Sheet metal strain analysis is an important tool to ensure products are manufactured within necessary tolerances. A common technique involves electrochemically etching a dark grid pattern of known size onto the flat sheet metal surface and then deforming the sheet. The change in the grid pattern after deformation can be used to calculate surface strain. The computer vision problem is to accurately detect the intersections of the grid pattern. To investigate this problem, a stereo camera system was designed and attached to a bridge style coordinate measurement machine. The stereo head consists of two high resolution monochrome CCD cameras mounted on a Renishaw PH10 motorized probe head that can be articulated into numerous, repeatable, preset positions. Stereo head calibration was achieved using Zhang’s technique with a planar target. Each probe position was calibrated using a global point set registration method to link coordinate systems. A novel approach to segmenting the grid pattern into squares involving region merging and watersheds is described. Grid intersections are determined to sub pixel accuracy and matched between images using a correlation based scheme. The accuracy of the system and experimental results are provided.
Laser trackers are precision measurement devices often used to measure parts too large for conventional Coordinate Measuring Machines (CMMs). Multiple laser trackers can be used simultaneously to increase the number of part features viewable and therefore available for measurement. Each laser tracker has its own coordinate system that is linked to the others through the measurement of common points. The process of registration uses these common points to bring all measurement data into a Common Coordinate System (CCS). Provided all measurements are in a CSS, any localized part feature measured by more than one laser tracker can benefit from sensor fusion. This process improves the measurement accuracy of a feature location by using the error information associated with each laser tracker. This paper describes the application of sensor fusion and registration algorithms to metrology. Testing of the registration and fusion algorithms is performed using an API laser tracker 2. The algorithms are being commercially implemented in the Maya Metrix Build!IT software.
Although initially the only Coordinate Measuring Machine (CMM) sensor available was a touch trigger probe, technological advances in sensors and computing have greatly increased the variety of available inspection sensors. Non-contact laser digitizers and analog scanning touch probes require very well tuned CMM motion control, as well as an extensible, open architecture interface. This paper describes the implementation of a retrofit CMM motion controller designed for open architecture interface to a variety of sensors. The controller is based on an Intel Pentium microcomputer and a Servo To Go motion interface electronics card. Motor amplifiers, safety, and additional interface electronics are housed in a separate enclosure. Host Signal Processing (HSP) is used for the motion control algorithm. Compared to the usual host plus DSP architecture, single CPU HSP simplifies integration with the various sensors, and implementation of software geometric error compensation. Motion control tuning is accomplished using a remote computer via 100BaseTX Ethernet. A Graphical User Interface (GUI) is used to enter geometric error compensation data, and to optimize the motion control tuning parameters. It is shown that this architecture achieves the required real time motion control response, yet is much easier to extend to additional sensors.
Conference Committee Involvement (1)
Sensors and Controls for Intelligent Manufacturing III