Fluorescence imaging is a powerful tool to detect the presence of processing agents, e.g., oils, lubricants, and organic coatings on metal surfaces. This imaging technique can be used in production, e.g. to determine the oil coverage on sheet metal to assure the best forming results or for inspecting the cleanliness of components before further processing like gluing, welding, coating, etc. The presented sensor is an evolution of the existing fluorescence laser scanner (F-Scanner) system1 and is optimized for measurement in motion. Adding this additional degree of freedom by mounting the scanner on a robot or gantry enables complete scans of large and complex shaped parts as well as selected areas that require special care, e.g., an increased level of cleanliness. The F-Scanner system has been improved in terms of footprint, weight, durability, and robustness. It can be operated with lightweight industrial robots and even cobots. In situations where ambient light makes fluorescence imaging challenging, a fast Fourier transform (FFT) based technique is used to ensure unperturbed measurements and high-contrast images. This work gives an overview of the advanced developments made and demonstrates the effect of FFT signal processing.
We present new imaging techniques for the detection and classification of particulate contamination on structured surfaces. This allows for cleanliness inspection directly on the sample. Classical imaging techniques for particle detection, such as dark-field imaging, are typically limited to flat surfaces because structures, scratches, or rough surfaces will give similar signals as particles. This problem is overcome using stimulated differential imaging. Stimulation of the sample, e.g. by air blasts, results in displacement of only the particles while sample structures remain in place. Thus, the difference of images before and after stimulation reveals the particles with high contrast. Cleanliness inspection systems also need to distinguish (often harmful) metallic particles from (often harmless) nonmetallic particles. A recognized classification method is measuring gloss. When illuminated with directed light, the glossy surface of metallic particles directly reflects most parts of the light. Non-metallic particles, in contrast, typically scatter most of the light uniformly. Here, we demonstrate a new imaging technique to measure gloss. For this purpose, several images of the sample with different angles of illumination are taken and analyzed for similarity.
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