Usage of scanning coordinate-measuring machines for inspection of screw threads has become a common practice nowadays. Compared to touch trigger probing, scanning capabilities allow to speed up measuring process while still maintaining high accuracy. However, in some cases accuracy drasticaly depends on the scanning speed. In this paper a compensation method is proposed allowing to reduce the influence of some dynamic effects while scanning screw threads on coordinate-measuring machines.
Due to inertial forces while high-speed scanning freeform workpieces with low radius of curvature on coordinate-measuring machines it is difficult for the control software to maintain stable contact between the probe and the surface. This is one of the reasons preventing accurate scanning at high speeds @cite_2 . The study of dynamic effects was conducted by many researchers. Application of signal analysis and processing theory to dimensional metrology was studied in @cite_4 . Pereira and Hocken @cite_2 proposed classification and compensation methods for dynamic errors of scanning coordinate-measuring machines. They used Taylor series and Fourier analysis to compensate measurement of circular features. ISO 10360 @cite_9 defines acceptance tests for scanning coordinate-measuring machines. Farooqui and Morse @cite_5 proposed reference artifacts and tests to compare scanning performance of different coordinate-measuring machines. @cite_12 conducted experimental research and concluded that freeform surfaces scanning time reduction is limited at high speeds by acceleration and deceleration of the probing system.
@cite_4 @cite_9 @cite_2 @cite_5 @cite_12
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Coordinate measuring machines (CMMs) with continuous-contact scanning capabilities are experiencing more and more use in a wide variety of discrete-part manufacturing industries. Many users of these CMMs, if asked, will say that their metrology requirements include high density scans at high speeds with high accuracy. These requirements are in conflict, as there will be some point at which the accuracy of the scanned data begins to decrease with an increase in the scanning speed. This paper addresses the effects of scanning speed on the performance of different CMMs using contact sensors. The use of a family of artifacts is proposed in order to evaluate the relative scanning performance as a function of scanning speed and the direction of the scan within the CMM volume. The artifacts that are developed for these tests have a sinusoidal waveform superimposed on a flat surface. This paper describes a series of experiments that utilize these artifacts and assess the ability of these tests to capture how a scanning CMM will perform when measuring actual parts. The necessity for reducing production cycle times while achieving better quality compels metrologists to look for new and improved ways to perform the inspection of parts manufactured. The advent of coordinate measuring machines led to a significant boost in accuracy, flexibility and reliability for measurement tasks. However, these machines are in some instances lagging behind machine tools and need improvement. One major limitation is the execution of measurements with low uncertainty at a reasonably fast rate to make it possible to measure more parts. This would ensure more reliability to the end product and better information to control the manufacturing process. Coordinate measuring machines with scanning capabilities offer the option to output high data density for parts at high speed. However, they are still considerably less accurate at faster measurement speeds and need to be improved. In this work a scanning measuring machine was extensively tested and a compensation model that accounts for part of its dynamic errors affecting measurement of circular features is proposed. Common usage of Coordinate Measuring Machines in industry means that they are applied not only for the measurement of the details, but also for the digitalization of the geometrical elements. Nowadays, the development of scanning methods enables the easy measurement of free surfaces. Digitalization of such surfaces with scanning probe heads is much faster than touch trigger probing, while the uncertainty level remains almost the same. However, the accuracy of points localization is dependent upon the scanning speed. We propose a new approach to appearance-based loop detection for mobile robots, using three-dimensional (3D) laser scans. Loop detection is an important problem in the simultaneous localization and mapping (SLAM) domain, and, because it can be seen as the problem of recognizing previously visited places, it is an example of the data association problem. Without a flat-floor assumption, two-dimensional laser-based approaches are bound to fail in many cases. Two of the problems with 3D approaches that we address in this paper are how to handle the greatly increased amount of data and how to efficiently obtain invariance to 3D rotations. We present a compact representation of 3D point clouds that is still discriminative enough to detect loop closures without false positives (i.e., detecting loop closure where there is none). A low false-positive rate is very important because wrong data association could have disastrous consequences in a SLAM algorithm. Our approach uses only the appearance of 3D point clouds to detect loops and requires no pose information. We exploit the normal distributions transform surface representation to create feature histograms based on surface orientation and smoothness. The surface shape histograms compress the input data by two to three orders of magnitude. Because of the high compression rate, the histograms can be matched efficiently to compare the appearance of two scans. Rotation invariance is achieved by aligning scans with respect to dominant surface orientations. We also propose to use expectation maximization to fit a gamma mixture model to the output similarity measures in order to automatically determine the threshold that separates scans at loop closures from nonoverlapping ones. We discuss the problem of determining ground truth in the context of loop detection and the difficulties in comparing the results of the few available methods based on range information. Furthermore, we present quantitative performance evaluations using three real-world data sets, one of which is highly self-similar, showing that the proposed method achieves high recall rates (percentage of correctly identified loop closures) at low false-positive rates in environments with different characteristics. © 2009 Wiley Periodicals, Inc.