For the varying size of the aerospace parts and reflective surface, it is a challenge to build an image acquisition system. Image acquisition is a very crucial part of automated visual inspection powered by AI. It helps to create a real-world dataset of images in order to accomplish the subsequent operation i.e. image processing.
To Acquire the best possible images of the manufactured aerospace parts with varying sizes (77mm to 110mm) like Latches, Retainers, and Trims and store the image dataset into QEC (Qualitas EagleEye® Cloud). This image dataset will further be used to train the customer’s AI model for inspection and other purposes.
HOW IS THIS PROBLEM BEING ADDRESSED CURRENTLY?
The inspection was being carried out manually to identify the parts and distribute them to the right trays/containers.
WHY IMAGE ACQUISITION IS REQUIRED?
Any AI-based image processing is heavily reliant on image data. So clearer the images, the easier it is to train to ensure system accuracy
HOW IMAGE ACQUISITION SYSTEM CAN SOLVE THIS PROBLEM?
A setup is built with a camera(s) with the right lens configuration for adequate resolution. Integrated lights are used to illuminate the area of interest. A proximity sensor is used to trigger the image acquisition mechanism in order to acquire the images of the products and transfer them to the QEC(Qualitas EagleEye® Cloud) via an interface
In this particular case, two image acquisition systems (Table Top) have to be developed with different configurations as there are two different working distances depending on the size of the parts. To trigger the acquisition process a push button will be connected to the system.