Fasheng Qiu, Dong Li, Chaoyang Guo, Shukun Xiao, Yuting Kang, Zhongqi Hao, Wenze Shi. Stress Evaluation Based on Laser Ultrasonic Time‐Frequency Statistical Feature Fusion[J]. Chinese Journal of Lasers, 2024, 51(17): 1704001
- Chinese Journal of Lasers
- Vol. 51, Issue 17, 1704001 (2024)
Fig. 1. Experimental setup
Fig. 2. Multi-feature fusion benchmark model for stress prediction
Fig. 3. Laser ultrasonic signal. (a) Laser signal and original laser ultrasonic signal; (b) laser ultrasonic signal after filtering
Fig. 4. Envelopes of laser ultrasonic signal from time and frequency domains. (a) Original signal and envelope of laser ultrasonic in time domain; (b) frequency spectrum and envelope of laser ultrasonic in frequency domain
Fig. 5. Stress dependent laser ultrasonic wave. (a) Laser ultrasonic signals under different stresses; (b) relationship between delay time of ultrasonic wave and applied stress
Fig. 6. Cumulative contribution of principal components of laser ultrasonic features
Fig. 7. Outputs of stress prediction by using different kernel functions. (a) Linear kernel function; (b) polynomial kernel function;
Fig. 8. R2 and RMSE of stress prediction results by using different kernel functions
Fig. 9. Stress prediction results by using different regressive stress prediction models. (a) Single feature; (b) multiple linear regression; (c) Bayes; (d) random forest; (e) SVM
Fig. 10. Prediction results at different stress levels by using different regressive models
Fig. 11. R2 and RMSE of stress prediction results in training and test sets by using different regressive stress prediction models. (a) R2; (b) RMSE
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Table 1. Pearson’s correlation coefficients between different laser ultrasonic features
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