Measuring principle and uncertainty analysis of a large volume measurement network based on the combination of iGPS and portable scanner

Chen, Zhehan; Du, Fengming

doi:10.1016/j.measurement.2017.03.037

Cited by 27 publications

(7 citation statements)

References 11 publications

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“…While the volume of solids is in general easily measured by means of cameras [13][14][15] or laser scanners [16], Altuntas [17] used a camera-based technique also to estimate the volume of a pile of granular material. Other techniques dealing with granular materials have also been found in literature: Yanling et al [18] propose a technique based on the use of laser telemeters for the calculation of the volume of coal piles, while Feng et al [19] discuss a method to calculate the volume of a pile of rice by means of reverse engineering.…”

Section: State Of the Artmentioning

confidence: 99%

A geometrical approach for the measurement of the volume of masses of granular material through grid-layout sensor networks

et al. 2020

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Section: State Of the Artmentioning

confidence: 99%

A geometrical approach for the measurement of the volume of masses of granular material through grid-layout sensor networks

et al. 2020

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“…Many scholars have studied equipment measurement uncertainty and performed simulation evaluations of measurement uncertainty. For the standard large space measurement equipment indoor global positioning system, many scholars from the measurement principle, equipment uncertainty and measurement accuracy of many aspects of research and applied to engineering practice to achieve good results (Fuzhou and Chen, 2012; Fuzhou and Chen, 2012; Chen and Du, 2017). Equipment uncertainty belongs to the equipment itself, cannot be fundamentally eliminated and can only reduce the impact of equipment on the measurement and thus reduce the alignment error.…”

Section: Introductionmentioning

confidence: 99%

Research on ERS point registration of large-size measurement field based on neural network non-uniform temperature field

Huang

2023

RIA

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Purpose Large size of aircraft assembly tooling structure and complex measurement environment exist. The laid enhanced reference points (ERS) are subject to a combination of nonuniform temperature fields and measurement errors, resulting in increased measurement registration errors. In view of the nonuniform temperature field and measurement errors affecting the ERS point registration problem, the purpose of this paper is to propose a neural network-based ERS point registration compensation method for large-size measurement fields under a nonuniform temperature field. Design/methodology/approach The approach is to collect ERS point information and temperature data, normalize the collected data to complete the data structure design and complete the construction of the neural network prediction model by data training. The data learning is performed to complete the prediction model construction, and the prediction model is used to complete the compensation analysis of ERS points. Finally, the algorithm is verified through experiments and engineering practice. Findings Experimental results show that the proposed neural network-based ERS point prediction and compensation method for nonuniform temperature fields effectively predicts ERS point deformation under nonuniform temperature fields compared with the conventional method. After the compensation analysis, the registration error is effectively reduced to improve registration accuracy. Reducing the combined effect of environmental nonuniform temperature field and measurement error has apparent advantages. Originality/value The method reduces the registration error caused by combining a nonuniform temperature field and measurement error. It can be used for aircraft assembly site prediction and registration error compensation analysis, which is essential to improve measurement accuracy further.

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“…[11,12,27,40]. Therefore, distributed metrology systems must provide a coordinate system for spatial referencing on the entire shop floor [7]. Following this idea, Demeester [8] defined a Global Reference System (GRS) as a system covering the measuring volume of an entire shop floor and enabling measurements at many points simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Virtual indoor-GPS for measurement uncertainty determination in reconfigurable environments

Nicksch

Sabzehi

Schmitt

2022

Prod. Eng. Res. Devel.

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In Line-less Mobile Assembly Systems, the mobilization of assembly resources and products enables rapid physical system reconfigurations to increase flexibility and adaptability. The clean floor approach discards fixed anchor points, so that assembly resources such as mobile robots and automated guided vehicles transporting products can adapt to new products and form new processes. Associated challenges are accurate spatial referencing between mobile resources to meet assembly tolerance requirements. There is a need for more accurate positioning data to locate and navigate mobile assembly resources. An indoor-GPS, as a distributed large-scale metrology system, is able to cover a wide shop floor area and to obtain positioning data with uncertainties in the submillimeter range. The measurement uncertainty of such a system depends on the spatial distribution of the transmitters and the receiver positions. To be able to validate positioning tolerance requirements of an assembly process, measurement uncertainties must be determined. Virtual measurements simulate measurement processes and model dependencies between the environment and the metrology system. This work presents a novel approach for a virtual indoor-GPS to determine measurement uncertainties during a process and to evaluate the measurement process capability. Experiments show the validity of the virtual indoor-GPS which can be used as a planning tool for metrology system setups within Line-less Mobile Assembly Systems.

show abstract

Measuring principle and uncertainty analysis of a large volume measurement network based on the combination of iGPS and portable scanner

Cited by 27 publications

References 11 publications

A geometrical approach for the measurement of the volume of masses of granular material through grid-layout sensor networks

A geometrical approach for the measurement of the volume of masses of granular material through grid-layout sensor networks

Research on ERS point registration of large-size measurement field based on neural network non-uniform temperature field

Virtual indoor-GPS for measurement uncertainty determination in reconfigurable environments

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