土工基础 ›› 2025, Vol. 39 ›› Issue (6): 998-1001.

• 测试技术 • 上一篇    下一篇

红层泥质软岩力学强度回弹波速法试验研究

曾雪松,罗阳楚君,冯世清,陈皓琪   

  1. (中国建筑西南勘察设计研究院有限公司,成都 610059)
  • 收稿日期:2023-11-30 修回日期:2023-12-27 出版日期:2025-12-31 发布日期:2026-01-31
  • 作者简介:曾雪松(1974-),男,正高级工程师,研究方向为岩土工程勘察、设计、施工、检测与监测。

Experimental Study on Mechanical Strength of Red Mudstone Soft Rock by Using Rebound Wave Velocity Method

ZENG Xuesong, LUO Yangchujun, FENG Shiqing, CHEN Haoqi   

  • Received:2023-11-30 Revised:2023-12-27 Online:2025-12-31 Published:2026-01-31

摘要: 能够准确、快速地获得岩石(体)力学性能指标,对保障施工安全、进度和施工质量具有重大的工程意义。以成都平原常见的红层泥质软岩为研究对象,采用二元非线性回归方程,利用回弹波速无损检测值建立强度预测模型,以求在一定范围内对岩石强度进行快速、无损和精确的预测。实践表明,这种回弹波速试验法,便于快速、准确、便捷地得到岩石的强度值,提高工程建设项目中获得力学强度指标的时效性和经济性,提高生产效率,节约工程造价,为研究红层泥质软岩力学性质和解决实际工程问题提供了新的思路和途径。

关键词: 回弹, 波速, 回归分析, 强度预测

Abstract: The mechanical strength of rock samples is a very important indicator in engineering practice, which can be used for the basic mechanical parameters of geotechnical engineering design and construction. Therefore, the ability to quickly and accurately obtain the compressive strength of rock samples is of great engineering significance for ensuring engineering quality, construction safety, and schedule. This study focuses on the red mudstone soft rock samples and proposes a rock strength testing method that combines rebound and wave velocity. A strength prediction model is established using binary nonlinear regression equations to achieve the goal of quickly, accurately, and non-destructive prediction of rock samples strength. Practice has shown that this rebound wave velocity test method is convenient for quickly, accurately, and conveniently obtaining the strength value of rock samples, improving the timeliness and economy of obtaining mechanical strength indicators in engineering construction projects, improving production efficiency, saving engineering costs, and providing new ideas and approaches for studying the mechanical properties of red mudstone soft rock samples and solving practical engineering problems.

Key words: Resilience, Wave Velocity, Regression Analysis, Strength Prediction

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