The features of the widely-used coordinate measuring arm (CMA) are discussed. A novel technology for quick volumetric error verification of CMA is presented. A modular space frame (MSF) to verify and calibrate the measuring accuracy of CMA is invented, which consists of standard balls, links and bases. An effective verification procedure is developed. Results are presented that show CMA can be verified and calibrated with accuracy of 0.015mm in 5 minutes by using the proposed method.
Laser tracker system (LTS) is an advanced 3D coordinates measuring system for large size. It can measure large 3D coordinates with advantages of broad range, high speed and high accuracy. However, when the size of having been measured large-scale part (such as airplane and shipbuilding) is larger than the LTS measuring range, it can not measure all of the required features of components in one location, which profoundly affect the LTS measuring scope and accuracy. In order to solve measuring problem for large-scale parts, a new method of frog-jumping is proposed based on the principle of using LTS to measure more than three frog-jumping spheres under the new and old coordinate system. The corresponding mathematical model of frog-jumping is established. Intensive experimental studies have been made to check validity of proposed method; the results show that using this technology the measurement of large-scale parts all features is realized effectively under the required accuracy constraints.
Integer carrier phase ambiguity resolution is the key to fast and high-precision Global navigation satellite system(GNSS) positioning and application. LAMBDA method is one of the best methods for fixing integer ambiguity. The principle of LAMBDA is discussed. For incompleteness of Cholesky decomposition and complexity of Integer Gauss transformation, a new approach for GNSS ambiguity decorrelation is proposed based on symmetric pivoting strategy and united inverse integer strategy. The new algorithm applies symmetric pivoting strategy to ambiguity covariance matrix while doing Cholesky decomposition, then finds the inverse and integer matrix of ‘L’. This method not only uses Cholesky decomposition to improve efficiency, but also avoids complicated Integer Gauss transformations. The feasibility and advantage of the method are verified using randomly simulation covariance matrix.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.