Author:
He Peng,Xu Yifan,Jiang Feng,Wang Gang,Xiao Zhiyong,Zheng Chengcheng
Abstract
AbstractTo quickly determine the blasting block degree and conduct an accurate and objective analysis of the tunnel blasting effect, this study has enhanced and improved upon the traditional genetic algorithm and Otsu algorithm. It has combined it with the marking watershed method and utilized ground digital acquisition to capture images of blasting debris. These images are then used in our custom-developed blasting analysis software to calculate the blasting block degree distribution and provide a quantitative analysis of blasting block degree. The research results show that the optimized image segmentation algorithm effectively improves the traditional threshold segmentation method on the poor effect of segmentation of the edge of the adherent block or the direct application of the watershed segmentation of the over-segmentation problem, to improve the segmentation accuracy based on the new segmentation technology is close to the traditional technology in terms of time. Through the self-developed software, the construction personnel in the project site to quickly obtain the blasting block degree histogram, block degree cumulative curve and other important indicators of the evaluation of the effect of blasting block degree, to provide data support for on-site construction, to assist in the modification of the blasting program, and to improve the efficiency of construction. This study realizes the rapid detection and block identification of blasting blocks, provides data support for the optimization of blasting parameters, and has good application and promotion value.
Funder
China Post doctoral Science Foundation
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Reference16 articles.
1. Jiang, F. et al. Evaluation of blasting effect based on analytic hierarchy process and cloud model in Open-pit mines. In Proc. IEEE 3rd Int. Conf. Cloud Comput. Big Data Anal. (ICCCBDA), Vol. 2018, 57–61 (2018).
2. Taji, M., Ataei, M., Goshtasbi, K. & Osanloo, M. ODM: A new approach for open pit mine blasting evaluation. J. Vib. Control 19, 1738–1752. https://doi.org/10.1177/1077546312439911 (2013).
3. Yang, Y. et al. Open-pit mine geological model construction and composite rock blasting optimization research. Shock Vib. 2022, 1468388. https://doi.org/10.1155/2022/1468388 (2022).
4. Lei, M. et al. A novel tunnel-lining crack recognition system based on digital image technology. Tunnell. Undergr. Space Technol. 108, 103724. https://doi.org/10.1016/j.tust.2020.103724 (2021).
5. Wang, P., Wang, S. & Jierula, A. Automatic identification and location of tunnel lining cracks. Adv. Civil Eng. 2021, 1–9. https://doi.org/10.1155/2021/8846442 (2021).