基于BP神经网络的地震动信号识别
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摘要
通过数据采集得到三种不同类型车辆的地震动信号,采用小波消噪和特征提取,得到样本数据对神经网络进行训练,训练完成的神经网络就能实现车辆类型的识别。试验结果表明,BP神经网络对车辆目标具有较高的识别率,证明对地震动信号的特征提取方法是正确的,人工神经网络是有效的目标识别方法。
BP neural network is an important method in target recognition.Wavelet transformation is widely used in signal de-noising and feature extraction.The ground vibration signals of three different vehicles can be got by data acquisition.The wavelet de-noising and feature extraction are adopted to achieve the sample data to train the neural network.The successfully trained neural network can recognize the types of different vehicles.The experimental result shows that BP neural network has high recognition rate for vehicles,the feature extraction method of ground vibration signals is correct,and artificial neural network is an effective method for target recognition.
BP neural network is an important method in target recognition.Wavelet transformation is widely used in signal de-noising and feature extraction.The ground vibration signals of three different vehicles can be got by data acquisition.The wavelet de-noising and feature extraction are adopted to achieve the sample data to train the neural network.The successfully trained neural network can recognize the types of different vehicles.The experimental result shows that BP neural network has high recognition rate for vehicles,the feature extraction method of ground vibration signals is correct,and artificial neural network is an effective method for target recognition.
引文
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[3]胡昌华,李国华,周涛.基于Matlab7.X的系统分析与分析:小波分析[M].西安:西安电子科技大学出版社,2008.
[4]丛爽.面向Matlab工具箱的神经网络理论及应用[M].合肥:中国科技大学出版社,2009.
[5]周开利,康耀红.神经网络模型及其Matlab仿真程序设计[M].北京:清华大学出版社,2005.
[6]Matlab中文论坛.Matlab神经网络30个案例分析[M].北京:北京航天航空大学出版社,2010.
[7]LAN Jin-hui,NAHAVANDI Saeid,LAN Tian,et al.Recog-nition of moving ground targets by measuring and processing se-imic signal[J].Measurement,2005,37(2):189-199.
[8]LETALICK Dietmar,CARLSSON Tomas,HABBER-STAD Hans,et al.Target recognition by vibration fre-quency analysis[J].Laser Radar Technology and Applica-tions,2003,5086(5):246-252.
[9]WELLMAN M C,SROUR N,HILLIS D B.Feature ex-traction and fusion of acoustic and seismic sensors for targetidentification[J].SPIE,1997,3081:139-145.
[10]YEN Nai C,DRAGONETTE Louis R.Wave packet de-composition for acoustic target recognition.on automatictarget recognition[J]SPIE,1997,3069:436-445.
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