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A particle swarm algorithm-based identification method for the optimal measurement area of large coordinate measuring machines (CMMs) is proposed in this study to realize the intelligent identification of measurement objects and optimize the measurement position and measurement space using laser tracer multi-station technology. The volumetric error distribution of the planned measurement points in the CMM measurement space is obtained using laser tracer multi-station measurement technology. The volumetric error of the specified step distance measurement points is obtained using the inverse distance weighting (IDW) interpolation algorithm. The quasi-rigid body model of the CMM is solved using the LASSO algorithm to obtain the geometric error of the measurement points in a specified step. A model of individual geometric errors is fitted with least squares. An error optimization model for the measurement points in the CMM space is established. The particle swarm optimization algorithm is employed to optimize the model, and the optimal measurement area of the CMM airspace is determined. The experimental results indicate that, when the measurement space is optimized based on the volume of the object being measured, with dimensions of (35 × 35 × 35) mm3, the optimal measurement area for the CMM, as identified by the particle swarm algorithm, lies within the range of 150 mm < X < 500 mm, 350 mm < Y < 700 mm, and −430 mm < Z < −220 mm. In particular, the optimal measurement area is defined as 280 mm < X < 315 mm, 540 mm < Y < 575 mm, and −400 mm < Z < −365 mm. Comparative experiments utilizing a high-precision standard sphere with a diameter of 19.0049 mm and a sphericity of 50 nm demonstrate that the identified optimal measurement area is consistent with the results obtained through the particle swarm algorithm, thereby validating the correctness of the method proposed in this study. [ABSTRACT FROM AUTHOR]

Due to the increasing requirements for the improvement of the accuracy of large coordinate-measuring machines (CMMs), the laser-tracing multi-station measurement technology, as one of the advanced precision measurement technologies, is worth studying in depth in terms of its practical application for the compensation of errors in large CMMs. Since it is difficult to maintain a constant temperature of about 20 °C in the actual workshop under the influence of solar radiation and convective heat transfer, there is a gradient in the spatial temperature distribution, and the overall temperature changes with the influence of external factors with synchronous hysteresis, it is difficult for the actual calibration environment to meet the standard environmental requirements. Therefore, the influence of temperature and other environmental factors on the accuracy of laser ranging and large-scale CMM calibration should not be ignored. In this paper, on the basis of analyzing the temperature distribution and change rule of large CMM measurement space under different working conditions, the radial basis function (RBF) neural network algorithm was used to build a non-uniform-temperature field model, and based on this model and the measurement principle of the laser-tracking instrument, the method of laser tracking and interferometric ranging accuracy enhancement was put forward under a non-uniform-temperature field. Finally, based on the multi-station technique of laser tracing, an accurate solution for the volumetric error of large CMMs under the condition of non −20 °C ambient temperature was realized. Simulation results proved that compared with the traditional temperature-compensation method, the proposed method improved the measurement accuracy of the volumetric error of a large-scale CMM using laser-tracing multi-station technology in a non-uniform-temperature field by 33.5%. This study provides a new approach for improving the accuracy of laser-tracer multi-station measurement systems. [ABSTRACT FROM AUTHOR]

Substantial experimental and theoretical efforts worldwide are devoted to explore the phase diagram of strongly interacting matter. At LHC and top RHIC energies, QCD matter is studied at very high temperatures and nearly vanishing net-baryon densities. There is evidence that a Quark-Gluon-Plasma (QGP) was created at experiments at RHIC and LHC. The transition from the QGP back to the hadron gas is found to be a smooth cross over. For larger net-baryon densities and lower temperatures, it is expected that the QCD phase diagram exhibits a rich structure, such as a first-order phase transition between hadronic and partonic matter which terminates in a critical point, or exotic phases like quarkyonic matter. The discovery of these landmarks would be a breakthrough in our understanding of the strong interaction and is therefore in the focus of various high-energy heavy-ion research programs. The Compressed Baryonic Matter (CBM) experiment at FAIR will play a unique role in the exploration of the QCD phase diagram in the region of high net-baryon densities, because it is designed to run at unprecedented interaction rates. High-rate operation is the key prerequisite for high-precision measurements of multi-differential observables and of rare diagnostic probes which are sensitive to the dense phase of the nuclear fireball. The goal of the CBM experiment at SIS100 (sNN= 2.7--4.9 GeV) is to discover fundamental properties of QCD matter: the phase structure at large baryon-chemical potentials (μB> 500 MeV), effects of chiral symmetry, and the equation of state at high density as it is expected to occur in the core of neutron stars. In this article, we review the motivation for and the physics programme of CBM, including activities before the start of data taking in 2024, in the context of the worldwide efforts to explore high-density QCD matter.

Locally Resonant Acoustic Metamaterials (LRAMs) have significant application potential because they can form subwavelength band gaps. However, most current research does not involve obtaining LRAMs with specified band gaps, even though such LRAMs are significant for practical applications. To address this, we propose a parameterized level-set-based topology optimization method that can use multiple materials to design LRAMs that meet specified frequency constraints. In this method, a simplified band-gap calculation approach based on the homogenization framework is introduced, establishing a restricted subsystem and an unrestricted subsystem to determine band gaps without relying on the Brillouin zone. These subsystems are specifically tailored to model the phenomena involved in band gaps in LRAMs, facilitating the opening of band gaps during optimization. In the multi-material representation model used in this method, each material, except for the matrix material, is depicted using a similar combinatorial formulation of level-set functions. This model reduces direct conversion between materials other than the matrix material, thereby enhancing the band-gap optimization of LRAMs. Two problems are investigated to test the method's ability to use multiple materials to solve band-gap optimization problems with specified frequency constraints. The first involves maximizing the band-gap width while ensuring it encompasses a specified frequency range, and the second focuses on obtaining light LRAMs with a specified band gap. LRAMs with specified band gaps obtained in three-material or four-material numerical examples demonstrate the effectiveness of the proposed method. The method shows great promise for designing metamaterials to attenuate specified frequency spectra as required, such as mechanical vibrations or environmental noise. [ABSTRACT FROM AUTHOR]

This paper presents a novel experimental approach for confirming that spherical mirror of a laser tracking system can reduce the influences of rotation errors of gimbal mount axes on the measurement accuracy. By simplifying the optical system model of laser tracking system based on spherical mirror, we can easily extract the laser ranging measurement error caused by rotation errors of gimbal mount axes with the positions of spherical mirror, biconvex lens, cat’s eye reflector, and measuring beam. The motions of polarization beam splitter and biconvex lens along the optical axis and vertical direction of optical axis are driven by error motions of gimbal mount axes. In order to simplify the experimental process, the motion of biconvex lens is substituted by the motion of spherical mirror according to the principle of relative motion. The laser ranging measurement error caused by the rotation errors of gimbal mount axes could be recorded in the readings of laser interferometer. The experimental results showed that the laser ranging measurement error caused by rotation errors was less than 0.1 μm if radial error motion and axial error motion were within ±10 μm. The experimental method simplified the experimental procedure and the spherical mirror could reduce the influences of rotation errors of gimbal mount axes on the measurement accuracy of the laser tracking system.

Multilateration measurement using laser trackers suffers from a cumbersome solution method for high-precision measurements. Errors are induced by the self-calibration routines of the laser tracker software. This paper describes an optimization solution model for laser tracker multilateration measurement, which effectively inhibits the negative effect of this self-calibration, and further, analyzes the accuracy of the singular value decomposition for the described solution model. Experimental verification for the solution model based on laser tracker and coordinate measuring machine (CMM) was performed. The experiment results show that the described optimization model for laser tracker multilateration measurement has good accuracy control, and has potentially broad application in the field of laser tracker spatial localization.