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Reliable and precise straightness profile measurements are crucial for manufacturing ultra-precision components and are capable of further enhancing their accuracy. The Fourier three-probe (F3P) straightness measurement allows for precise assessment of the workpiece profile on the machine by eliminating the harmful influence of the error motion of the sliding table. However, the probe spacing uncertainty deteriorates the measurement accuracy remarkably; and, the affecting mechanism behind this phenomenon has not yet been studied in detail. In this context, this paper thoroughly investigated the propagation of the probe spacing uncertainty in the F3P measurement. First, the influence of the probe spacing deviation is analyzed. Next, by calculating the partial differential of Laplace transform of the workpiece profile, we algebraically deduce the probe spacing uncertainty propagation law, especially in the harmonic domain. Subsequently, Monte Carlo simulations are carried out to confirm the derived propagation law. To reduce uncertainty propagation, a hybrid approach is presented: (I) F3P measurements are carried out under changing probe spacings to produce several sets of Fourier coefficients; (II) optimal harmonic estimates are selected individually according to the harmonic uncertainty. Finally, simulations and experimental measurements are performed for verification., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

The efficient computation of viewpoints for solving vision tasks comprising multi-features (regions of interest) represents a common challenge that any robot vision system (RVS) using range sensors faces. The characterization of valid and robust viewpoints is even more complex within real applications that require the consideration of various system constraints and model uncertainties. Hence, to address some of the challenges, our previous work outlined the computation of valid viewpoints as a geometrical problem and proposed feature-based constrained spaces (C-spaces) to tackle this problem efficiently for acquiring one feature. The present paper extends the concept of C-spaces to consider multi-feature problems using feature cluster constrained spaces (GC-spaces). A GC-space represents a closed-form, geometrical solution that provides an infinite set of valid viewpoints for acquiring a cluster of features satisfying diverse viewpoint constraints. Furthermore, the current study outlines a generic viewpoint planning strategy based on GC-spaces for solving vision tasks comprising multi-feature scenarios effectively and efficiently. The applicability of the proposed framework is validated on two different industrial vision systems used for dimensional metrology tasks.

Digital twins of measurement systems are used to estimate their measurement uncertainty. In the past, virtual coordinate measuring machines have been extensively researched. Research on digital twins of optical systems is still lacking due to the high number of error contributors. A method to describe a digital twin of an optical measurement system is presented in this article. The discussed optical system is a laser line scanner mounted on a coordinate measuring machine. Each component of the measurement system is mathematically described. The coordinate measuring machine focuses on the hardware errors and the laser line scanner determines the measurement error based on the scan depth, in-plane angle and out-of-plane angle. The digital twin assumes stable measurement conditions and uniform surface characteristics. Based on the Monte Carlo principle, virtual measurements can be used to determine the measurement uncertainty. This is demonstrated by validating the digital twin on a set of calibrated ring gauges. Two validation tests are performed: the first verifies the virtual uncertainty estimation by comparison with experimental data. The second validates the measured diameter of different ring gauges by comparing the estimated confidence interval with the calibrated diameter.

Surface topography measurements are vital in industrial quality control. Linear roughness measurements are among the most preferred methods, being quick to perform and easy to interpret. The ISO 16610 standard series prescribes filters that can be used for most cases, but has limitations for restricted measurement lengths. This is because the standard filter type is a Gaussian filter, which like most instances of kernel convolution filters has no output near the edges of the profile, effectively shortening the length of the filtered output profile as compared to the input. In some cases, this leads to a lack of representative data after filtration. Especially in fields such as Additive Manufacturing (AM) this becomes a problem, due to the high "roughness to measurable data length"-ratio that characterizes complex AM parts. This paper describes a method that allows to overcome this limitation:•A method for circular padding of short measured tracks is described and validated.•A flexible profile data post-processing tool was developed in MATLAB to grant users more control over the data analysis. Results obtained from roughness profiles long enough for normal ISO procedures are shown to not change significantly when circularly padded. When only a shorter section of the data is available, where the standard protocol would not be able to compute a filtered profile and related parameters anymore, the circular padding method is shown to lead to results that are in good agreement with the ISO standard procedures., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 The Authors. Published by Elsevier B.V.)

Optical measurement and characterization are two of the pillars of metrology. The ability to measure precisely with high dynamic range and accuracy betters our understanding of nature and the universe. In this feature issue, we present a collection of articles that delves into the fundamental techniques used to advance the field.

Displacement measuring sensors play an essential role in all aspects of dimensional metrology. They can be used for direct displacement measurements but more often they are part of a measurement system, such as an atomic force microscope, roughness tester or a coordinate measuring machine (CMM). In order to achieve traceable measurements that can be related to the meter, these sensors must be calibrated against a reference standard that is more noise- and error-free than the sensor under test. A description of the various methods to achieve the ultimate traceability, repeatability and accuracy of such a calibration system is the main part of this paper. Various interferometric methods will be reviewed including several methods that use directly a primary standard as a reference: either an iodine-stabilized laser or a frequency comb. It is shown that various methods exist to quantify or mitigate the periodic errors that are inherent to interferometric methods. Also it is shown that knowledge of this periodicity may lead to a separation of periodic and non-periodic non-linearity errors of both the calibration instrument as the sensor under test. This review is limited to small-range sensors, typically with a range <100 μm. It is concluded that today's technology enables sound and traceable sensor calibration up to the sub-nano and even picometer level of uncertainties., Competing Interests: The author declares no conflict of interest.

Displacement laser interferometer systems are widely used for the calibration of machine tools and CMMs (Coordinate Measuring Machines). Additionally, they are often the workhorse in dimensional calibration laboratories, where they act as the basic metrological traceability link for many calibrations. This paper gives a review of the calibration of such systems, where several approaches, such as the calibrations of separate components or the system as a whole, are reviewed. The calibrations discussed are: the laser frequency, the counting system, software evaluation of the environmental conditions, environmental and material temperature sensor calibration and the calibration of optics that is part of the system. For these calibrations considerations are given about the ways these can be carried out and about establishing the re-calibration intervals., Competing Interests: The author declares no conflict of interest.

Objective: To describe the anesthetic management of a dog undergoing caudal vena cava (CVC) occlusion during adrenalectomy, and to discuss a reflex bradycardia that was observed during the procedure., Case Summary: General anesthesia of a 10-year-old Rhodesian ridgeback for excision of an adrenal mass and associated CVC tumor thrombus was performed. The dog was premedicated with IV methadone and anesthesia was induced with IV alfaxalone and maintained with isoflurane in 100% oxygen. An IV remifentanil infusion was administered for intraoperative analgesia. Surgical removal of the thrombus necessitated temporary complete occlusion of the CVC. During CVC occlusion an acute paradoxical bradycardia occurred, which was successfully treated with IV atropine. The cardiovascular change resembled a Bezold-Jarisch or reverse Bainbridge reflex, and was believed to be mediated by cardiac mechanoreceptors following the sudden decrease in preload. Increased myocardial contractility subsequent to increased sympathetic nervous system activity may also have contributed. A decrease in urine output was observed following CVC occlusion but had returned to normal 2 hours following the end of anesthesia. Recovery from anesthesia was otherwise uneventful., New or Unique Information Provided: Although the mechanism is unclear, a paradoxical bradycardia may occur during complete CVC occlusion in the dog. Factors that increase sympathetic nervous system outflow, such as administration of dopamine, may have contributed to the occurrence of the reflex., (© Veterinary Emergency and Critical Care Society 2017.)

Regional finite-difference models often have cell sizes that are too large to sufficiently model well-stream interactions. Here, a steady-state hybrid model is applied whereby the upper layer or layers of a coarse MODFLOW model are replaced by the analytic element model GFLOW, which represents surface waters and wells as line and point sinks. The two models are coupled by transferring cell-by-cell leakage obtained from the original MODFLOW model to the bottom of the GFLOW model. A real-world test of the hybrid model approach is applied on a subdomain of an existing model of the Lake Michigan Basin. The original (coarse) MODFLOW model consists of six layers, the top four of which are aggregated into GFLOW as a single layer, while the bottom two layers remain part of MODFLOW in the hybrid model. The hybrid model and a refined "benchmark" MODFLOW model simulate similar baseflows. The hybrid and benchmark models also simulate similar baseflow reductions due to nearby pumping when the well is located within the layers represented by GFLOW. However, the benchmark model requires refinement of the model grid in the local area of interest, while the hybrid approach uses a gridless top layer and is thus unaffected by grid discretization errors. The hybrid approach is well suited to facilitate cost-effective retrofitting of existing coarse grid MODFLOW models commonly used for regional studies because it leverages the strengths of both finite-difference and analytic element methods for predictions in mildly heterogeneous systems that can be simulated with steady-state conditions., (© 2015, National Ground Water Association.)