基于双正交小波变换QRS波检测方法研究与改进

心电图中QRS波是特征最明显的波形,是医学上诊断症状的重要依据,因此QRS波的正确识别成为心电检测的首要问题。由于心电信号是mV级的微弱信号,易受各种干扰影响;同时,目前常用的小波变换识别QRS波方法,计算量大,对系统要求高。针对这些问题,首先,提出使用双正交B样条小波基对心电信号进行处理,并通过在各尺度波形上检测极大值取代模极大值对的方式,搜索R波;然后,使用MIT-BIH心律失常数据库验证算法效果,并针对验证结果对原始算法进行检测策略的优化,改用自适应阈值的检测方式;同时,引进对部分可疑点搜索模极大值对的检查方法,减少假阳性的情况。算法经MIT-BIH验证,得到98.9%的准确率。     

可调谐半导体激光吸收光谱技术在脱硝微量氨检测系统中的应用

脱硝主要还原剂氨气的在线检测,是防止氨气对环境二次污染的有效手段。LGA-4500是基于可调谐半导体激光吸收光谱技术(TDLAS)的实时在线分析系统,可提供快速准确可靠的分析数据,是确保烟气排放安全、环保的一种理想分析系统。     

小波在输油管道泄漏检测定位系统中的应用研究

提出一种小波变换与负压波相结合,使用阈值降噪理论对输油管道泄漏点进行检测定位的方法。实验证明,基于此法的输油管道泄漏检测定位系统切实可行,极大地提高了信号的可检测性,并能提高定位精度、减少误报率。     

A Novel Approach Using a Two-Dimensional Wavelet Transform in Ball Grid Array (BGA) Substrate Conducting Path Inspections

This paper presents a novel approach for localising open and short boundary defect candidates on ball grid array (BGA) substrate conducting paths by using a 2D wavelet transform (2D WT). Once the potential defects are identified, traditional printed circuit board (PCB) inspection algorithms can focus on these candidates for further analysis to identify true open and short defects. The defect-detecting scope and the inspection effort are thereby significantly reduced. The binary BGA substrate image is processed. It shows only the boundaries of BGA substrate conducting paths, which are further decomposed directly by 2D WT. Since most of the wavelet energy is clustered at the edges of image objects, the wavelet transform modulus sum (WTMS) of each edge pixel on BGA substrate conducting path boundaries is initially collected. By comparing the WTMS of an edge pixel on decomposition level j with its WTMS on an adjacent decomposition level j + 1, an across-level ratio can be estimated to verify the irregularity of an edge pixel. That is, an edge pixel is classified as strongly irregular (e.g. potential open or short defects) if its across-level ratio reaches a predefined threshold. The proposed approach is template-free and easy to implement, so it is suitable for small-batch production. Real BGA substrates with synthetic boundary defects are used as test samples to evaluate the performance of the proposed approach. Experimental results show that the proposed method is capable of capturing all the open and short defects on BGA substrate conducting paths without missing any errors by using a selected across-level ratio threshold and appropriate decomposition level.     

基于提升小波包和神经网络的结构损伤检测

提出一种提升小波包分解、多传感器特征融合和神经网络模式分类相结合的结构损伤诊断方法.首先,对多个传感器采集的振动响应信号进行提升格式小波包分解,定义标准化相对能量并计算每个频带上的相对能量;然后,把这些传感器信号的小波包相对能量融合作为神经网络分类器的输入特征向量,实现损伤的诊断和评价.数值仿真结果表明,提升小波包分解的频带能量分布能够较好地反映结构的损伤特征;特征融合能够使不同传感器的信息相互补充,减小了损伤检测信息的不确定性,使诊断信息具有较高的精度和可靠性.     

Enhancing Weak Defect Features Using Undecimated and Adaptive Wavelet Transform for Estimation of Roller Defect Size in a Bearing

Defects in bearings affect the vibration level, resulting in and increase in temperature and decomposition of lubricant. Estimation of roller defect size is a complex task because it revolves as well as rotates during the motion. Signals from a defective roller of a bearing are superimposed by the signal from races, cage, and background noise. In this communication, a signal processing scheme is proposed that makes the signal suitable for estimating the size of the defect in the rolling element of a tapered roller bearing. To achieve this, in the first stage of processing, shift-invariant soft thresholding is applied to denoise the signal. It suppresses the noise without affecting defect-related features. Further, in the second stage of processing, continuous wavelet transform (CWT) using adaptive wavelet is applied. The adaptive wavelet is designed from the impulse extracted from the signal using the least squares fitting method. It results in higher coefficients in the region of impulse produced due to the defect. Finally, time marginal integration (TMI) of CWT coefficients is carried out for estimation of defect width. A study was performed for six different cases in which the size of the defect and orientation varies. Results of measurements of roller defect widths estimated using the proposed scheme were compared with defect widths calculated using image examination. For the nonoverlapping signature of defects (such as defects at 0° and 90° orientations), the maximum deviation in the width measurement using the proposed scheme is 6.52%. The error may increase when signature of two defects are overlapped.