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核爆次声探测中闪电干扰信号特征分析
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作者 庞新良 张元 +3 位作者 程先友 常芸芬 青建华 马彦 《核电子学与探测技术》 CAS CSCD 北大核心 2013年第6期724-727,共4页
针对核爆次声探测系统中实测的闪电干扰次声信号进行了特征分析。采用去均值、去大气扰动、滤波、归一化等数据预处理之后,用统计理论对次声信号的频谱特性进行了分析,根据统计结论获得闪电次声信号的频谱特性。分析结果表明闪电次声信... 针对核爆次声探测系统中实测的闪电干扰次声信号进行了特征分析。采用去均值、去大气扰动、滤波、归一化等数据预处理之后,用统计理论对次声信号的频谱特性进行了分析,根据统计结论获得闪电次声信号的频谱特性。分析结果表明闪电次声信号特征有别于核爆次声信号特征,提取此特征值可组成能用于核爆次声探测分类识别的特征向量。 展开更多
关键词 核爆次声信号 闪电次声信号 分类算法 次声识别 核爆监测
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Acoustic emission source identification based on harmonic wavelet packet and support vector machine 被引量:4
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作者 于金涛 丁明理 +2 位作者 孟凡刚 乔玉良 王祁 《Journal of Southeast University(English Edition)》 EI CAS 2011年第3期300-304,共5页
In order to solve the fatigue damage identification problem of helicopter moving components, a new approach for acoustic emission (AE) source type identification based on the harmonic wavelet packet (HWPT) feature... In order to solve the fatigue damage identification problem of helicopter moving components, a new approach for acoustic emission (AE) source type identification based on the harmonic wavelet packet (HWPT) feature extraction and the hierarchy support vector machine (H-SVM) classifier is proposed. After a four-level decomposition of the HWPT, the energy feature of AE signals in different frequency bands is extracted, which overcomes the shortcomings of the traditional wavelet packet including energy leakage, and inflexible frequency band selection and different frequency resolutions on different levels. The H-SVM classifier is trained with a subset of the experimental data for known AE source types and tested using the remaining set of data. The results of pressure-off experiments on the specimens of carbon fiber materials indicate that the proposed approach can effectively implement the AE source type identification, and has a better performance in terms of computational efficiency and identification accuracy than the wavelet packet (WPT) feature extraction. 展开更多
关键词 harmonic wavelet packet hierarchy support vector machine acoustic emission source identification
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Monitoring and Recognition of Debris Flow Infrasonic Signals 被引量:11
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作者 LIU Dun-long LENG Xiao-peng +2 位作者 WEI Fang-qiang ZHANG Shao-jie HONG Yong 《Journal of Mountain Science》 SCIE CSCD 2015年第4期797-815,共19页
Low frequency infrasonic waves are emitted during the formation and movement of debris flows, which are detectable in a radius of several kilometers, thereby to serve as the precondition for their remote monitoring.Ho... Low frequency infrasonic waves are emitted during the formation and movement of debris flows, which are detectable in a radius of several kilometers, thereby to serve as the precondition for their remote monitoring.However, false message often arises from the simple mechanics of alarms under the ambient noise interference.To improve the accuracy of infrasound monitoring for early-warning against debris flows, it is necessary to analyze the monitor information to identify in them the infrasonic signals characteristic of debris flows.Therefore, a large amount of debris flow infrasound and ambient noises have been collected from different sources for analysis to sum up their frequency spectra, sound pressures, waveforms, time duration and other correlated characteristics so as to specify the key characteristic parameters for different sound sources in completing the development of the recognition system of debris flow infrasonic signals for identifying their possible existence in the monitor signals.The recognition performance of the system has been verified by simulating tests and long-term in-situ monitoring of debris flows in Jiangjia Gully,Dongchuan, China to be of high accuracy and applicability.The recognition system can provide the local government and residents with accurate precautionary information about debris flows in preparation for disaster mitigation and minimizing the loss of life and property. 展开更多
关键词 Debris flow INFRASOUND Interference noise MONITORING Signal recognition
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