Application: Presence Verification

Inspection Challenge:

A manufacturer of fighter planes needed to examine the wing of an F15 fighter. Twelve different types of fasteners had to be identified and their presence verified. The manufacturer also needed to know the X-Y co-ordinates of the fasteners to make sure that they were in the correct position.

Need to Assess:

• Which fastener is in view of the camera (in multiples of four if necessary).
• Give X and Y co-ordinates of the centroid of the fastener.
  

Machine Vision Solution:

The following DT Vision Foundry Tools were added to the Point and Click Script to solve this inspection challenge:

• AVI Player Tool – This tool is showing a variety of images for quick display purposes. Normally this tool will be replaced with the Picture Tool, which takes the image of the product in order for the measurements to be processed.
• Open ROI Tool – This opens the ROI (Region of Interest) where the system will complete the calculations.
• Image Classifier Tool – This tool will have images of all the differing types of fasteners, and when a fastener passes underneath the camera, the Image Classifier Tool will give the user the correct fastener in any rotation.
• Blob Analysis Tool - This tool uses 78 different statistics to pick up on any figure. In this case, the tool will be used to threshold the ROI to check the outline of the fastener, and look for the centroid of the fastener. This information is passed through the Serial I/O Tool.
• ROI Shape Fitter – This tool displays the centroid of the fastener.
• Text Tool – This tool displays the results of the test.
• Status Tool – This tool also displays the PASS/FAIL results and will also show the pass/fail rate, variables and will also save any images either passed or failed to a folder for later failure analysis to be completed.

The screen shot below shows that the image has been captured from a camera and has been displayed upon the screen in a view port. The screen first shows that the Image Classifier Tool has found the correct fastener and has displayed the results on the screen. The Blob Analysis Tool then thresholds the ROI to achieve all the statistics needed within that ROI to calculate the centroid of the fastener.

The Image Classifier Tool will then use the same ROI to check the catalogue of images it has in its memory to tell the vision system which fastener is being presented underneath the camera. The result of this can be displayed on the screen.

The screen above shows another fastener has come into view and the system has correctly identified the fastener and has reported the central co-ordinates for this specific type. The accuracy of this is really down to the pixel array on the camera.

The screen below shows the user that there is a very good GUI (Graphical User Interface) available within the package. This Status Tool shows the user all the vital information that is needed for the quality inspection of their product to be as efficient as possible.

The statistics, which are shown, are as follows:

• Pass or Fail sign (green or red respectively).
• Pass/Fail percentages.
• Variables that the user is looking for.
• The ability to save all the statistics and pass/failed images for later failure analysis inspection.
• Warnings, e.g. in case there are five failures consecutively.

This routine will continue to check the different fasteners until the user/programmer is satisfied that the job is done and then if needed then the system can be used for checking a variety of many other products.

From then on, there are a number of scenarios that can be implemented. The Digital I/O Tool can signal the user’s PLC to operate a robot to discard the failed articles and to let the passed articles continue down the production line.

The I/O tool can even make the production line stop if there are any faults found with the products that are being checked.

Result:

The Data Translation machine vision solution automated the inspection process, resulting in improved quality and efficiency for the manufacturer.