Kinematic calibration of a laser tracker based on nonlinear optimization of a refined geometric error model

Chen, Xiaopeng; Liu, Yanyang; Yang, Xu; Gou, Siyuan; Ma, Siyan; Ullah, Zakir

doi:10.1016/j.measurement.2021.110672

Cited by 3 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is difficult to identify individual geometric errors in these performance tests, and the measurement process is complex. Some studies [22][23][24] establish kinematic error models and use the nonlinear optimization method to identify the exact values of the geometric error parameters at one time. Compared to performance tests, the calibration process mentioned above takes less time.…”

Section: Introductionmentioning

confidence: 99%

A Transit Tilt and Offset Errors Calibration Method for Improving Laser Tracker Measurement Accuracy Based on the Telecentric Measurement System

Wang,

Zhang,

Dong

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

Laser trackers are instruments used to measure the three-dimensional coordinates of objects with high precision. It is necessary to study calibration methods to identify geometric errors of laser trackers so as to compensate for errors and improve measurement accuracy. Among the offsets, tilts, and eccentricity errors in the system, the transit tilt and offset errors play important roles and have an essential effect on the measurement accuracy, which need to be calibrated and compensated for. Current methods for detecting geometric errors between the transit and standing axes are complex and time-consuming. In this paper, a fast and novel calibration method is proposed, which can be easily operated with high precision. Two test rods are coaxially mounted on the ends of the transit axis to extend the hidden transit axis. Then, a telecentric measurement system is used to record the projection images of the test rods and identify the position of the transit axis. The transit offset and tilt errors were thus obtained by comparing the central axis positions of the two test rods before and after the standing axis rotated 180 degrees. Moreover, a numerical analysis method was proposed based on the least square circle fitting method to calibrate the installation eccentricity errors of the test rods. Experimental results verify that the measurement accuracy of the laser tracker can be improved after error compensation using the calibrated transit offset and tilt errors. The measurement error of the laser tracker can be reduced from 161 µm to about 73 µm after compensation at a distance of 5 m, while the error can be decreased from 143 µm to about 108 µm at a distance of 10 m.

show abstract

Section: Introductionmentioning

confidence: 99%

A Transit Tilt and Offset Errors Calibration Method for Improving Laser Tracker Measurement Accuracy Based on the Telecentric Measurement System

Wang,

Zhang,

Dong

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

Positional error compensation for aviation drilling robot based on Bayesian linear regression

Chen,

Lv,

Xue

et al. 2024

Engineering Applications of Artificial Intelligence

View full text Add to dashboard Cite

Research on registration error compensation of large-scale measurement field based on neural network

Huang

et al. 2023

Review of Scientific Instruments

View full text Add to dashboard Cite

The combination of large tooling size, environmental vibration, and equipment errors at the aircraft assembly site leads to errors in the enhanced reference system (ERS) point measurement information. ERS point errors directly reduce the accuracy of the assembly measurement field. This paper proposes ERS point error prediction and registration compensation based on the neural network to address this problem. First, the effects of equipment measurement errors and environmental vibration factors on the measurement field are studied. The ERS point error prediction model based on the neural network is established. On this basis, model evaluation is used to assess the prediction model of this paper. Then, a measurement field registration compensation model is constructed based on the neural network error results for ERS point compensation analysis. Finally, an experimental validation platform was built to predict the ERS point errors and compensate for the constructed measurement fields using the method in this paper. The experimental results show that, compared with the conventional method, the maximum registration errors in the X, Y, and Z directions are reduced from 0.0812, −0.0565, and −0.2810 to −0.0184, −0.0010, and 0.0022 mm, respectively, after compensation in this paper. The method proposed in this paper can not only predict the ERS point error state and provide a reference for designers but also guide the selection of appropriate ERS points when constructing the measurement field. The compensation method in this paper effectively reduces the measurement field registration error.

show abstract

Kinematic calibration of a laser tracker based on nonlinear optimization of a refined geometric error model

Cited by 3 publications

References 20 publications

A Transit Tilt and Offset Errors Calibration Method for Improving Laser Tracker Measurement Accuracy Based on the Telecentric Measurement System

A Transit Tilt and Offset Errors Calibration Method for Improving Laser Tracker Measurement Accuracy Based on the Telecentric Measurement System

Positional error compensation for aviation drilling robot based on Bayesian linear regression

Research on registration error compensation of large-scale measurement field based on neural network

Contact Info

Product

Resources

About