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 There are usually different noises in seismic data before stacking.In order to pickup effectual wave,we must remove noise waves such as surface wave and random noise with high frequency.The normal methods include:1D filter,fx filter,tp transform,fx prediction,etc.However,these methods have limitations that they only particular emphasis on a single characteristic of surface wave or are based on some hypothesis.Wavelet packet is a timefrequency analytical method,and can be better of dividing the seismic... There are usually different noises in seismic data before stacking.In order to pickup effectual wave,we must remove noise waves such as surface wave and random noise with high frequency.The normal methods include:1D filter,fx filter,tp transform,fx prediction,etc.However,these methods have limitations that they only particular emphasis on a single characteristic of surface wave or are based on some hypothesis.Wavelet packet is a timefrequency analytical method,and can be better of dividing the seismic data in detail than wavelet transform.It can describe the distribution of effectual wave and noise wave in timespace field at same frequency,comparing with traditional Fourier transform.By decomposing seismic data before stacking with wavelet packet,separate surfacewave and random noise of high frequency from seismic data.After processing wavelet packet reconstruction,we can eliminate noisewave and allow fewer damage of effectual wave.Through validating real data,wavelet packet is good for removing noise.  叠前地震资料是多种波的复合体,为了提取有效波,必需消除主要的干扰波,如面波、高频随机干扰波。一般的去噪方法有:一维滤波、滤波、变换、f—x预测等,但它们都侧重于考虑某一方面的单一特性或某种条件假设,这些方法具有一定的局限性。小波包变换是一种时频分析的方法,它对地震资料进行时频精细划分优于小波变换,与传统的Fourier变换相比,它能刻画出具有相同频率的有效波与干扰波在时间空间域的分布。经过小波包对叠前资料分解,可分离出面波、高频随机干扰等,然后再经过小波包重构,可有效地剔除干扰,且对有效波的伤害较少。经实际资料验证,小波包变换,确实是一个十分有效的去噪方法。  Traditionall filtering methods, such as fkfiltering,fx filtering, bandpass filtering,KL transform and Radon transform, eliminate the noises in seismic waves by the difference in frequency, wave number, time difference and amplitude. However, for seismic data acquired from mountainous regions, these methods fail to yield satisfactory results. In this paper, we try to eliminate the noises by the fine difference of wave shapes. Methods from mathematical morphology were adopted in seismic data processing.We studied... Traditionall filtering methods, such as fkfiltering,fx filtering, bandpass filtering,KL transform and Radon transform, eliminate the noises in seismic waves by the difference in frequency, wave number, time difference and amplitude. However, for seismic data acquired from mountainous regions, these methods fail to yield satisfactory results. In this paper, we try to eliminate the noises by the fine difference of wave shapes. Methods from mathematical morphology were adopted in seismic data processing.We studied the effects of the size and shape of structural elements on signals. Results from real data processing were presented.  传统的滤波方法一般是根据地震波的频率、波数、时差、振幅的差异进行去噪处理 ,如 f k滤波 ,f x 滤波、带通滤波、K L变换、拉冬变换等。对于山地地震资料 ,这些滤波方法的应用受到限制。可以从波形形态的细微差异上寻求新的滤波方法。根据数学形态学的滤波性质 ,考虑将其用在地震资料处理中。主要讨论了结构元素的尺寸、形状和幅值对处理结果的影响 ,并对实际地震资料做了处理。数学形态学的开闭运算 ,能滤除比结构元素小的亮细节和暗细节 ,可用其去除地震资料中的高频噪者。  A method is provided to eliminate the noise around driver's ears from heavy construction machinery such as grab and loading machinery caused by their powerful engine and hydraulic pump based on adaptive inverse control. A controller is constructed founded on Xfiltering employing DCT/LMS algorithm to drive the loudhailer installed near the driving seat, whose output waves of the same frequency and magnitude with noise transmitted to the cab will counteract each other, due to so called destructive disturbing... A method is provided to eliminate the noise around driver's ears from heavy construction machinery such as grab and loading machinery caused by their powerful engine and hydraulic pump based on adaptive inverse control. A controller is constructed founded on Xfiltering employing DCT/LMS algorithm to drive the loudhailer installed near the driving seat, whose output waves of the same frequency and magnitude with noise transmitted to the cab will counteract each other, due to so called destructive disturbing effect, by which reducing the noise partly around the motorman's ears.  针对挖掘机和装载机等重型工程机械作业时发动机及液压泵振动产生的司机耳边强噪声 ,提出了一种基于自适应逆控制的消除方法。利用X 滤波DCT LMS算法构造控制器 ,使之驱动驾驶室内扬声器的输出声波具有与传播到驾驶室内的噪声相同的频率和振幅 ,且处于反相。当两声波相遇时 ,由于破坏性干扰作用 ,它们相互部分抵消 ,从而降低了司机耳边噪声   << 更多相关文摘 
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