冲击荷载下岩体应力波振动信号频率特征分析

冯佳兴; 袁利伟; 彭纪; 陈明辉; 陈迪; 起卓

doi:10.11858/gywlxb.20240897

冲击荷载下岩体应力波振动信号频率特征分析

doi: 10.11858/gywlxb.20240897

冯佳兴^1,,
袁利伟^2,*, ,,
彭纪³,
陈明辉²,
陈迪²,
起卓²

1.
昆明理工大学国土资源工程学院, 云南昆明　650093
2.
昆明理工大学公共安全与应急管理学院, 云南昆明　650093
3.
保山职业学院, 云南保山　678000

基金项目: 国家自然科学基金（52364020）

详细信息

作者简介:
冯佳兴（1999－），男，硕士研究生，主要从事安全监测研究. E-mail：821866927@qq.com

通讯作者:
袁利伟（1978－），男，博士，教授，主要从事安全科学理论技术、矿山安全技术、灾害风险管控与预警预报研究. E-mail：86593592@qq.com

中图分类号: O381; O521.2; TD235
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出版历程
- 收稿日期: 2024-09-28
- 修回日期: 2024-10-28
- 录用日期: 2025-02-14
- 网络出版日期: 2025-04-18
- 刊出日期: 2025-05-01

Frequency Characterization of Stress Wave Vibration Signals in Rock Mass under Impact Loading

FENG Jiaxing^1
,,
YUAN Liwei^{2,*
, ,},
PENG Ji³,
CHEN Minghui²,
CHEN Di²,
QI Zhuo²

1.
School of Land and Resources Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan, China
2.
School of Public Safety and Emergency Management, Kunming University of Science and Technology, Kunming 650093, Yunnan, China
3.
BaoShan Vocational College, Baoshan 678000, Yunnan, China

摘要

摘要: 岩体在外部荷载冲击作用下会产生不同频率的信号。首先，通过自制探头的光纤监测系统监测现场岩体受到瞬时冲击荷载前后的应力波信号，并采用鲁棒性局部均值分解（robust local mean decomposition，RLMD）方法，结合快速傅里叶变换对实验得到的监测信号进行时频分析；然后，通过LS-DYNA软件模拟冲击荷载施加于岩体并产生应力波的过程，并将模拟应力波频率与实验监测应力波频率进行对比；最后，分析了弹性模量和密度发生改变时模拟应力波频率的变化。结果表明：在现场施加冲击荷载后，现场监测所得信号经过频谱分解会出现频率为1500～2300 Hz的多个极大振幅特征信号，与模拟应力波时频分析中获得的2203 Hz的主频率信号基本符合；模拟应力波频率与一维平面应力波推导的频率呈相反的变化趋势。
- 时频分析 /
- 特征频率 /
- 冲击荷载 /
- 振动信号 /
- 光纤传感技术
Abstract: Rock body will generate signals with different frequencies under the impact of external loads. This paper monitors the stress wave signals before and after the rock body is subjected to transient impact loads through the fiber-optic monitoring system with homemade probes, and conducts time-frequency analysis of the experimental monitoring signals using the robust local mean decomposition (RLMD) method combined with the fast Fourier transform (FFT). After that, LS-DYNA software is used to simulate the impact load applied to the rock body and generate the stress wave, and the frequency of the stress wave is verified against the frequency of the experimentally monitored stress wave. Finally, the relationship between the simulated stress wave frequency change under the change of elastic modulus and density is analyzed. Results show that the signals monitored in the field will appear as multiple signals with great amplitude after spectral decomposition of 1500–2300 Hz after the impact is applied in the field, which is consistent with the simulation result of the time-frequency analysis of the stress wave in the main frequency signal of 2203 Hz, and the opposite trend to the frequency change indicated by the one-dimensional planar stress wave derivation, which will be the next step of the research issue.
- time-frequency analysis /
- eigenfrequency /
- shock loading /
- vibration signals /
- fiber-optic sensing technology

HTML全文

图 1 监测设备探头内部以及监测系统

Figure 1. Monitoring equipment probe and the monitoring system

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图 2 实验方法和测点布置

Figure 2. Experimental method and layout of measurement points

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图 3 现场实验照片

Figure 3. Photos of field experiment

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图 4 噪声信号

Figure 4. Noise signals

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图 5 施加载荷后的监测信号

Figure 5. Monitoring signals after loading

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图 6 RLMD部分流程示意图

Figure 6. Schematic diagram of the RLMD process

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图 7 噪声信号频率

Figure 7. Noise signals frequency

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图 8 施加载荷后的监测信号频率

Figure 8. Monitoring signals frequency after loading

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图 9 数值模拟建模

Figure 9. Modeling of numerical simulation

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图 10 数值模拟得到的应力变化云图

Figure 10. Stress variation nephograms obtained from numerical simulation

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图 11 数值模拟得到的应力波及其频谱分析

Figure 11. Numerical stress wave and spectral analysis

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图 12 模拟应力波频率与改变物理参数的关系

Figure 12. Relationship of numerical stress wave frequency versus changing physical parameters

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表 1 岩体的RHT模型参数^[22]

Table 1. Parameters of RHT model of rock^[22]

ρ₀/(kg·m⁻³)	G/GPa	A	n	B	$ {Q}_{0} $	$ {{{{n}}}}_{{{\rm{f}}}} $	$ {A}_{\mathrm{f}} $	$ {g}_{{\rm{c}}}^{{*}} $
2 660	15.4	1.65	0.56	0.010 5	0.68	0.62	1.59	0.78

$ {g}_{\mathrm{t}}^{*} $	B₀	B₁	T₁/GPa	T₂/GPa	N	$ \beta_{\rm{c}} $	$ {\beta }_{\mathrm{t}} $	γ
0.7	0.9	0.9	45.4	0	4	0.032	0.025	0

D₁	D₂	A₁/GPa	A₂/GPa	A₃/GPa	$ {f}_{\rm{t}}^{{*}} $	$ {f}_{\rm{s}}^{{*}} $	$ \alpha_0 $	$ {p}_{\mathrm{e}\mathrm{l}} $/MPa
0.037	1	45.4	40.9	4.2	0.1	0.18	1.078	16

$ {p}_{\mathrm{c}\mathrm{o}\mathrm{m}\mathrm{p}} $/GPa	$ {\dot{\varepsilon }}^{\mathrm{t}} $/ms⁻¹	$ {\dot{\varepsilon }}^{\mathrm{c}} $/ms⁻¹	$ {\dot{\varepsilon }}_{0}^{\mathrm{c}} $/ms⁻¹	$ {\dot{\varepsilon }}_{0}^{\mathrm{t}} $/ms⁻¹	$ {\varepsilon }_{\mathrm{p}}^{\mathrm{m}} $	$ \xi $	$ {f}_{\mathrm{c}} $/MPa
0.6	3×10²²	3×10²²	3×10⁻⁸	3×10⁻⁹	0.01	0.44	48

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表 2 信号特征比较

Table 2. Comparison of signal characteristics

Signal	RMS frequency/Hz	1 800–2 500 Hz energy percentage/%	Shock factor
Analog signal	2 473.01	33.39	55.91
Shock signal 1	2 190.45	31.76	107.03
Shock signal 2	2 262.70	26.53	125.57
Noise signal	2 239.34	16.87	9.92
Human voice signal	1 979.62	12.97	7.17
Mechanical signal	1 080.73	3.63	19.24

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