有色金属科学与工程Issue(6)：73-77,5.
不同岩石脆性破坏声发射时频特性及信号识别
Time-frequency characteristic and signal recognition of acoustic emission generated from different rock brittle failure
摘要
Abstract
Considering the instability of acoustic emission (AE) signals of different rock fracture, the method for feature extraction and comprehensive recognition of AE is put forward combining with AE parameters, Welch spectrum, EMD and BP neural network. Through the acoustic emission experiment of three different brittle rocks under uniaxial compression, stress-strain curve and AE data are obtained. Comparative analysis is carried out towards the time-frequency characteristics of AE signal of rock samples. Feature vectors, such as AE parameters, Welch spectrum, and EMD energy entropy, are integrated with BP neural network to recognize different AE signal patterns. The results show that there are similarities and differences in characteristic evolving with stress or time of AE parameters of different rocks under uniaxial compression; characteristic differences of AE spectrum and energy distribution of different rocks can be well reflected from EMD and Welch spectrum; a high recognition rate can be reached by neural network with various characteristics of different rock acoustic emission.关键词
岩石力学/声发射/Welch谱/EMD能量熵/BP神经网络/信号识别Key words
rock mechanics/acoustic emission(AE)/Welch spectrum/EMD energy entropy/BP neural network/recognition分类
矿业与冶金引用本文复制引用
刘建伟,吴贤振,刘祥鑫,喻圆圆,胡维,尹丽冰..不同岩石脆性破坏声发射时频特性及信号识别[J].有色金属科学与工程,2013,(6):73-77,5.基金项目
国家自然科学基金资助项目（51174071）；江西省教育厅科技计划项目（GJJ12336）；江西省教育厅青年基金项目（GJJ12364）；河北联合大学青年基金资助项目（z201203）；江西理工大学研究生创新专项资金项目 （）
