YUAN Zhouhao, YE Yicheng, LUO Binyu, YAN Yaofeng. Hierarchical characterization joint surface roughness coefficient of rock joint based on wavelet transform[J]. Journal of China Coal Society, 2022, 47(7): 2623-2642.
Citation: YUAN Zhouhao, YE Yicheng, LUO Binyu, YAN Yaofeng. Hierarchical characterization joint surface roughness coefficient of rock joint based on wavelet transform[J]. Journal of China Coal Society, 2022, 47(7): 2623-2642.

Hierarchical characterization joint surface roughness coefficient of rock joint based on wavelet transform

  • How to quantize the characterization of joint roughness accurately has always been an issue in the field of joint rock mechanics. Joint surface morphology is multiscale,and the contribution of waviness and unevenness to the joint surface roughness is different. Under the premise of considering the multiscale characteristics of the joint surface,how to realize the accurate characterization of the joint surface roughness needs further research. The waveletbased optimization criterion was proposed based on the energyentropy ratio. The critical decomposition level criterion was defined based on the energy retention percentage and the signal standard deviation. Combined with wavelet transform theory,the theory of joint surface morphology decomposition was developed. Based on the decomposition theory,ten standard JRC profiles was taken as objects to realize the accurate decomposition of the joint surface morphology. The statistical parameters of the waviness and unevenness (firstorder derivative root mean square Z 2,joint surface roughness index R p-1) were calculated,and the differences between them were analyzed,revealing the reason why the statistical parameters appear to be locally convex with the increase in roughness. Then,a hierarchy characterization formula was established based on the statistical parameters. Finally,the formula was verified by the shear test of the joint specimen. The results are as follows:① The optimal wavelet basis coif5 determined based on the wavelet base optimization criterion can be used for the wavelet transform of joint surface morphology. ② The fourth decomposition level determined based on the critical decomposition level criterion is suitable for the identification of waviness and unevenness. ③ The statistical parameters of the waviness and unevenness are different,and the statistical parameters of the unevenness are larger than those of the waviness. The phenomenon that the statistical parameters appear to be locally convex with the increase in roughness when the statistical parameters are used to characterize the undecomposed standard roughness profile is due to the fact that the difference in the morphological contribution of the waviness and unevenness is not considered. ④ The result calculated by the hierarchy characterization formula is consistent with the inverse value calculated by the shear test,and the accuracy is better than the calculation result of the unhierarchy characterization formula,which indicate that the hierarchy characterization formula is reliable. This research provides a new way for the decomposition of the joint surface morphology.
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