共查询到20条相似文献,搜索用时 15 毫秒
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针对图像在传输过程中容易出现干扰的问题,该文通过研究图像的增强技术,通过对比分析,提出了一种结合阈值去噪与边缘优化的图像增强算法,该算法结合小波Contourlet 变换与人眼的视觉固有特性,有效地对分解后的图像系数进行分类,并结合改进边缘优化算法的增益因子来优化边缘区信号;而非边缘区采用改进后的软阈值去噪算法进行去噪处理.经实验,该算法具有准确性高与去噪能力强的特性,能够在去噪的同时有效保护边缘信号,与预期目标相符,具有一定的实用价值. 相似文献
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ABSTRACTTo improve the accuracy of the magnetic flux leakage (MFL) nondestructive testing in practical applications, it is very significant and key to deal with the detected MFL signals. As for the de-noising process of the MFL signals, a multilevel filtering approach based on wavelet de-noising combined with median filtering is proposed. By analyzing and comparing the de-noising properties of three wavelet families, i.e., Daubechies wavelet, Coiflets wavelet, and Symlets wavelet, two wavelet bases with the best de-noising performance are recognized and selected, namely sym6 and sym8 (the Symlets wavelet functions of order 6 and 8). Then, a new cascaded filter is constructed by combining sym6 and sym8 wavelets and cascading the median filtering method. An experimental platform is established to carry out the MFL testing, through the de-noising process for the measured MFL signals, and the results indicate that the proposed improved algorithm integrates with the merits of wavelet de-noising and median filtering. Compared with the traditional wavelet de-noising, the improved algorithm can not only improve the signal-to-noise ratio (SNR), but also reduce the de-noising error, resulting in enhancing signal quality to facilitate subsequent defect recognition. 相似文献
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With the rapid development of mechanical equipment, mechanical health monitoring field has entered the era of big data. Deep learning has made a great achievement in the processing of large data of image and speech due to the powerful modeling capabilities, this also brings influence to the mechanical fault diagnosis field. Therefore, according to the characteristics of motor vibration signals (nonstationary and difficult to deal with) and mechanical ‘big data’, combined with deep learning, a motor fault diagnosis method based on stacked de-noising auto-encoder is proposed. The frequency domain signals obtained by the Fourier transform are used as input to the network. This method can extract features adaptively and unsupervised, and get rid of the dependence of traditional machine learning methods on human extraction features. A supervised fine tuning of the model is then carried out by backpropagation. The Asynchronous motor in Drivetrain Dynamics Simulator system was taken as the research object, the effectiveness of the proposed method was verified by a large number of data, and research on visualization of network output, the results shown that the SDAE method is more efficient and more intelligent. 相似文献
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基于PCNN区域分割的图像邻域去噪算法 总被引:3,自引:0,他引:3
针对小波图像去噪方法中使用的NeighShrink方法,本文提出了一种有效的保护图像边缘的图像去噪算法.主要改进了NeighShrink方法中固定的邻域范围,根据图像自身的性质,自适应分割成不同的邻域对图像进行去噪处理;并进一步结合小波层内相关性,对各个不规则邻域加上固定的窗口,选择了几何距离更为接近且在同一不规则邻域内的系数,以完善NeighShrink方法.该算法采取平稳小波对含噪图像进行分解,以保持相位不变性,并对低频子带利用脉冲耦合神经网络模型进行图像分割,按照一定的规则将性质相似的像素点相接,得到原图像分割后的信息.在处理过程中利用得到的分割信息对边缘予以保护.实验结果表明,该方法在降低了图像噪声的同时又尽可能地保留了图像的边缘信息,是一种有效的去噪方法. 相似文献
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针对爆破振动信号去噪的问题,提出基于EEMD(ensemble empirical mode decomposition,集成经验模态分解)和小波变换结合的去噪方法。首先,采用EEMD将爆破振动信号分解成若干个IMF分量,然后利用自相关函数选择主要包含噪声的分量,再利用基于无偏估计的小波阈值去噪方法分别对含噪声分量进行去噪,最后,将去噪得到的分量之和与剩余分量相加,得到最终的消噪信号。该方法兼具了小波去噪以及EEMD去噪的优点,使得去噪后的信号信噪比更高,有用信息保留更完备,为爆破振动信号的去噪提供了一条新的途径。 相似文献
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渐近信号瞬态频率的提取 总被引:7,自引:0,他引:7
由渐近信号的小波分析出发,研究了渐近信号小波变换的渐近估计方法。着重讨论了渐近信号在小波变换下的特征,构造了信号瞬态频率提取的实现算法。最后结合仿真数值,得到了较好的结果。 相似文献
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针对分布式光纤管道安全预警系统检测信号的混沌特性,最大Lyapunov指数(λm ax)被定义为降噪指标用于评价各种小波及其阈值组合的降噪性能.基于小波阈值降噪法,采用不同的小波族系和阈值选取及重调方法对现场实测人工挖掘信号进行降噪处理.现场实验数据的分析结果表明检测信号存在混沌特征.在此基础上,λm ax被用于评价小波降噪性能.最后,通过对比实验结果,sym2小波、Sqtwolog阈值选取规则和M ln阈值重调方法,可以有效地消除现场实测信号中的噪声,达到最优的降噪效果. 相似文献
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基于小波包的振动信号去噪应用与研究 总被引:6,自引:1,他引:6
小波包分析算法对上一层的低频部分和高频部分同时进行细分,具有更为精确的局部分析能力。基于小波包变换的优良时频分析特性,论述小波包分析的基本原理,研究小波包在振动检测信号消噪处理中的应用,给出应用小波包变换对基于MSP430F449单片机的信号采集电路所检测到的振动信号进行消噪处理的实例。结果表明小波包变换的方法可以降低系统噪声影响,通过变换分解出高频噪声部分,利用小波包收缩的阈值量化方法能够更好地去掉高频部分,从而达到有效去除信号中噪声的目的。 相似文献
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缓冲特性曲线BP神经网络在Matlab上的方便实现 总被引:3,自引:0,他引:3
借助于Matlab,针对发泡聚乙烯的缓冲曲线的BP神经网络模型,详细探讨了样本、隐层数、隐层节点数、转移函数以及训练函数选取的不同,对模型结果精度及泛化能力的影响. 相似文献
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针对目前陀螺导航装备缺乏动态性能测试方法的状况,本文提出并实现了车载动态性能测试系统.并根据航向数据非连续变化的特点,提出了基于周期平移的小波阈值降噪算法.该算法通过对信号的分段周期平移、阈值降噪、逆平移的方法实现降噪,有效地克服了常规小波阈值降噪算法带来的Pseudo-Gibbs现象.仿真及实测数据表明采用该算法能够在有效剔除异常点、消除噪声的同时,消除降噪信号中的Pseudo-Gibbs现象.跑车实验表明车载动态性能测试系统为陀螺导航设备提供了有效的解决方案和统一的测试平台. 相似文献
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