The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The problem stated is there is no reliable in-service inspection method that quickly and easily detects the composite material damage. The aerospace industry needs to make efficient use of the inspections to turn the aircraft around in an efficient timeframe. This paper discusses the methodology for semi-automatic visualization of the process of inspecting composite materials for damage. The research is focused on the application of inspection of composite damage in aircrafts using Light Detection and Ranging (LIDAR). Two configurations using the LIDAR is discussed in determining damage to an aircraft. The configurations are derived from several studies using smaller aircraft parts and a small autonomous RMax helicopter. This study helps provide a solution for a quick turnaround and an efficient scan of the possible composite damage in aircraft. The four primary objectives are: Objective 1: Determine whether semi-automated three-dimensional visualization composite inspection techniques are as effective as experienced human inspectors in locating potential composite damage. Objective 2: Determine whether data from several Light Detection and Ranging (LIDAR) cameras can be combined for use in conducting semi-automated three-dimensional visualization composite inspections. Objective 3: Determine whether LIDAR camera scans can be performed on a moving aircraft for use with semi-automated three-dimensional visualization composite inspections. Objective 4: Assess the important human factors contributors associated with interpreting the LIDAR camera scan data.