MScMS-II: an innovative IR-based indoor coordinate measuring system for large-scale metrology applications

According to the current great interest concerning large-scale metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance are assuming a more and more important role among system requirements. This paper describes the architecture and the working principles of a novel infrared (IR) optical-based system, designed to perform low-cost and easy indoor coordinate measurements of large-size objects. The system consists of a distributed network-based layout, whose modularity allows fitting differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load. The overall system functionalities, including distributed layout configuration, network self-calibration, 3D point localization, and measurement data elaboration, are discussed. A preliminary metrological characterization of system performance, based on experimental testing, is also presente

AAO Starbugs: software control and associated algorithms

The Australian Astronomical Observatory's TAIPAN instrument deploys 150 Starbug robots to position optical fibres to accuracies of 0.3 arcsec, on a 32 cm glass field plate on the focal plane of the 1.2 m UK-Schmidt telescope. This paper describes the software system developed to control and monitor the Starbugs, with particular emphasis on the automated path-finding algorithms, and the metrology software which keeps track of the position and motion of individual Starbugs as they independently move in a crowded field. The software employs a tiered approach to find a collision-free path for every Starbug, from its current position to its target location. This consists of three path-finding stages of increasing complexity and computational cost. For each Starbug a path is attempted using a simple method. If unsuccessful, subsequently more complex (and expensive) methods are tried until a valid path is found or the target is flagged as unreachable.Comment: 10 pages, to be published in Proc. SPIE 9913, Software and Cyberinfrastructure for Astronomy IV; 201

Alternative method for the metrological characterization of spur gears in the sub-millimeter range using optical equipment

The aim of this work is to develop a software that allows the inspection of spur gear manufactured in the sub-millimeter range. The measurements are made using a digital optical machine and using an analysis proprietary software implemented in Matlab®, which is able to handle images, captured using the digital optical machine. The software allows to evaluate the profile and pitch deviations as establish in the ISO/TR 10064-1:1992 standar

A Gaussian process and image registration based stitching method for high dynamic range measurement of precision surfaces

Optical instruments are widely used for precision surface measurement. However, the dynamic range of optical instruments, in terms of measurement area and resolution, is limited by the characteristics of the imaging and the detection systems. If a large area with a high resolution is required, multiple measurements need to be conducted and the resulting datasets needs to be stitched together. Traditional stitching methods use six degrees of freedom for the registration of the overlapped regions, which can result in high computational complexity. Moreover, measurement error increases with increasing measurement data. In this paper, a stitching method, based on a Gaussian process, image registration and edge intensity data fusion, is presented. Firstly, the stitched datasets are modelled by using a Gaussian process so as to determine the mean of each stitched tile. Secondly, the datasets are projected to a base plane. In this way, the three-dimensional datasets are transformed to two-dimensional (2D) images. The images are registered by using an (x, y) translation to simplify the complexity. By using a high precision linear stage that is integral to the measurement instrument, the rotational error becomes insignificant and the cumulative rotational error can be eliminated. The translational error can be compensated by the image registration process. The z direction registration is performed by a least-squares error algorithm and the (x, y, z) translational information is determined. Finally, the overlapped regions of the measurement datasets are fused together by the edge intensity data fusion method. As a result, a large measurement area with a high resolution is obtained. A simulated and an actual measurement with a coherence scanning interferometer have been conducted to verify the proposed method. The stitching result shows that the proposed method is technically feasible for large area surface measurement

Optical diffraction for measurements of nano-mechanical bending

Micromechanical transducers such as cantilevers for AFM often rely on optical readout methods that require illumination of a specific region of the microstructure. Here we explore and exploit the diffraction effects that have been previously neglected when modeling cantilever bending measurement techniques. The illumination of a cantilever end causes an asymmetric diffraction pattern at the photodetector that significantly affects the calibration of the signal in the popular optical beam deflection technique (OBDT). Conditions for optimized linear signals that avoid detection artifacts conflict with small numerical aperture illumination and narrow cantilevers which are softer and therefore more sensitive. Embracing diffraction patterns as a physical measurable allows a richer detection technique that decouples measurements of tilt and curvature and simultaneously relaxes the requirements on the alignment of illumination and detector. We show analytical results, numerical simulations and physiologically relevant experimental data demonstrating the usefulness of these diffraction features. We offer experimental design guidelines and identify and quantify possible sources of systematic error of up to 10% in OBDT. We demonstrate a new nanometre resolution detection method that can replace OBDT, where Frauenhofer and Bragg diffraction effects from finite sized and patterned cantilevers are exploited. Such effects are readily generalized to arrays, and allow transmission detection of mechanical curvature, enabling in-line instruments. In particular, a cantilever with a periodic array of slots produces Bragg peaks which can be analyzed to deduce the cantilever curvature. We highlight the comparative advantages over OBDT by detecting molecular activity of antibiotic Vancomycin, with an RMS noise equivalent to less than $2.5 \mu M$ (1.5 nm), as example of possible multi-maker bio-assays.Comment: 9 pages, 8 figure

Shape descriptors and statistical classification on areal topography data for tile inspection in tessellated surfaces

Verification of conformance to design specifications in production, and identification of defects related to wear or other damage during maintenance, are key metrological aspects that must be addressed for micro-scale tessellated surfaces. A new algorithmic approach is presented that operates on topography datasets as obtained by areal topography instruments. The approach combines segmentation algorithms with a novel implementation of the angular radial transform, originally adopted by the MPEG-7 standard, to implement shape descriptors and associated similarity metrics. Applications to the inspection and verification of laser-manufactured micro-embossing topographies are illustrated. The topographies are first segmented to extract the individual tiles; the tiles are then encoded through shape descriptors. Principal component analysis and cluster analysis are used to investigate the behaviour of the angular radial transform coefficients. Finally, an algorithmic classifier based on supervised learning (k-nearest neighbours) is implemented and shown to be effective at identifying defects and at discriminating between defect types

Multisensor data fusion via Gaussian process models for dimensional and geometric verification

An increasing amount of commercial measurement instruments implementing a wide range of measurement technologies is rapidly becoming available for dimensional and geometric verification. Multiple solutions are often acquired within the shop-floor with the aim of providing alternatives to cover a wider array of measurement needs, thus overcoming the limitations of individual instruments and technologies. In such scenarios, multisensor data fusion aims at going one step further by seeking original and different ways to analyze and combine multiple measurement datasets taken from the same measurand, in order to produce synergistic effects and ultimately obtain overall better measurement results. In this work an original approach to multisensor data fusion is presented, based on the development of Gaussian process models (the technique also known as kriging), starting from point sets acquired from multiple instruments. The approach is illustrated and validated through the application to a simulated test case and two real-life industrial metrology scenarios involving structured light scanners and coordinate measurement machines. The results show that not only the proposed approach allows for obtaining final measurement results whose metrological quality transcends that of the original single-sensor datasets, but also it allows to better characterize metrological performance and potential sources of measurement error originated from within each individual sensor

Better than a lens -- Increasing the signal-to-noise ratio through pupil splitting

Lenses are designed to fulfill Fermats principle such that all light interferes constructively in its focus, guaranteeing its maximum concentration. It can be shown that imaging via an unmodified full pupil yields the maximum transfer strength for all spatial frequencies transferable by the system. Seemingly also the signal-to-noise ratio (SNR) is optimal. The achievable SNR at a given photon budget is critical especially if that budget is strictly limited as in the case of fluorescence microscopy. In this work we propose a general method which achieves a better SNR for high spatial frequency information of an optical imaging system, without the need to capture more photons. This is achieved by splitting the pupil of an incoherent imaging system such that two (or more) sub-images are simultaneously acquired and computationally recombined. We compare the theoretical performance of split pupil imaging to the non-split scenario and implement the splitting using a tilted elliptical mirror placed at the back-focal-plane (BFP) of a fluorescence widefield microscope