Experimental study on acoustic waves of different types of debris flow using generalized S transform
-
摘要: 开展稀性、过渡性、黏性泥石流等3类泥石流声波模型试验后,通过引入窗函数参数,提出一种广义S变换,分析不同类型泥石流声波信号的时频特征,针对传统傅立叶变换的不足,运用小波包变换方法,提取声波信号的频带能量分布特征。研究表明：①相比较传统的时频分析手段,广义S变换具有优良的时频聚焦性和分辨率；②随着泥石流重度的增加,泥石流峰值频率向低频移动；③经小波包变换可将信号分解为8个频段（0～6.25,6.25～12.5,12.5～18.75,18.75～25,25～31.25,31.25～37.5,37.5～43.75,43.75～50 Hz）,稀性泥石流主要分布在S6-8,过渡性和黏性泥石流能量集中于S2-4内；④基于声波信号频率区间和频带能量可综合识别不同类型泥石流。Abstract: The physical model tests in laboratory for debris flow with three types of sub-viscous, intermediate and viscous debris flows are performed. By introducing the window function parameters, a generalized S transform is proposed to analyze the time-frequency characteristics for acoustic signals of different types of debris flows. At the same time, in view of the shortcomings of the traditional Fourier transform, a wavelet packet transform method is used to extract the distribution characteristics of frequency band energy of the acoustic signals. The results show that: (1) Compared with the traditional time-frequency analysis methods, the generalized S transform has excellent time-frequency focus and resolution. (2) With the increase of the bulk density of debris flow, the peak frequency of debris flow moves to low frequency. (3) The signals are decomposed into 8 frequency bands (0 ~ 6.25, 6.25 ~ 12.5, 12.5 ~ 18.75, 18.75 ~ 25, 25 ~ 31.25, 31.25 ~ 37.5, 37.5~43.75, 43.75 ~ 50 Hz) by using the wavelet packet transform, the sub-viscous debris flow is mainly distributed in S6-8, and the intermediate and viscous debris flows are concentrated in S2-4. (4) Comprehensive identification of different types of debris flows can be realized based on the frequency range and frequency band energy of acoustic signals.
-
-
![]()
图 4 声波信号广义S变换时频分布
Figure 4. Generalized S transform time-frequency distribution of acoustic signals
![]()
图 5 典型泥石流声波信号时频分布
Figure 5. Time-frequency distribution of acoustic signals for typical debris flows
![]()
图 6 不同类型泥石流频带能量分布
Figure 6. Distribution of wavelet packet frequency band for different debris flows
表 1 试验工况设计
Table 1 Design of experimental conditions
流体性质 稀性 过渡性 黏性 密度/(t·m-3) 1.3 1.5 1.7 1.9 2.0 试验组数 13 16 19 11 6 
下载: 导出CSV
表 2 不同类型泥石流小波包频带能量及其分布
Table 2 Energy and distribution of wavelet packet frequency band for different debris flows
频带序号 能量分布百分比/% 稀性 过渡性 黏性 S1 0.78 1.15 0.75 S2 8.50 16.99 9.89 S3 7.44 12.63 15.26 S4 9.35 17.73 24.27 S5 16.65 11.16 9.98 S6 24.78 8.36 15.46 S7 10.88 14.70 8.36 S8 21.61 17.29 16.03
下载: 导出CSV
表 3 蒋家沟泥石流不同频带能量分布
Table 3 Energy distribution in different frequency bands of debris flow in Jiangjia gully
S1 S2 S3 S4 S5 S6 S7 S8 5.63 9.14 35.73 21.66 0.46 0.86 19.48 7.04
下载: 导出CSV
-
[1] PILGER C, BITTNER M. Infrasound from tropospheric sources: impact on mesopause temperature?[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2009, 71(8/9): 816-822.
[2] 胡雨豪, 袁路, 马东涛, 等. 泥石流次声警报研究进展[J]. 地球科学进展, 2018, 33(6): 606-613. https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201806008.htm HU Yu-hao, YUAN Lu, MA Dong-tao, et al. Research progress on debris flow infrasound warning[J]. Advances in Earth Science, 2018, 33(6): 606-613. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201806008.htm
[3] 朱星, 许强, 汤明高, 等. 典型岩石破裂产生次声波试验研究[J]. 岩土力学, 2013, 34(5): 1306-1312. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX201305012.htm ZHU Xing, XU Qiang, TANG Ming-gao, et al. Experimental study of infrasound wave generated by typical rock fracture[J]. Rock and Soil Mechanics, 2013, 34(5): 1306-1312. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX201305012.htm
[4] 康玉梅, 朱万成, 白泉, 等. 基于小波变换时频能量分析技术的岩石声发射信号时延估计[J]. 岩石力学与工程学报, 2010, 29(5): 1010-1016. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201005021.htm KANG Yu-mei, ZHU Wan-cheng, BAI Quan, et al. Time-delay estimation of emission signals of rock using time-frequency energy analysis based on wavelet transform[J]. Chinese Journal of Rock Mechanics and Engineering, 2010, 29(5): 1010-1016. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201005021.htm
[5] 戴峰, 姜鹏, 徐奴文, 等. 蓄水期坝肩岩质边坡微震活动性及其时频特性研究[J]. 岩土力学, 2016, 37(增刊1): 359-370. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX2016S1048.htm DAI Feng, JIANG Peng, XU Nu-wen, et al. Study of microseismicity and its time-frequency characteristics of abutment rock slope during impounding period[J]. Rock and Soil Mechanics, 2016, 37(S1): 359-370. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX2016S1048.htm
[6] 张法全, 王海飞, 王国富, 等. 基于RST-NMF模型的微震信号时频分析和识别[J]. 振动与冲击, 2019, 38(17): 1-7. https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCJ201917002.htm ZHANG Fa-quan, WANG Hai-fei, WANG Guo-fu, et al. Time-frequency analysis and identification for micro-seismic signals based on RST-NMF model[J]. Journal of Vibration and Shock, 2019, 38(17): 1-7. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCJ201917002.htm
[7] COVIELLO V, ARATTANO M, COMITI F, et al. Seismic characterization of debris flows: insights into energy radiation and implications for warning[J]. Journal of Geophysical Research: Earth Surface, 2019, 124(6): 1440-1463.
[8] 章书成, 余南阳. 泥石流早期警报系统[J]. 山地学报, 2010, 28(3): 379-384. https://www.cnki.com.cn/Article/CJFDTOTAL-SDYA201003019.htm ZHANG Shu-cheng, YU Nan-yang. Early warning system to debris flow[J]. Mountain Research, 2010, 28(3): 379-384. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SDYA201003019.htm
[9] STOCKWELL R G. Localization of the complex spectrum: the S transform[J]. IEEE Transactions on Signal Processing, 1996, 44(4): 998-1001.
[10] 郑成龙, 王宝善. S变换在地震资料处理中的应用及展望[J]. 地球物理学进展, 2015, 30(4): 1580-1591. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201504012.htm ZHENG Cheng-long, WANG Bao-shan. Applications of strans form in seismic data processing[J]. Progress in Geophysics, 2015, 30(4): 1580-1591. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201504012.htm
[11] PINNEGAR C R, MANSINHA L. Time-local spectral analysis for non-stationary time series: The S-transform for noisy signals[J]. Fluctuation and Noise Letters, 2003, 3(3): L357-L364.
[12] MOUKADEM A, BOUGUILA Z, ABDESLAM D O, et al. A new optimized Stockwell transform applied on synthetic and real non-stationary signals[J]. Digital Signal Processing, 2015, 46: 226-238.
[13] 李力, 魏伟, 唐汝琪. 基于改进S变换的煤岩界面超声反射信号处理[J]. 煤炭学报, 2015, 40(11): 2579-2586. https://www.cnki.com.cn/Article/CJFDTOTAL-MTXB201511013.htm LI Li, WEI Wei, TANG Ru-qi. Processing of ultrasonic reflection signal from coal-rock interface using modified S-transform[J]. Journal of China Coal Society, 2015, 40(11): 2579-2586. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-MTXB201511013.htm
[14] 袁路. 泥石流次声影响因素的实验研究[D]. 成都: 中国科学院、水利部成都山地灾害与环境研究所, 2019. YUAN Lu. Experimental Study on the Influence Factors of Infrasound From Debris Flow[D]. Chengdu: Institute of Mountain Hazards and Environment, CAS, 2019. (in Chinese)
[15] 袁路, 胡雨豪, 马东涛, 等. 泥石流性质和规模对声波特性影响的实验研究[J]. 山地学报, 2018, 36(6): 889-897. https://www.cnki.com.cn/Article/CJFDTOTAL-SDYA201806008.htm YUAN Lu, HU Yu-hao, MA Dong-tao, et al. Influences of debris flow property and scale on acoustic wave characteristics by experiment[J]. Journal of Mountain Research, 2018, 36(6): 889-897. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SDYA201806008.htm
[16] 丁明涛, 韦方强. 云南蒋家沟泥石流成因及其防治措施探析[J]. 水土保持研究, 2008(1): 20-22. https://www.cnki.com.cn/Article/CJFDTOTAL-STBY200801007.htm DING Ming-tao, WEI Fang-qiang. Research on the cause and countermeasures of debris flow hazard of Jiangjia Valley, Yunnan Province[J]. Research of Soil and Water Conservation, 2008(1): 20-22. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-STBY200801007.htm
[17] 康志成, 崔鹏, 韦方强, 等. 中国科学院东川泥石流观测研究站观测实验资料集(1995—2000)[M]. 北京: 科学出版社, 2007. KANG Zhi-cheng, CUI Peng, WEI Fang-qiang, et al. Data Collection of Dongchuan Debris Flow Observation and Research Station Chinese Academy of Sciences (1995—2000)[M]. Beijing: China Science Publishing, 2007. (in Chinese)
计量
- 文章访问数:
- HTML全文浏览量: 0
- PDF下载量:
