基于离散波束分析的煤样品卸载故障的声学发射前体特性研究
Shaojie Ma1, Yan Zhou2, Depeng Ma3
1Chongqing Vocational Institute of Engineering, Chongqing, 402260, China.
Scientific reports
|December 31, 2024
概括
对声辐射信号的波形分析可以预测煤炭样本的故障. 识别第一个负利普希茨指数,排除特定范围,为岩石破裂提供了有效的早期预警.
科学领域:
- 地质技术工程 地质技术工程
- 信号处理 信号处理
- 材料科学 材料科学 材料科学
背景情况:
- 声辐射 (AE) 信号是故障期间岩石损伤的特征.
- 传统的方法与离散的,非静止的AE信号作斗争.
- 波形分析为处理这些信号提供了一种有效的方法.
研究的目的:
- 调查波波分析的应用,以处理煤样本的AE信号.
- 使用AE信号分解和奇点检测识别煤样失效的预测指标.
主要方法:
- 降低声学发射信号的噪声.
- 使用Matlab.使用三轴卸载试验的AE信号的分解.
- 对于时间序列数据的奇点检测和利普希茨指数分析.
主要成果:
- 最初出现负利普希茨指数 (α) 表示潜在的故障时间.
- 利普希茨指数值的特定范围 (-0.15到-0.31) 需要排除,以便准确预测.
- 预测和实际破裂时间之间的绝对差异处于[5.2s, 17.1s]范围内,其中63.6%处于[5.2s, 10.0s]范围内.
结论:
- 基于波纹的奇点检测是岩石力学AE信号分析的可行方法.
- 负利普希茨指数的时间为煤炭样本失败提供了一个可量化的预测窗口.
- 这种方法为地质技术应用中的预警系统提供了实用方法.
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