - 0.01496; Average R2 - 99.98%. The results show good precision and accuracy of the sensor.

Six sets of data were collected by positioning the motor stage to move back and forth three times. The step size and the motor speed was chosen such
that every single pixel is covered during every experiment. Data from all six experiments are superimposed into a single plot. The abscissa shows the web displacement measured using the motor position sensor. The ordinate shows the web edge measured using our web guide sensor. Both the axes are represented in millimeters. The blue dots in the plots are the actual measured data and the green lines are the linear fit for each set of experiment.

The table shows the parameters for the linear fit to the data from each experiment. All the experiments showed excellent precision, accuracy and linearity of the sensor (and the sensing principle) irrespective of the optical properties of the substrate. No calibration or any type
of adjustment was made to the sensor between these experiments. Moreover, the ambient light conditions did not affect the sensor accuracy, precision or linearity.

Conclusions

The experimental results show the accuracy and precision of the sensor is unaffected by the material properties unlike conventional sensors which are affected by contrast. The sensor accurately measures the web edge position defined by the contrasting materials, irrespective of the substrate and without need for any teaching procedures.

In Addition

Check out our video to see these results in action.
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