煤矿生产系统干扰事件的离散小波变换检测
|
摘要
小波变换常用于数字信号传输的噪声检测与处理,为了检测煤矿生产系统中的突发事件,将其模拟为数字信号传输中的干扰,构建系统稳态方程和对应的扰动方程,根据离散小波变换原理,将煤矿生产系统中的监测数据分解为近似部分和细节部分,再进行离散变换。采用多尺度边缘检测法,由光滑后的一阶和二阶导数检测出信号的模极大值点即为瞬态突变点。将A矿记录到的瓦斯浓度监控数据进行可行性分析后,在MATLAB的wavelet工具中对该瓦斯浓度监控数据作离散小波变换,找到四个瓦斯浓度瞬态突变点,那么这四个时刻发生了煤与瓦斯突出事件。结果表明该方法简单、实用性强。据此从计算机实时监控和现场技术防突方面提出应对煤矿干扰事件的措施。
Wavelet transform is commonly used on noise detection and treatment of digital signal transmission.To detect emergencies in coal production systems,these emergencies were simulated as the events of interference in digital signal transmission.And the system steady-state equation and the corresponding perturbation equation were built.According to discrete wavelet transform theory,monitoring data in mine production system was decomposed into approximate part and detailed part,and then discretely transformed.Multi-scale edge detection method was used with smoothed first and second derivative,to find that modulus maxima points were transient abrupt-change points which we just need.Gas concentration monitor data of Mine A was feasibility analysed,and discrete wavelet transformed using wavelet tools in MATLAB.Four transient abrupt-change points were found and the results showed that on the four times there happened coal and gas outburst events.The concluding was that the method was simple and practical.Accordingly,in terms of computer real-time monitoring and on-site technology conflict prevention,some measures were put forward to deal with mine disturbance events.
Wavelet transform is commonly used on noise detection and treatment of digital signal transmission.To detect emergencies in coal production systems,these emergencies were simulated as the events of interference in digital signal transmission.And the system steady-state equation and the corresponding perturbation equation were built.According to discrete wavelet transform theory,monitoring data in mine production system was decomposed into approximate part and detailed part,and then discretely transformed.Multi-scale edge detection method was used with smoothed first and second derivative,to find that modulus maxima points were transient abrupt-change points which we just need.Gas concentration monitor data of Mine A was feasibility analysed,and discrete wavelet transformed using wavelet tools in MATLAB.Four transient abrupt-change points were found and the results showed that on the four times there happened coal and gas outburst events.The concluding was that the method was simple and practical.Accordingly,in terms of computer real-time monitoring and on-site technology conflict prevention,some measures were put forward to deal with mine disturbance events.
引文
[1]郑治真等.小波变换及其MATLAB工具的应用[M].北京:地震出版社,2001
[2]王世明.小波变换在图像信号消噪问题的应用研究[D].大连:大连理工大学,2009
[3]李良成,刘秋宏,张璟.小波变换在生物医学信号中的应用[J].中国医疗器械信息,2008,14(8):24-25LI Liang-cheng,LIU Qiu-hong,ZHANG Jing.Wavelettransform in the application of biomedical signal[J].Chi-na Medical Device Information,2008,14(8):24-25
[4]陈国金,梁军,钱积新.基于小波变换去噪的多元统计投影分析及其在化工过程监控中的应用[J].化工学报,2003,54(10):1478-1481CHEN Guo-jin,LIANG Jun,QIAN Ji-xin.Multivariate sta-tistical projection analysis based on wavelet transform de-noising and its application in chemical process monitoring[J].Chemical Science,2003,54(10):1478-1481
[5]姚菡,盛立芳,贺赟,等.利用连续小波提取近海大气湍流中的相干结构[J].中国海洋大学学报(自然科学版),2011,41(5):7-14YAO Han,SHENG Li-fang,HE Yun,et al.Coherentstructures extraction in coastal water atmospheric turbu-lence using[J].Journal of China Ocean University(Nat-ural Science Edition),2011,41(5):7-14
[6]严家斌,刘贵忠,柳建新.小波变换在天然电磁场信号时间序列处理中的应用[J].地质与勘探,2008,44(3):75-78YAN Jia-bin,LIU Gui-zhong,LIU Jian-xin.Application ofwavelet transform in natural electromagnetic signal timeseries[J].Geology and Exploration,2008,44(3):75-78
[7]雷宏宇.基于多分辨分析理论的数字图像融合方法[D].长沙:国防科技大学,2009
[8]李水根,吴纪桃.分形与小波[M].北京:科学出版社,2002
[9]汪理全,徐金海,屠世浩,等.矿业工程概论[M].徐州:中国矿业大学出版社,2004
[10]杜立东.小波变换在电能质量暂态信号检测中的应用[D].北京:华北电力大学(北京),2006
[11]杨福增,王峥,韩文霆,等.基于小波变换的红枣裂沟的多尺度边缘检测[J].农业工程学报,2005,21(6):92-95YANG Fu-zeng,WANG Zheng,HAN Wen-ting,et al.Multi-scale edge detection of dates fissure based onwavelet transform[J].Journal of Agricultural Engineer-ing,2005,21(6):92-95
[12]康福钧,于海勇,于斌.细水煤矿特大瓦斯爆炸事故的处理与分析[J].中国安全生产科学技术,2005,1(5):31-35KANG Fu-jun,YU Hai-yong,YU Bin.Large gas explo-sion incident processing and analysis in Xishui coal mine[J].China Safety Science and Technology,2005,1(5):31-35
[2]王世明.小波变换在图像信号消噪问题的应用研究[D].大连:大连理工大学,2009
[3]李良成,刘秋宏,张璟.小波变换在生物医学信号中的应用[J].中国医疗器械信息,2008,14(8):24-25LI Liang-cheng,LIU Qiu-hong,ZHANG Jing.Wavelettransform in the application of biomedical signal[J].Chi-na Medical Device Information,2008,14(8):24-25
[4]陈国金,梁军,钱积新.基于小波变换去噪的多元统计投影分析及其在化工过程监控中的应用[J].化工学报,2003,54(10):1478-1481CHEN Guo-jin,LIANG Jun,QIAN Ji-xin.Multivariate sta-tistical projection analysis based on wavelet transform de-noising and its application in chemical process monitoring[J].Chemical Science,2003,54(10):1478-1481
[5]姚菡,盛立芳,贺赟,等.利用连续小波提取近海大气湍流中的相干结构[J].中国海洋大学学报(自然科学版),2011,41(5):7-14YAO Han,SHENG Li-fang,HE Yun,et al.Coherentstructures extraction in coastal water atmospheric turbu-lence using[J].Journal of China Ocean University(Nat-ural Science Edition),2011,41(5):7-14
[6]严家斌,刘贵忠,柳建新.小波变换在天然电磁场信号时间序列处理中的应用[J].地质与勘探,2008,44(3):75-78YAN Jia-bin,LIU Gui-zhong,LIU Jian-xin.Application ofwavelet transform in natural electromagnetic signal timeseries[J].Geology and Exploration,2008,44(3):75-78
[7]雷宏宇.基于多分辨分析理论的数字图像融合方法[D].长沙:国防科技大学,2009
[8]李水根,吴纪桃.分形与小波[M].北京:科学出版社,2002
[9]汪理全,徐金海,屠世浩,等.矿业工程概论[M].徐州:中国矿业大学出版社,2004
[10]杜立东.小波变换在电能质量暂态信号检测中的应用[D].北京:华北电力大学(北京),2006
[11]杨福增,王峥,韩文霆,等.基于小波变换的红枣裂沟的多尺度边缘检测[J].农业工程学报,2005,21(6):92-95YANG Fu-zeng,WANG Zheng,HAN Wen-ting,et al.Multi-scale edge detection of dates fissure based onwavelet transform[J].Journal of Agricultural Engineer-ing,2005,21(6):92-95
[12]康福钧,于海勇,于斌.细水煤矿特大瓦斯爆炸事故的处理与分析[J].中国安全生产科学技术,2005,1(5):31-35KANG Fu-jun,YU Hai-yong,YU Bin.Large gas explo-sion incident processing and analysis in Xishui coal mine[J].China Safety Science and Technology,2005,1(5):31-35
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心