多系统协同测量场公共转站点布设优化方法

林雪竹; 董济育; 郭丽丽; 李丽娟

doi:10.3788/gzxb20265507.0712002

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多系统协同测量场公共转站点布设优化方法

仪器，测量，度量学 | 更新时间：2026-06-10

- 多系统协同测量场公共转站点布设优化方法
- Research on the optimization method for the layout of public transfer stations in multi-system collaborative measurement fields
- 光子学报 2026年页码：1-26
- 作者机构：
  
  长春理工大学光电工程学院飞行器结构检测与评估学科与技术中心，长春 130022
- 作者简介：
  
  林雪竹（1985—），女，副研究员，博士，主要研究方向为光电精密测量与数字孪生。Email: custsnow@163.com
- 基金信息：
  
  吉林省自然基金面上项目(20250102240JC)
- DOI：10.3788/gzxb20265507.0712002
  中图分类号： TH741
- CSTR：32255.14.gzxb20265507.0712002
- 收稿：2025-12-25，
  
  修回：2026-03-23，
  
  录用：2026-04-27，
- 稿件说明：
移动端阅览
林雪竹，董济育，郭丽丽，等. 多系统协同测量场公共转站点布设优化方法［J］.光子学报，2026，55（7）：0712002

LIN Xuezhu， DONG Jiyu， GUO Lili， et al. Research on the optimization method for the layout of public transfer stations in multi-system collaborative measurement fields［J］. Acta Photonica Sinica， 2026， 55（7）：0712002
林雪竹，董济育，郭丽丽，等. 多系统协同测量场公共转站点布设优化方法［J］.光子学报，2026，55（7）：0712002 DOI： 10.3788/gzxb20265507.0712002. CSTR： 32255.14.gzxb20265507.0712002.

LIN Xuezhu， DONG Jiyu， GUO Lili， et al. Research on the optimization method for the layout of public transfer stations in multi-system collaborative measurement fields［J］. Acta Photonica Sinica， 2026， 55（7）：0712002 DOI： 10.3788/gzxb20265507.0712002. CSTR： 32255.14.gzxb20265507.0712002.

摘要

在多系统协同测量场中测站已知的前提下，为了进一步提高不同系统、不同站位之间的数据融合精度，提出一种多系统协同测量场的公共转站点优化布设方法。首先，建立多系统协同测量坐标统一模型及测量场精度评价模型；其次，基于隐藏点移除算法实现工装遮挡下的单测站可视区域判定，通过几何容差方法结合各单站可视区域实现多测站共视区域判定，为公共转站点选址提供可视及观测冗余条件；再次，运用蒙特卡洛法进行不确定度分析以优化候选点集，依据差异化精度阈值筛选得到最优公共转站点集合；最后，通过仿真分析与实例验证对方法性能进行评估。结果表明：本文方法的整体测站均方根误差与公共转站点均方根误差，较传统方法提升约34%与32%，较兼顾位置分布与测量精度的坐标转换公共点优选方法分别提升约15%与22%，在某飞机实际装配现场的多系统协同测量场中，整体测站均方根误差与公共转站点均方根误差分别为0.078 mm和0.071 mm。该方法为复杂遮挡环境下多系统协同测量场的高精度、稳健组网提供了有效解决方案与理论支持。

Abstract

In the domain of high-end precision equipment manufacturing and the assembly of large-scale components， such as large machinery and complex opto-mechanical systems， the multi-system collaborative measurement field has emerged as an advanced methodology. By integrating diverse measurement instruments （e.g.， laser trackers， electronic theodolites） for coordinated data acquisition and fusion， it offers extensive spatial coverage， high precision， and enhanced efficiency， providing critical measurement support throughout the manufacturing process. The core challenge lies in achieving precise spatial coordinate unification among these heterogeneous systems， which differ significantly in measurement principles， error sources， and coverage capabilities. The spatial distribution of public transfer stations， which serve as common reference points for coordinate transformation between different instrument stations and systems， is pivotal for ensuring transformation accuracy， improving network efficiency， and enhancing overall measurement field stability. However， current practices predominantly rely on manual， experience-based placement of these stations， guided by principles of uniform distribution over the component's surface. This approach often neglects critical constraints such as line-of-sight visibility under complex tooling occlusions， the redundancy of multi-station observations， and the propagation of measurement uncertainties. Consequently， it frequently leads to suboptimal point selection， necessitating repeated on-site adjustments， compromising measurement efficiency， and ultimately degrading the accuracy and robustness of the coordinate transformation. Therefore， there is a pressing need for a systematic， optimization-driven methodology for deploying public transfer stations within a pre-planned multi-system measurement network to maximize data fusion precision.To address this gap， this paper proposes a comprehensive optimization method for the placement of public transfer stations in multi-system collaborative measurement fields. The methodology unfolds in several interconnected stages. First， a unified coordinate transformation model and a corresponding accuracy evaluation model for the multi-system measurement field are established. The transformation model employs a weighted least-squares approach to solve for optimal rotation and translation parameters between local and global coordinate systems， while the evaluation model defines overall root mean square error （RMSE） metrics for both instrument stations and public points to quantify network precision. Second， an optimization model for station placement is constructed， focusing on two core functionalities： visibility determination and uncertainty-based optimization. For visibility， the Hidden Point Removal （HPR） algorithm is introduced to accurately determine the visible region on the target component from each individual station， accounting for occlusions from tooling and fixtures. Subsequently， a geometric tolerance method is applied to intersect these individual visible regions， identifying common-view areas observable by multiple stations simultaneously， thereby ensuring necessary observational redundancy for public points. Third， candidate points within the common-view areas are generated via voxel-based down-sampling to reduce computational load. Then， a Monte Carlo simulation is employed for uncertainty analysis. Distinct error models for the laser tracker （incorporating distance and angular errors） and the electronic theodolite （incorporating instrument and sighting errors） are used to predict the three-dimensional measurement uncertainty for each candidate point. Finally， differential accuracy thresholds are applied to filter the candidate set， yielding an optimal collection of public transfer stations that satisfy both visibility and precision requirements.The effectiveness of the proposed method is rigorously validated through a detailed simulation experiment centered on a large aircraft model （10m×5m×3m） within a measurement volume of 12m×9m×4m， featuring complex tooling occlusions. The collaborative network comprised six laser tracker stations and four electronic theodolite stations. The results demonstrated significant advantages over traditional empirical placement. Regarding deployment efficiency and reliability， the proposed method achieved a 100% first-attempt network success rate， meaning all ten stations were successfully integrated into a unified network with sufficient （≥3） common points between necessary station pairs without requiring supplementary points. In contrast， the traditional method only achieved a 70% success rate initially， necessitating additional point placement to complete the network. More importantly， in terms of measurement accuracy， the optimized layout yielded a station overall RMSE of 0.055 mm and a public transfer station overall RMSE of 0.046 mm. These figures represent a substantial improvement of approximately 34% and 32%， respectively， compared to the traditional method's station overall RMSE of 0.084 mm and public point overall RMSE of 0.068 mm. Analysis revealed that the optimized points were concentrated in key structural areas （fuselage， wings， empennage） and exhibited a tighter， superior distribution of coordinate uncertainty. The method effectively suppressed error accumulation， which was more pronounced in the traditional scheme due to longer chains of coordinate transformations.In conclusion， this research presents a novel and systematic optimization methodology for deploying public transfer stations in multi-system collaborative measurement fields with predetermined instrument stations. By integrating a visibility analysis framework based on the HPR algorithm and multi-station common-view intersection with a precision optimization module based on system-specific error modeling and Monte Carlo uncertainty analysis， the method overcomes the limitations of experience-based placement. The experimental results on a complex aircraft model confirm that the proposed approach not only significantly enhances the efficiency and reliability of the initial network establishment but also delivers markedly superior coordinate unification accuracy for both the instrument stations and the public points themselves. This study provides a robust theoretical foundation and a practical solution for constructing high-precision， stable， and efficient multi-system collaborative measurement networks， especially in environments characterized by significant occlusions. It offers valuable guidance for practical engineering applications in the precision manufacturing and assembly of large-scale components.

关键词

Keywords

references

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