Development of an Automated Laser Depaint System, 10-R8155
Principal Investigators
Dan H. Weissling
Michael P. Rigney
Michael O. Blanton Jr.
Inclusive Dates: 06/03/10 – 03/01/11
Background — Laser paint removal has the potential to become the process of choice for a number of industries. The advantages of laser coating removal include reduced waste stream volume, lower maintenance and lower power consumption. Although these advantages were recognized two decades ago, the ability to deliver sufficient laser power to the end effector of an extended-reach robotic system, suitable for whole-aircraft paint removal, has only recently become feasible with the maturity of fiber lasers. In addition, this type of laser offers power control capability appropriate to prevent damage to sensitive substrates and enable selective coating removal. Though manual open-loop testing is showing good results, the key to the success of an automated system is closed-loop sensing/control of the process.
The purpose of this project was to develop a control solution comprised of sensors and data analysis software to measure the coating removal state and provide real-time feedback to modulate laser power. This closed-loop control system was then integrated with a commercial fiber laser into a custom robotic platform.
Approach — This project developed a real-time, closed-loop control system that used machine vision to characterize the target surface, and then provided a control signal to modulate a laser power source. A high frame rate color camera and a filtered monochrome camera were used to provide RGB and NIR spectral data for real-time analysis of the coating removal process. The two cameras were optically aligned via a beam splitter, and software controls allowed for fine-tuning to match the field of view of both cameras. Images were acquired at twice the rate of the laser raster period. This allowed alternate analysis of the left and right image fields, which were synchronized with the laser position. Subsequent analysis and spectral classification were used to identify coating versus substrate and to modulate the laser power to precisely control the coating removal process.
Work was executed in two phases. Phase 1 developed and validated the sensor/control system, and Phase 2 integrated the new technology into a large-scale coating-removal robotic platform at SwRI to validate and demonstrate system capability.
Accomplishments — This program successfully developed a sensor package that provided operational coating/substrate discrimination for high-contrast combinations in the presence of brightly incandescing laser/coating interactions and smoke. Using commercial-off-the-shelf equipment, acquisition and analysis of image data and communicating laser control data at rates of 600Hz and 300Hz were achieved.
