Fast in-situ tool inspection based on inverse fringe projection and compact sensor heads

Abstract

Inspection of machine elements is an important task in production processes in order to ensure the quality of produced parts and to gather feedback for the continuous improvement process. A new measuring system is presented, which is capable of performing the inspection of critical tool geometries, such as gearing elements, inside the forming machine. To meet the constraints on sensor head size and inspection time imposed by the limited space inside the machine and the cycle time of the process, the measuring device employs a combination of endoscopy techniques with the fringe projection principle. Compact gradient index lenses enable a compact design of the sensor head, which is connected to a CMOS camera and a flexible micro-mirror based projector via flexible fiber bundles. Using common fringe projection patterns, the system achieves measuring times of less than five seconds. To further reduce the time required for inspection, the generation of inverse fringe projection patterns has been implemented for the system. Inverse fringe projection speeds up the inspection process by employing object-adapted patterns, which enable the detection of geometry deviations in a single image. Two different approaches to generate object adapted patterns are presented. The first approach uses a reference measurement of a manufactured tool master to generate the inverse pattern. The second approach is based on a virtual master geometry in the form of a CAD file and a ray-tracing model of the measuring system. Virtual modeling of the measuring device and inspection setup allows for geometric tolerancing for free-form surfaces by the tool designer in the CAD-file. A new approach is presented, which uses virtual tolerance specifications and additional simulation steps to enable fast checking of metric tolerances. Following the description of the pattern generation process, the image processing steps required for inspection are demonstrated on captures of gearing geometries. © 2016 SPIE.