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Innovative quality inspection methods for CFRP primary structural parts

Periodic Reporting for period 1 - SonicScan (Innovative quality inspection methods for CFRP primary structural parts)

Reporting period: 2019-04-01 to 2020-09-30

The SonicScan project aims at developing NDT methods based on ultrasonic testing that are suitable for primary structural parts. The main challenge is the compact shape of the parts and their high thickness. To address this problem the project will build upon the sampling phased array technology that allows the tomographic inspection of parts and combine it with a robotic handling system to move the sensor across the part. Particular emphasis will be put on the model-based, automatic planning of the robot's inspection path to ensure that all elements of the part are inspected. This will be based on methods developed by the project partners for image-based surface inspection robots and they will be adapted to volumetric inspection methods. Data analysis for automatic defect detection, segmentation and classification will be developed, including machine learning methods such as random forests. The main result of the project will be an integrated inspection robot that will be demonstrated on landing gear components.

The technologies developed in the project will have impact on the manufacturing of structural composite parts, in particular on their quality control in series production, and on the efficient deployment of ultrasonic inspection robots, by increasing the usability of such robots through automatic adaptation to new part designs. SonicScan aims at two main objectives:
(A) Enhanced methods for ultrasonic testing and data analysis, building upon recent advances in the sampling phased array technology including 3D reconstruction and data analysis methods based on machine learning.
(B) Automatic methods for planning of inspection tasks in robotic systems to ensure automatic and cost-efficent inspection. This will be achieved by including a physical inspection process model to generate an automatic inspection path from a CAD model of the part.
Since the beginning of the project, a robotic work cell for ultrasonic inspection was installed in the laboratory at Profactor. This work cell serves as a demonstrator for technology developed within the project. A set of test specimens were provided by the topic manager. These were used in a first round of trials in order to test the newly developed inspection workflow. ACS focused on implementation of advanced data processing for use with the phased array technology. Volumetric data reconstruction from phased array scans was implemented and showed good results on moderately curves surfaces. For the remainder of the project, this technology will be further enhanced and more challenging cases will be addressed. Profactor was mostly involved in development of path planning algorithms. There is a set of challenges that were tackled in this context: Optimal positioning of the ultrasonic inspection head, collision avoidance, complex robot motions for connecting individual regions that need to be scanned.
The project is on the way to go beyond the state of the art for the following items:
(1) Reconstruction technology for ultrasound data acquired with the full matrix capture (FMC) method will be developed. Adaptive methods are applied here that target the maximum out of the acquired data.
(2) Automatic path planning algorithms are developed that enable
(3) The use of deep learning methods for evaluation of ultrasonic scan data is investigated.
We expect that all three technologies will have a significant impact that goes beyond the specific application of ultrasonic testing and quality control for carbon fiber re-inforced polymers. Other applications where the SonicScan technology will have an impact are different ultrasound-based quality control tasks and automated analysis of robotic scanning data via machine learning in general. Path planning capabilities, as developed within the project are expected to enable more flexibility of robots to automate inspection processes and in increase flexibility in general. We expect that this will have a positive impact on the digital transformation of European economy.