基于小波包分析的AOD炉喷溅预报特征信息提取
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摘要
研究了用小波包分析方法从炉口音频信号中提取AOD炉喷溅预报特征信息的方法。采用db10(小波基函数)小波对喷溅发生前的特征信号进行4层小波包分解,结合快速傅里叶变换法及小波尺度谱进行时频特征分析,并研究了其各频带分解信号的能量比例特点。结果表明,喷溅前40s信号的主频值较正常信号有明显降低,0~312Hz与312~625Hz频段信号能量值比例变化显著。而且低频重构信号可以极好地滤除多种现场干扰,说明该时频特征可以作为准确预报喷溅的特征向量。最后,通过实验确定了8个特征向量值并分别与喷溅或正常信号的特征向量进行相关性比较,验证得出相关度0.95可作为喷溅预报的判定阈值。从而实现了喷溅预报特征信号的准确提取并可转化为计算机容易识别的数值特征。
Wavelet packet analysis method was used to study the extraction of splash prediction for AOD furnace from audio signal of furnace opening.Using db10 wavelet completed 4layers wavelet packet decomposition from characteristic signal before splash,combined with fast Fourier transform method and wavelet scale spectrum to analyse the time-frequency characteristic,the energy ratio characteristics of the signal frequency band decomposition.The test results show that the frequency value of the 40 ssignal before splash was significantly lower than normal signal,the signal energy ratio between 0-312 Hz and 312-625 Hz frequency band changed significantly.Additionally,the low frequency reconstruction signal was excellent in filtering a variety of scene interference signal,which shows that the time-frequency characteristics can forecast splash feature vector.Finally,8feature vectors was determined by the experiment and compared with the feature vector of splash or normal signals,and verified that relevance 0.95 can be used as a threshold of splash forecast decision.So that realizing the accurate feature extraction of splash prediction;the prediction result can be converted into computer numerical characteristics easily recognized.
Wavelet packet analysis method was used to study the extraction of splash prediction for AOD furnace from audio signal of furnace opening.Using db10 wavelet completed 4layers wavelet packet decomposition from characteristic signal before splash,combined with fast Fourier transform method and wavelet scale spectrum to analyse the time-frequency characteristic,the energy ratio characteristics of the signal frequency band decomposition.The test results show that the frequency value of the 40 ssignal before splash was significantly lower than normal signal,the signal energy ratio between 0-312 Hz and 312-625 Hz frequency band changed significantly.Additionally,the low frequency reconstruction signal was excellent in filtering a variety of scene interference signal,which shows that the time-frequency characteristics can forecast splash feature vector.Finally,8feature vectors was determined by the experiment and compared with the feature vector of splash or normal signals,and verified that relevance 0.95 can be used as a threshold of splash forecast decision.So that realizing the accurate feature extraction of splash prediction;the prediction result can be converted into computer numerical characteristics easily recognized.
引文
[1]Shakirov M,Boutchenkov A,Galperine G.Prediction and prevention of slopping in a bof[J].Iron and Steel Technology,2004,1(1):38.
[2]张大勇,张彩军,徐志荣.音频化渣技术在150t复吹转炉上的开发与应用[J].中国冶金,2007,17(8):20.
[3]孙海军,陈嘉颖,佟溥翘,等.音频控渣技术在冶炼高铬高锰铁水的应用[J].中国冶金,2012,22(10):15.
[4]王三忠,李文山,吕亚.转炉炼钢喷溅的控制及预防措施[J].河南冶金,2009,17(4):32.
[5]蒋晓放,刘春华,谢良德.宝钢300t转炉音平控渣技术的开发与应用[J].宝钢技术,2000,26(2):41.
[6]陈嘉颖.转炉造渣过程检测的声学原理及应用[J].钢铁研究学报,1999,11(3):57.
[7]李宏男,孙鸿敏.小波分析在土木工程领域中的应用[J].世界地震工程,2003,19(2):17.
[8]薛海涛,李永艳,崔春翔,等.基于小波分析的点焊过程喷溅特征信息提取[J].焊接学报,2007,28(5):38.
[9]王学军,马辉,孙伟,等.基于小波分析的转子碰摩故障特征提取[J].农业机械学报,2008,39(4):76.
[10]陈长征,罗跃纲,张省,等.基于小波分析的机械故障特征提取研究[J].机械强度,2001,23(2):148.
[11]曾宪伟,赵卫明,师海阔,等.利用小波包变换对地震信号进行时频分析时小波基函数的选取[J].地震研究,2010,33(4):36.
[2]张大勇,张彩军,徐志荣.音频化渣技术在150t复吹转炉上的开发与应用[J].中国冶金,2007,17(8):20.
[3]孙海军,陈嘉颖,佟溥翘,等.音频控渣技术在冶炼高铬高锰铁水的应用[J].中国冶金,2012,22(10):15.
[4]王三忠,李文山,吕亚.转炉炼钢喷溅的控制及预防措施[J].河南冶金,2009,17(4):32.
[5]蒋晓放,刘春华,谢良德.宝钢300t转炉音平控渣技术的开发与应用[J].宝钢技术,2000,26(2):41.
[6]陈嘉颖.转炉造渣过程检测的声学原理及应用[J].钢铁研究学报,1999,11(3):57.
[7]李宏男,孙鸿敏.小波分析在土木工程领域中的应用[J].世界地震工程,2003,19(2):17.
[8]薛海涛,李永艳,崔春翔,等.基于小波分析的点焊过程喷溅特征信息提取[J].焊接学报,2007,28(5):38.
[9]王学军,马辉,孙伟,等.基于小波分析的转子碰摩故障特征提取[J].农业机械学报,2008,39(4):76.
[10]陈长征,罗跃纲,张省,等.基于小波分析的机械故障特征提取研究[J].机械强度,2001,23(2):148.
[11]曾宪伟,赵卫明,师海阔,等.利用小波包变换对地震信号进行时频分析时小波基函数的选取[J].地震研究,2010,33(4):36.
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