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对大型轴承表面损伤进行定位,有助于及时发现故障,加快修复速度。提出了一种使用单个声发射传感器对大型轴承表面损伤进行定位的方法。针对轴承环形结构,利用Lamb波频散特性,估计不同频段信号的可能模式和传播速度,使用Akaike信息准则(AIC)确定不同频段信号到达传感器的时间差。根据不同频带到达传感器的时间差估计不同模式下声发射源位置。针对传播模式不确定和仅利用一个时间差的镜像位置问题,改变传感器位置后对同一声发射源进行第二次定位,剔除不合理的传播模式,从而得到声发射源的唯一确定位置。通过在圆柱滚子推力轴承上进行的断铅试验,验证了该方法的有效性。 相似文献
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结构健康监测中常用声发射信号进行声发射源的定位及特征描述。多个冲击事件发生时,声发射信号是多个信号的混叠,而且混合方式未知,这使利用声发射信号对冲击源进行定位变得非常困难。而近年来兴起的基于独立分量分析的盲源分离技术为解决这一难题提供了可能。本文采用基于信息极大化原理的反馈网络结构对同时作用在铝梁上的两个冲击事件产生的声发射混合信号进行分离,估计出各个源信号到达传感器的时延后,运用两点直线定位公式对两个冲击源进行定位。混合仿真实验验证了基于信息极大化原理的独立分量分析方法估计时延的有效性,铝梁上的两源冲击实验,进一步表明运用独立分量分析方法能较好的解决多冲击源定位问题。 相似文献
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基于小波聚类的罐底声发射源聚集区域自动识别 总被引:1,自引:0,他引:1
利用声发射(AE)技术进行储罐罐底腐蚀检测过程中,不仅要获得声发射信号,还要根据声发射源分布的疏密了解罐底各处的腐蚀情况.传统方法一般采用人工方式进行腐蚀区域划分和识别,效率和准确率都低.为解决该问题,提出了一种基于小波聚类的罐底声发射源聚集区域自动识别方法.算法过程主要包括:划分网格、二维离散小波变换、区域查找和标记、确定声发射源所属区域等步骤.现场实验数据表明,该方法能够对任意分布形状的声发射源聚集区域进行自动识别,特别是能够将因加热盘管腐蚀产生的声发射源划分到同一区域,有效提高了对罐底腐蚀评估的效率和准确性.此外,以声发射源分布信息熵作为区域识别有效性的评价指标,选择信息熵最大的识别结果作为最终声发射源聚集区域识别结果最为有效. 相似文献
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无源雷达本身不发射电磁波,而是利用广播、电视外部信号作为辐射源照射目标来估计出目标位置并以此来跟踪目标。因为雷达自身不需要发射信号而是利用外来辐射信号探测目标,无源雷达可以大大提高雷达的生存能力。 相似文献
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摘 要:针对移动滚动轴承非接触声发射检测中,一个故障源信号可能被多个传感器采集,致使这些声信号包含故障信息不完整且存在重叠的问题,综合考虑声波传播理论、多传感器声信号时差关系、滚动轴承典型故障撞击频率等,建立滚动轴承故障非接触多传感器声信号融合方法。建立滚动轴承故障非接触多传感器声发射检测试验台,分别采集移动滚动轴承滚动体、外圈和内圈故障声信号。采用融合方法对同声源信号进行处理,利用信号相似理论证明了融合信号与故障源信号的相似程度高于各传感器声信号。采用声发射累计撞击计数法对融合处理后的滚动轴承不同故障声信号进行分析。结果表明,该融合算法能有效地处理多传感器接收的同声源信号,可利用融合后信号进行准确的故障识别。 相似文献
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Mingshun Jiang Shizeng Lu Yaozhang Sai Qingmei Sui Lei Jia 《Journal of Modern Optics》2013,60(20):1634-1640
An intelligent acoustic emission (AE) source localization technique by using fiber Bragg grating (FBG) sensors was investigated. Four FBGs sensing network was established for detecting the AE signal. And power intensity demodulation method was initialized employing narrow-band tunable laser. The intelligent AE source localization method was proposed based on wavelet transform, cross-correlation analysis, and least squares support vector machines (LS-SVM). LS-SVM modal’s input is signal time difference and output is AE source position. The location experiments were carried out on a 500 mm × 500 mm × 2 mm aluminum alloy plate. The results showed that the AE source position abscissa and ordinate localization errors are all less than 10 mm. The maximum and average localization errors are 8.65 and 6.78 mm, respectively. The research results provided a novel method for AE source localization by using FBG sensors. 相似文献
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Abstract: To overcome the disadvantages of current acoustic emission (AE) source location methods, such as classical approaches based on times of arrival and artificial neural networks based on AE signal features, support vector machines (SVM)‐based models have been employed to recognise AE source regions in structures. However, in some circumstances, it seems that a more accurate positioning of AE sources is needed. This study concerns the spatial three‐dimensional (3D) positioning (i.e. coordinates) for damages in hydraulic concrete structures using the least squares SVM (LS‐SVM) regression with AE signal features. The data of artificial discrete AE sources were acquired from simulated AE events on a hydraulic concrete specimen. Various combinations of signal features were chosen to adequately excavate effective information and to obtain the multi‐output LS‐SVM regression model of the best performance. The training and testing results show that the proposed model can realise the accurate spatial 3D positioning of damages in hydraulic concrete structures in laboratory situations and reduce human factors (e.g. judgment of AE propagation velocity, etc.) in the AE source location process. Meanwhile, the work remaining in taking this idea to a practical implementation was discussed. 相似文献
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S.P.Lu O.Y.Kwon K.J.Lee T.B.Kim 《材料科学技术学报》2003,19(3):201-205
A corrosion resistant CuNi cladding was deposited on SM45C (equivalent to AISI1045) substrate by DC inverse arc welding. During the welding process, a three channel acoustic emission (AE) monitoring system was applied to detect the crack signals generating from both the cladding process and after cladding. Characteristics of the welding crack signal and noise signal had been analyzed systematically. Based on the record time of the signal, the solidification crack and delayed crack were distinguished. By two-dimensional AE source location, the crack position was located,and then investigated by scanning electron microscopy (SEM). Results showed that the AE system could detect the welding crack with high sensitivity and the two-dimensional source location could accurately determine the crack position. Microstructures of the cladding and heat affected zone (HAZ) were examined. Dendrites in the cladding and coarse grains in the HAZ were found. 相似文献
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煤粉粒径的测量是燃煤电站一项重要的工作。针对目前筛分法存在的缺点,提出了一种结合声发射信号与BP神经网络在线识别煤粉粒径的方法。在频域中对噪声信号与煤粉声发射信号进行比较,确定了信号中反映煤粉粒径的频率区间,并利用小波包置零方法对信号进行去噪,在信噪比与信号平滑度方面比较了几种常用小波函数的去噪效果。通过功率谱分析发现了信号能量随煤粉粒径的变化特征。最后提取信号能量特征,利用BP神经网络对煤粉粒径进行识别。研究结果表明,结合声发射信号与BP神经网络识别煤粉粒径,可以获得良好的效果。 相似文献
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A New Signal Processing and Feature Extraction Approach for Bearing Fault Diagnosis using AE Sensors
In this paper, a new signal processing and feature extraction approach for bearing fault diagnosis using acoustic emission (AE) sensors is presented. The presented approach uses time-frequency manifold analysis to extract time-frequency manifold features from AE signals. It reconstructs a manifold by embedding AE signals into a high-dimensional phase space. The tangent direction of the neighborhood for each point is then used to approximate its local geometry. The variation of the manifolds representing different condition states of the bearing can be revealed by performing multiway principal component analysis. AE signals acquired from a bearing test rig are used to validate the presented approach. The test results have shown that the presented approach can interpret different bearing conditions and is effective for bearing fault diagnosis. 相似文献
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煤矿井下局部通风机实施“双风机双电源自动切换及三专两闭锁”功能,是保障煤矿掘进工作面通风安全的重要手段。本文对煤矿井下局部通风机“双风机双电源自动切换及三专两闭锁”功能进行了探讨。 相似文献
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声发射信号到达时间的信息,对于声发射事件的定位、识别以及声发射源机理分析都是非常重要的。实际应用中,常用人工读取或通过设定幅值阈值来获取信号的到达时间。针对以上常用方法的缺点,本文结合噪声信号的AR模型和声发射信号的AR模型,应用Akaike信息准则,实现了对声发射信号到达时间的自动识别。对实验数据的识别结果显示,该方法对信号的幅频特性变化比较敏感。在相同信噪比的情况下,该方法识别的偏差要小于阈值法。当信噪比较低时,阈值法可能会给出错误的结果,而该方法仍然能够给出较准确的结果。 相似文献
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综合新型木塑复合材料各类模式试样、源定位及信号的波形、常规参数、频谱、小波包最优树叶子节点能量谱等特征,对主损伤区附近的声发射事件,应用频谱分析和小波变换等信号处理手段提取特征参数,确定不同缺陷及损伤模式所对应的声发射特征信号,为日后进行神经网络模式识别奠定基础。由于新型木塑复合材料的声发射研究刚刚起步,对该材料的声发射特征还有待进一步的分析,常常需要借鉴其它复合材料的声发射检测结果,这势必会带来一定的局限性及适用性问题。对新型木塑复合材料的声发射参数的定量化还有待于大量实验数据的积累和归纳分析。 相似文献
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针对岩石声发射(AE)信号的低信噪比、随机性强、非平稳性等特点,提出了一种基于总体经验模态(EEMD)及单通道盲源分离(SCBSS)的AE信号滤波方法。将含有背景噪声的AE信号进行EEMD分解,得到一系列按频率从高到低排列的本征模函数(IMF);提取高频背景噪声信号与观测信号构建虚拟多通道观测信号;利用快速不动点优化算法(FastICA)对构建的虚拟多通道观测信号进行盲源分离(BSS),进而得到滤波后的AE信号。通过构造含噪声AE信号进行数值仿真实验及实测数据分析,将基于EEMD及SCBSS滤波方法与小波阈值滤波方法进行比较。实验结果表明:小波阈值滤波方法会导致滤波后的AE信号频域信息失真,影响滤波后的AE信号上升时间,能量等参数识别;该方法可以对含噪声AE信号进行有效地滤波处理,能够较好地滤除AE信号中的非平稳随机噪声,并且能够保护滤波后的AE信号频域信息。 相似文献