Xin-yuan WEI, Yu-chen CHEN, En-ming MIAO, Xu-gang FENG, Qiao-sheng PAN. Application of principal component algorithm in spindle thermal error modeling of CNC machine tools[J]. Optics and Precision Engineering, 2021, 29(11): 2649

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- Optics and Precision Engineering
- Vol. 29, Issue 11, 2649 (2021)

Fig. 1. Experimental object: three axis vertical mechining center

Fig. 2. Position of displacement sensor

Fig. 3. Temperature curve of K1

Fig. 4. Temperature curve of K9

Fig. 5. Thermal errors in Z direction curves of each experiment

Fig. 6. The influence of the number of TSPs on the prediction effect of the model

Fig. 7. Structure of BP neural network

Fig. 8. Fitting accuracy results of four modeling algorithms

Fig. 9. Prediction accuracy results of four modeling algorithms

Fig. 10. Robustness results of four modeling algorithms

Fig. 11. Verification experiment V1~V3 spindle speed setting

Fig. 12. The curve of V1 predicted by K1 model

Fig. 13. Thermal error compensation measurement results
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Table 1. Position and function of temperature sensor
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Table 2. Experimental parameters of each batch
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Table 3. Principal components and contribution rate of K1
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Table 4. Selection results of TSPs of each experiment(PCA)
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Table 5. Selection results of TSPs of each experiment(FCGC)
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Table 6. Model coefficient of MLR of each batch experiment
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Table 7. Model coefficient of ridge regression of each batch experiment

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