基于聚类分析的层状砂岩失效模式与破坏前兆识别

丁自伟; 张辰晨; 孙文亮; 董云俊; 余茂清

doi:10.20174/j.JUSE.2026.03.34

地下空间与工程学报 >

2026 , Vol. 22 >Issue 3: 1090 - 1102

DOI: https://doi.org/10.20174/j.JUSE.2026.03.34

防灾与环境

基于聚类分析的层状砂岩失效模式与破坏前兆识别

丁自伟 ,
张辰晨 ,
孙文亮 ,
董云俊 ,
余茂清

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1.西安科技大学能源学院,西安 710054;
2.西部矿井开采及灾害防治教育部重点实验室,西安 710054;
3.山东能源集团西北矿业有限公司,西安 710005

丁自伟(1987—),男,山东临沂人,博士,教授、博士生导师,主要研究方向为智能岩石力学。E-mail:zwding519@163.com

张辰晨(2000—),男,西安人,硕士生,主要研究方向为智能岩石力学。E-mail:pvdbll8b@163.com

收稿日期: 2025-12-27

网络出版日期: 2026-06-23

基金资助

国家自然科学基金面上资助项目(52074209)

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Failure Mode and Failure Precursor Identification of Layered Sandstone Based on Cluster Analysis

Ding Ziwei ,
Zhang Chenchen ,
Sun Wenliang ,
Dong Yunjun ,
Yu Maoqing

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1. College of Energy Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, P. R. China;
2. Key Laboratory of Western Mine Exploitation and Hazard Prevention, Ministry of Education, Xi’an 710054, P. R. China;
3. Shandong Energy Group Xibei Mining Co., Ltd., Xi'an 710005, P. R. China

Received date: 2025-12-27

Online published: 2026-06-23

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摘要

层状砂岩广泛分布在地下空间工程的围岩环境中,基于聚类分析的方法研究层状砂岩在循环载荷下的破坏模式并识别失效信号可以分析复杂应力条件下岩体的失效行为。对层状砂岩试样进行循环加载实验,监测岩石破坏的声发射信号,通过K-means++聚类算法对信号进行归类,揭示了层状砂岩在循环载荷下的破坏模式,识别出岩石破坏相关的前兆信号。结果表明:单轴加载试样的宏观破坏以剪切破坏为主,每级加载3次试样呈剪切-拉伸混合破坏,每级加载5次试样以拉伸破坏为主;每级加载3次试样时前中期微裂隙与大尺度裂隙共同发育,后期则主要以大尺度裂隙的稳定扩展为主,最终由微小裂隙的贯通形成了主要裂缝,每级加载5次时试样大尺度裂纹稳定发展,临近破坏时迅速贯通;不同加载条件下聚类分析的轮廓系数分别为0.81与0.93,并归类得到3类信号:Ⅰ型信号以拉伸信号为主,在2组样本的占比为39.2%与37.9%,Ⅱ型信号以混合破坏为主,在2组样本的占比为43.3%与57.3%,Ⅲ型信号以剪切破坏为主,在2组样本占比为17.4%及4.8%,且随着临近岩样失效而发生频率增加。研究可为层状砂岩破坏模式和失效预测提供理论依据。

关键词： 声发射监测; 循环加卸载; 聚类分析; 破坏前兆; 层状砂岩

本文引用格式

丁自伟 , 张辰晨 , 孙文亮 , 董云俊 , 余茂清 . 基于聚类分析的层状砂岩失效模式与破坏前兆识别[J]. 地下空间与工程学报, 2026 , 22(3) : 1090 -1102 . DOI: 10.20174/j.JUSE.2026.03.34

Abstract

Layered sandstone is widely distributed in the surrounding rock environment of underground space engineering. The method based on cluster analysis is used to study the failure modes of layered sandstone under cyclic loading and identify failure signals, which can analyze the failure behavior of rock mass under complex stress conditions. Cyclic loading experiments were conducted on layered sandstone samples to monitor the acoustic emission signals of rock failure. The signals were classified using K-means++clustering algorithm, revealing the failure mode of layered sandstone under cyclic loading and identifying precursor signals related to rock failure. The results show that: The macroscopic failure of uniaxial loaded specimens is mainly shear failure, with a mixed shear tensile failure observed in specimens loaded three times per level, and tensile failure observed in specimens loaded five times per level; When the sample is loaded three times per level, micro cracks and large-scale cracks develop together in the early and middle stages. In the later stage, the stable expansion of large-scale cracks is the main trend, and ultimately the main cracks are formed by the penetration of micro cracks. When the sample is loaded five times per level, the large-scale cracks in the sample develop stably and quickly penetrate when approaching failure; The contour coefficients of cluster analysis under different loading conditions were 0.81 and 0.93, respectively, and three types of signals were classified: Type I signal was mainly tensile signal, accounting for 39.2% and 37.9% of the two groups of samples; Type II signal was mainly mixed failure, accounting for 43.3% and 57.3% of the two groups of samples; Type III signal was mainly shear failure, accounting for 17.4% and 4.8% of the two groups of samples, and the frequency of occurrence increased with the failure of adjacent rock samples. The research provides a scientific basis for the failure mode and failure prediction of layered sandstone.

Key words： acoustic emission monitoring; cyclic loading and unloading; clustering analysis; failure precursor; layered sandstone

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