| 引用本文: | 刘铁新,董自岩,郭怡宁.鹈鹕优化算法在岩体结构面分组中的应用[J].哈尔滨工业大学学报,2024,56(3):117.DOI:10.11918/202304025 |
| LIU Tiexin,DONG Ziyan,GUO Yining.Application of pelican optimization algorithm to clustering analysis of rock mass structural plane[J].Journal of Harbin Institute of Technology,2024,56(3):117.DOI:10.11918/202304025 |
|
| 摘要: |
| 结构面广泛分布于岩体之中,难以逐一进行分析。现有研究方法存在对初始信息敏感,分组结果可靠性差,以及难以准确对产状相近的结构面进行分组等不足。针对上述问题,提出了一种基于鹈鹕优化算法（POA）的岩体结构面分组方法。首先,利用POA算法全局寻优初始聚类中心,结合模糊C均值算法（FCM）将结构面产状数据进行完全分组。其次,利用蒙特卡罗模拟技术,生成符合Fisher分布的产状数据。最后,基于正交设计,对比传统FCM算法,以识别错误率为指标,研究了新算法在不同结构面数量、结构面组数、聚类中心、离散度情况下分组精度的变化规律。结果表明:聚类中心对分组精度具有显著影响；所提方法能对产状极点边界不清晰的结构面数据进行有效分组,可有效提高分组精度和分组结果的可靠性。以大连某水库边坡结构面数据为基础,对其进行分组处理,验证了新方法的工程实用性。研究结果可以为结构面三维网络计算机模拟和岩体工程稳定性分析提供依据。 |
| 关键词: 岩体力学 鹈鹕优化算法 模糊C均值算法 结构面分组 正交设计 |
| DOI：10.11918/202304025 |
| 分类号:TU452 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(U19A8,4) |
|
| Application of pelican optimization algorithm to clustering analysis of rock mass structural plane |
|
LIU Tiexin,DONG Ziyan,GUO Yining
|
|
（College of Transportation Engineering, Dalian Maritime University, Dalian 116600, Liaoning, China）
|
| Abstract: |
| The discontinuities are widely distributed in the rock mass and are difficult to analyze one by one. Therefore, it is of great engineering value and scientific significance to carry out the dominant grouping of the discontinuities. The existing research methods are sensitive to the initial information, the grouping results are not reliable, and it is difficult to accurately group the discontinuities with similar discontinuity orientations. To address these problems, this paper proposes a method for grouping discontinuities in rock masses based on the pelican optimization algorithm (POA). The POA algorithm is used to globally find the optimal initial clustering center and combine with the fuzzy C-mean algorithm (FCM) to fully group the discontinuity orientations. A Monte Carlo simulation technique is used to generate discontinuity orientations that conform to the Fisher distribution. Based on the orthogonal design, using the recognition error rate as the index, the new algorithm was compared with the traditional FCM algorithm, and the variation regulation of grouping accuracy was investigated under different number of discontinuities, number of discontinuities groups, clustering centers and dispersion degree. The results indicate that the cluster centers have a significant impact on grouping accuracy, and the proposed method is capable of effectively grouping structural data with unclear boundary of geological features, thereby improving the accuracy and reliability of the grouping results. Based on the data of the slope structural plane of a reservoir in Dalian, it is grouped and processed to verify the engineering practicability of the new method. This study can provide a basis for the three-dimensional network computer simulation of structural plane and the stability analysis of rock mass engineering. |
| Key words: rock mass mechanics POA FCM structural plane grouping orthogonal design |
