[1]黄 金,吴庆良,陈 钒.基于CEEMDAN-WPT联合去噪的灾后求救信号 能量分布特征研究[J].南京理工大学学报(自然科学版),2020,44(02):194-201.[doi:10.14177/j.cnki.32-1397n.2020.44.02.010]
 Huang Jin,Wu Qingliang,Chen Fan.Study on energy distribution character about post-disaster rescue signal based on CEEMDAN-WPT denoising[J].Journal of Nanjing University of Science and Technology,2020,44(02):194-201.[doi:10.14177/j.cnki.32-1397n.2020.44.02.010]
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基于CEEMDAN-WPT联合去噪的灾后求救信号 能量分布特征研究
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
44卷
期数:
2020年02期
页码:
194-201
栏目:
出版日期:
2020-04-30

文章信息/Info

Title:
Study on energy distribution character about post-disaster rescue signal based on CEEMDAN-WPT denoising
文章编号:
1005-9830(2020)02-0194-08
作者:
黄 金1吴庆良1陈 钒2
1.西南大学 工程技术学院,重庆 400716; 2.中电建路桥集团有限公司,北京 100048
Author(s):
Huang Jin1Wu Qingliang1Chen Fan2
1.College of Engineering and Technology,Southwest University,Chongqing 400716,China; 2.China Power Construction Road and Bridge Group Co Ltd Beijing 100048,China
关键词:
灾后救援 自适应噪声完备集合经验模态分解 小波包 频带能量
Keywords:
post-disaster rescue complete ensemble empirical mode decomposition with adaptive noise wavelet packets band energy
分类号:
TD77
DOI:
10.14177/j.cnki.32-1397n.2020.44.02.010
摘要:
在隧道、矿山等复杂环境的地下工程灾后救援中,求救敲击信号微弱且经常淹没在噪声环境中,如何有效拾取求救敲击信号是灾后救援的关键问题。该文以现场敲击数据为基础,选取钢架、钢管、铁锤等不同类型的敲击信号进行对比研究。首先采用自适应噪声完备集合经验模态分解的改进算法(CEEMDAN)对信号进行分解,运用功率谱密度、相关系数和方差贡献率分析方法选择包含有效信息的IMF分量,再利用小波包阈值去噪(WPT)对信号进行分层滤波,最终得到信号的工作特征信息; 其次利用小波包分析模块分别求得每个节点重构信号的小波包频带能量,研究不同类型敲击信号在频带内的能量分布特性,并比较其频带能量的分布差异。结果表明,钢架、钢管、铁锤等敲击信号的能量分布大致相同,多集中于0~250 Hz; 通过能量频带细化分析发现,在能量波峰处,钢架敲击地面占比最少,铁锤敲击地面占比最多,该文方法可为灾后求救信号的有效识别提供基础,且为救援设备的传感器参数选择提供依据。
Abstract:
The post-disaster rescue environment of underground projects such as tunnels and mines under construction is complex,and the knock signal for rescue is weak and often submerged in the noise environment. How to effectively pick up the knock signal for rescue is the most important task of post-disaster rescue. Based on the on-site knocking data,different types of knock signals of steel frame,steel pipe and hammer are selected for comparative study. Firstly,the signal is decomposed with the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN). The power spectral density,correlation coefficient and variance contribution methods are used to screen the IMF containing real physical meaning. Then wavelet packet threshold de-noising(WPT)is used to filter the signal hierarchically. Secondly,the wavelet packet band energy of reconstructed signal at each node is obtained by using the wavelet packet analysis module. The energy distribution characteristics of different types of knock signals are studied,and the energy distribution differences in the frequency band are compared. The results show that the energy distribution of different types of knock signals of steel frame,steel pipe and hammer is approximately the same,mostly concentrated in 0~250 Hz. Through more detailed analysis of energy frequency band,the proportion of steel frame knocking on the ground is the least,and the proportion of hammer knocking on the ground is the largest. The research results provide a basis for effective identification of rescue signals after disasters and the selection of sensor parameters of rescue equipment.

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备注/Memo

备注/Memo:
收稿日期:2019-01-29 修回日期:2019-04-09
基金项目:重庆市基础前沿技术研究课题(2017jcyjAX0229); 中央高校基本科研业务费(SWU2120134207)
作者简介:黄金(1997-),男,主要研究方向:土木工程,E-mail:748198589@qq.com; 通讯作者:吴庆良(1985-),男,博士,讲师,主要研究方向:岩土工程安全监测、预警及灾后救援等,E-mail:wuqingliang@swu.edu.cn。
引文格式:黄金,吴庆良,陈钒. 基于CEEMDAN-WPT联合去噪的灾后求救信号能量分布特征研究[J]. 南京理工大学学报,2020,44(2):194-201.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2020-04-20