• Infrared and Laser Engineering
  • Vol. 54, Issue 3, 20240623 (2025)
Yang ZHANG, Yipin SU, Yongkang LU*, Junqing LI..., Qihang CHEN, Ruidi YAN and Wei LIU|Show fewer author(s)
Author Affiliations
  • School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China
  • show less
    DOI: 10.3788/IRLA20240623 Cite this Article
    Yang ZHANG, Yipin SU, Yongkang LU, Junqing LI, Qihang CHEN, Ruidi YAN, Wei LIU. Prediction and compensation of thermal offset in tooling ERS points under non-uniform temperature fields (invited)[J]. Infrared and Laser Engineering, 2025, 54(3): 20240623 Copy Citation Text show less
    The overall framework for the prediction and compensation of thermal offset in tooling ERS points under non-uniform temperature fields
    Fig. 1. The overall framework for the prediction and compensation of thermal offset in tooling ERS points under non-uniform temperature fields
    Logic diagram for determining the global trend of the tooling temperature field using LOOCV
    Fig. 2. Logic diagram for determining the global trend of the tooling temperature field using LOOCV
    Schematic of global temperature field reconstruction
    Fig. 3. Schematic of global temperature field reconstruction
    Logic diagram of the approach for selecting virtual temperature measurement points based on multi-objective optimization
    Fig. 4. Logic diagram of the approach for selecting virtual temperature measurement points based on multi-objective optimization
    Flowchart of the adaptive dynamic local search prairie dog optimization
    Fig. 5. Flowchart of the adaptive dynamic local search prairie dog optimization
    Comparison of temperature field reconstruction by GPR-GTFR and Kriging methods
    Fig. 6. Comparison of temperature field reconstruction by GPR-GTFR and Kriging methods
    Schematic of the model simplification process
    Fig. 7. Schematic of the model simplification process
    Schematic of model meshing and constraint settings
    Fig. 8. Schematic of model meshing and constraint settings
    Experimental configuration
    Fig. 9. Experimental configuration
    Experimental scenario
    Fig. 10. Experimental scenario
    Temperature sensor data recording curve
    Fig. 11. Temperature sensor data recording curve
    Prediction curves of thermal offset for ERS points under uniform temperature change
    Fig. 12. Prediction curves of thermal offset for ERS points under uniform temperature change
    Prediction curves of thermal offset for a ERS point under varying temperature changes
    Fig. 13. Prediction curves of thermal offset for a ERS point under varying temperature changes
    Station transfer errors before and after compensation
    Fig. 14. Station transfer errors before and after compensation
    ParameterValue
    Elastic modulus E/MPa2.1×105
    Poisson's ratio $\upsilon $0.3
    Thermal expansion coefficient $\alpha $/℃−11.2×10−5
    Density $\rho $/g·cm−37.85
    Table 1. Material properties of the tooling
    ParameterExperiment group number
    12345678
    RMSE0.02160.02670.02850.03650.01990.02290.01840.0215
    MeanE0.01880.02570.02800.02770.01730.02000.01470.0177
    MaxE0.03820.03000.03130.03720.02020.03000.03250.0351
    Table 2. Prediction error analysis of thermal offset for reference points (Unit: mm)
    RMSE-XRMSE-YRMSE-Z
    Before compensation0.23810.17400.1999
    After compensation0.03700.03850.0424
    Table 3. RMSE comparison of station transfer errors in X, Y, and Z directions before and after compensation (Unit: mm)
    Yang ZHANG, Yipin SU, Yongkang LU, Junqing LI, Qihang CHEN, Ruidi YAN, Wei LIU. Prediction and compensation of thermal offset in tooling ERS points under non-uniform temperature fields (invited)[J]. Infrared and Laser Engineering, 2025, 54(3): 20240623
    Download Citation