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基于CWT-MSTransformer的风电齿轮箱故障特征识别模型 认领 引用
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作者 张雪莹 伍轶明 《机电工程》 CAS 北大核心 2026年第5期945-956,共12页
针对风电齿轮箱受强噪声环境影响,导致智能诊断模型诊断准确率严重下降的问题,提出了一种基于连续小波变换和多尺度Transformer(CWT-MSTransformer)的风电齿轮箱故障诊断方法。首先,采用了离散小波变换将风电齿轮的振动信号分解为高频... 针对风电齿轮箱受强噪声环境影响,导致智能诊断模型诊断准确率严重下降的问题,提出了一种基于连续小波变换和多尺度Transformer(CWT-MSTransformer)的风电齿轮箱故障诊断方法。首先,采用了离散小波变换将风电齿轮的振动信号分解为高频分量和低频分量,并利用CWT将其转换为高频和低频时频图;然后,设计了一个多尺度分层特征提取模块,该模块通过不同尺度的动态卷积进行多尺度局部特征提取,并利用注意力机制关注重要的故障特征,剔除了冗余信息;最后,采用高效注意力机制改进了Swin-Transformer,并利用其进行全局特征提取,以挖掘细微的故障特征;采用两个齿轮箱数据集进行了噪声环境下的实验验证。研究结果表明:该方法在强噪声环境中的平均诊断准确率为93.13%,均高于对比方法,这说明CWT-MSTransformer具有良好的抗噪性能;此外,通过梯度类激活映射(Grad-CAM)进行了特征学习可视化处理,结果表明CWT-MSTransformer能够聚焦关键的故障特征。这意味着在噪声环境下,该方法不仅能够有效地识别故障特征,而且能够增强模型的可解释性,在现实故障诊断中具有可行性。 展开更多
关键词 齿轮传动 故障诊断方法 风电机组 基于连续小波变换和多尺度Transformer 模型可解释性增强 梯度类激活映射
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Drive-by damage detection and localization exploiting continuous wavelet transform and multiple sparse autoencoders 认领 引用
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作者 Lorenzo Bernardini Francesco Morgan Bono Andrea Collina 《Railway Engineering Science》 EI 2025年第4期721-745,共25页
Drive-by techniques for bridge health monitoring have drawn increasing attention from researchers and practitioners,in the attempt to make bridge condition-based monitoring more cost-efficient.In this work,the authors... Drive-by techniques for bridge health monitoring have drawn increasing attention from researchers and practitioners,in the attempt to make bridge condition-based monitoring more cost-efficient.In this work,the authors propose a drive-by approach that takes advantage from bogie vertical accelerations to assess bridge health status.To do so,continuous wavelet transform is combined with multiple sparse autoencoders that allow for damage detection and localization across bridge span.According to authors’best knowledge,this is the first case in which an unsupervised technique,which relies on the use of sparse autoencoders,is used to localize damages.The bridge considered in this work is a Warren steel truss bridge,whose finite element model is referred to an actual structure,belonging to the Italian railway line.To investigate damage detection and localization performances,different operational variables are accounted for:train weight,forward speed and track irregularity evolution in time.Two configurations for the virtual measuring channels were investigated:as a result,better performances were obtained by exploiting the vertical accelerations of both the bogies of the leading coach instead of using only one single acceleration signal. 展开更多
关键词 Drive-by Sparse autoencoder Steel truss railway bridge Continuous wavelet transform Damage detection Damage localization
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基于VMD-CWT和Swin Transformer的滚动轴承故障诊断方法 认领 引用 被引量：4
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作者 曾信凌 龙江 +1 位作者 魏友 吴云飞 《机械制造与自动化》 2025年第6期18-23,34,共6页
针对滚动轴承故障信号存在噪声干扰且故障特征提取不精确的问题,提出一种基于变分模态分解(VMD)、连续小波变换(CWT)和Swin Transformer网络相结合的滚动轴承智能故障诊断方法。利用变分模态分解对信号进行降噪,通过CWT将重构后的信号... 针对滚动轴承故障信号存在噪声干扰且故障特征提取不精确的问题,提出一种基于变分模态分解(VMD)、连续小波变换(CWT)和Swin Transformer网络相结合的滚动轴承智能故障诊断方法。利用变分模态分解对信号进行降噪,通过CWT将重构后的信号转换为时频图;以二维特征图像作为输入训练Swin Transformer模型,实现滚动轴承的智能故障诊断。试验结果表明:VMD-CWT结合Swin Transformer网络的方法具有更高的故障诊断精度,实测数据中测试集准确率高达99.79%。 展开更多
关键词 滚动轴承 变分模态分解 连续小波变换 Swin Transformer 故障诊断
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DETECTION OF INCIPIENT LOCALIZED GEAR FAULTS IN GEARBOX BY COMPLEX CONTINUOUS WAVELET TRANSFORM 认领 引用 被引量：6
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作者 HanZhennan XiongShibo LiJinbao 《Chinese Journal of Mechanical Engineering》 EI CAS 2003年第4期363-366,共4页
As far as the vibration signal processing is concerned, composition ofvibration signal resulting from incipient localized faults in gearbox is too weak to be detected bytraditional detecting technology available now. ... As far as the vibration signal processing is concerned, composition ofvibration signal resulting from incipient localized faults in gearbox is too weak to be detected bytraditional detecting technology available now. The method, which includes two steps: vibrationsignal from gearbox is first processed by synchronous average sampling technique and then it isanalyzed by complex continuous wavelet transform to diagnose gear fault, is introduced. Twodifferent kinds of faults in the gearbox, i.e. shaft eccentricity and initial crack in tooth fillet,are detected and distinguished from each other successfully. 展开更多
关键词 Gear transmission Fault diagnosis Synchronous average sampling technique Complex continuous wavelet transform
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PARAMETERS OPTIMIZATION OF CONTINUOUS WAVELET TRANSFORM AND ITS APPLICATION IN ACOUSTIC EMISSION SIGNAL ANALYSIS OF ROLLING BEARING 认领 引用 被引量：8
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作者 ZHANG Xinming HE Yongyong HAO Rujiang CHU Fulei 《Chinese Journal of Mechanical Engineering》 EI CAS 2007年第2期104-108,共5页
Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform （CWT） has been successfully used in the field of fault diagnosis. The principle of ... Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform （CWT） has been successfully used in the field of fault diagnosis. The principle of scale selection in CWT is discussed. Based on genetic algorithm, an optimization strategy for the waveform parameters of the mother wavelet is proposed with wavelet entropy as the optimization target. Based on the optimized waveform parameters, the wavelet scalogram is used to analyze the simulated acoustic emission （AE） signal and real AE signal of rolling bearing. The results indicate that the proposed method is useful and efficient to improve the quality of CWT. 展开更多
关键词 Rolling bearing Fault diagnosis Acoustic emission （AE） Continuous wavelet transform （CWT） Genetic algorithm
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基于参数优化的VMD和CWT结构密集模态参数识别 认领 引用
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作者 赵丽洁 孙子一 +2 位作者 王昊 解咏平 练继建 《振动与冲击》 EI CSCD 北大核心 2026年第4期51-60,共10页
针对变分模态分解的模态分解数K及二次惩罚因子α难以确定和连续小波变换对结构密集模态参数识别精度不高的问题,提出了一种基于参数优化变分模态分解(variational mode decomposition,VMD)与连续小波变换(continuous wavelet transform... 针对变分模态分解的模态分解数K及二次惩罚因子α难以确定和连续小波变换对结构密集模态参数识别精度不高的问题,提出了一种基于参数优化变分模态分解(variational mode decomposition,VMD)与连续小波变换(continuous wavelet transform,CWT)相结合的结构密集模态参数识别方法。以能量集中度与互信息构建全新综合目标函数,引入蜣螂优化算法自适应地搜寻最佳[K,α]参数组合;其次,基于最优[K,α]参数组合,对具有密集模态的振动响应信号进行VMD,结合皮尔逊相关系数指标筛选有效模态分量;最后,对有效模态分量进行CWT识别结构的模态频率和模态阻尼比。通过四自由度密集模态系统仿真算例表明,相比传统CWT算法,参数优化VMD结合CWT的方法,识别结构的密集模态参数精度更高,并具备一定的抗噪声性能;五层框架结构模型试验进一步验证了所提方法的实用性。 展开更多
关键词 模态参数识别 变分模态分解(VMD) 连续小波变换(CWT) 密集模态
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Inversion formula and Parseval theorem for complex continuous wavelet transforms studied by entangled state representation 认领 引用
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作者 胡利云 范洪义 《Chinese Physics B》 SCIE EI CAS 2010年第7期263-267,共5页
In a preceding letter （2007 Opt. Lett. 32 554） we propose complex continuous wavelet transforms and found Laguerre-Gaussian mother wavelets family. In this work we present the inversion formula and Parseval theorem ... In a preceding letter （2007 Opt. Lett. 32 554） we propose complex continuous wavelet transforms and found Laguerre-Gaussian mother wavelets family. In this work we present the inversion formula and Parseval theorem for complex continuous wavelet transform by virtue of the entangled state representation, which makes the complex continuous wavelet transform theory complete. A new orthogonal property of mother wavelet in parameter space is revealed. 展开更多
关键词 Parseval theorem complex continuous wavelet transforms entangled state representation
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On Inversion of Continuous Wavelet Transform 认领 引用 被引量：2
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作者 Lintao Liu Xiaoqing Su Guocheng Wang 《Open Journal of Statistics》 2015年第7期714-720,共7页
This study deduces a general inversion of continuous wavelet transform (CWT) with timescale being real rather than positive. In conventional CWT inversion, wavelet’s dual is assumed to be a reconstruction wavelet or ... This study deduces a general inversion of continuous wavelet transform (CWT) with timescale being real rather than positive. In conventional CWT inversion, wavelet’s dual is assumed to be a reconstruction wavelet or a localized function. This study finds that wavelet’s dual can be a harmonic which is not local. This finding leads to new CWT inversion formulas. It also justifies the concept of normal wavelet transform which is useful in time-frequency analysis and time-frequency filtering. This study also proves a law for CWT inversion: either wavelet or its dual must integrate to zero. 展开更多
关键词 Continuous Wavelet Transform Wavelet’s Dual Inversion Normal Wavelet Transform Time-Frequency Filtering
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样本不均衡条件下滚动轴承故障FCWT-DDIM-SwinT识别方法 认领 引用
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作者 孙祥海 邱明 +4 位作者 李军星 张松林 刘志卫 刘静涛 高锐 《河南科技大学学报（自然科学版）》 CAS 北大核心 2026年第1期53-62,M0005,共10页
针对滚动轴承故障识别中因样本不均衡导致准确率低的问题,提出一种去噪扩散隐式模型(DDIM)结合Swin Transformer(SwinT)的故障识别方法。首先,对采集到的滚动轴承原始振动信号进行快速连续小波变换(FCWT),将其重构为二维时频图像。然后... 针对滚动轴承故障识别中因样本不均衡导致准确率低的问题,提出一种去噪扩散隐式模型(DDIM)结合Swin Transformer(SwinT)的故障识别方法。首先,对采集到的滚动轴承原始振动信号进行快速连续小波变换(FCWT),将其重构为二维时频图像。然后,使用DDIM扩充原始不均衡数据集,构建出故障样本类别分布均衡数据集。最后,将均衡数据集应用于SwinT模型的训练过程,从而实现滚动轴承多种故障类型的准确诊断。工程实例表明:利用DDIM能够有效解决故障样本不均衡的问题;同时,与其他识别模型相比,SwinT模型的平均识别准确率提高了5.72%,具有更优越的轴承故障识别能力。 展开更多
关键词 滚动轴承 快速连续小波变换 去噪扩散隐式模型 Swin Transformer 故障识别
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联合最优FOD_CWT与光谱指数的盐碱农田土壤有机质估算 认领 引用
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作者 左超燕 贾科利 +3 位作者 叶静雨 李浩宇 张俊华 丁启东 《水土保持通报》 CAS CSCD 北大核心 2026年第4期160-171,共12页
[目的]为实现盐碱农田土壤有机质高精度监测,提出了一种分数阶微分(FOD)、连续小波变换(CWT)与光谱指数构建的框架。[方法]以新疆伽师县两块盐碱农田为试验区域,以地面高光谱反射率数据和野外采样数据为数据源,对原始高光谱反射率实现... [目的]为实现盐碱农田土壤有机质高精度监测,提出了一种分数阶微分(FOD)、连续小波变换(CWT)与光谱指数构建的框架。[方法]以新疆伽师县两块盐碱农田为试验区域,以地面高光谱反射率数据和野外采样数据为数据源,对原始高光谱反射率实现步长为0.25的微分变换,在此基础上,进行6个尺度连续小波变换,选取最优的微分阶数和小波分解尺度组合构建比值指数(RI)、差值指数(DI)和归一化差异指数(NDI),并构建随机森林(RF)模型、极端梯度提升(XGBoost)模型、支持向量回归(SVR)模型和轻量级梯度提升机(LightGBM)模型定量估算土壤有机质含量。[结果]FOD处理后,0.75阶微分光谱反射率与有机质相关性最高,明显优于原始光谱与整数阶变换;FOD_CWT联合处理后,0.25阶FOD组合2~5尺度表现最优,相关系数达0.726;光谱反射率数据与有机质相关性最高(提升0.197),可有效提升光谱与土壤有机质相关性;FOD_CWT_XGBoost组合的预测性能最优,测试集R2达0.744。[结论]分数阶微分与小波变换组合能深度挖掘光谱信息,所构建的模型适用于土壤有机质估算。 展开更多
关键词 有机质 地面高光谱 分数阶微分 连续小波变换 光谱指数 机器学习
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Natural frequencies and damping estimation based on continuous wavelet transform 认领 引用
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作者 代煜 孙和义 +1 位作者 李慧鹏 唐文彦 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2008年第6期794-800,共7页
The continuous wavelet transform(CWT)based method was improved for estimating the natural frequencies and damping ratios of a structural system in this paper.The appropriate scale of CWT was selected by means of the l... The continuous wavelet transform(CWT)based method was improved for estimating the natural frequencies and damping ratios of a structural system in this paper.The appropriate scale of CWT was selected by means of the least squares method to identify the systems with closely spaced modes.The important issues related to estimation accuracy such as mode separation and end effect,were also investigated.These issues were associated with the parameter selection of wavelet function based on the fitting error of least squares.The efficiency of the method was confirmed by applying it to a simulated 3dof damped system with two close modes. 展开更多
关键词 modal parameters continuous wavelet transform least squares method
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基于CWT-PDCNN的船舶电机故障诊断研究 认领 引用
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作者 尚垣吉 尚前明 蒋婉莹 《舰船科学技术》 北大核心 2026年第2期102-107,共6页
针对船舶电机在复杂运行环境中易出现多种故障、且工况变化对故障特征提取造成干扰的问题,构建了一种基于连续小波变换(Continuous Wavelet Transform,CWT)与并行双通道卷积神经网络(Parallel Dual-Channel CNN,PDCNN)相结合的混合工况... 针对船舶电机在复杂运行环境中易出现多种故障、且工况变化对故障特征提取造成干扰的问题,构建了一种基于连续小波变换(Continuous Wavelet Transform,CWT)与并行双通道卷积神经网络(Parallel Dual-Channel CNN,PDCNN)相结合的混合工况故障诊断模型。该方法将原始振动信号分别进行一维特征提取和二维CWT时频图变换,形成双模态输入数据,对数据提取多尺度特征后使用PDCNN进行特征融合与分类。测试结果表明,所提出模型在混合工况下的故障识别准确率达92.10%,相比仅使用一维信号或二维图像输入的模型准确率分别提高了16.88%与6.28%。同时,不同故障类型的特征区分度在t分布随机邻域嵌入(t-distributed Stochastic Neighbor Embedding,t-SNE)可视化中表现明显。研究结果说明,融合CWT与PDCNN结构能够有效提升电机在复杂工况下的故障诊断精度与鲁棒性,具有较强的工程应用潜力。 展开更多
关键词 电机 故障诊断 连续小波变换 卷积神经网络
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基于GASF-CWT转换和特征融合的变压器故障诊断方法 认领 引用
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作者 穆娜瓦尔·阿不都克热木 吐松江·卡日 +3 位作者 谢丽蓉 张淑敏 刘鹏伟 韦强宇 《现代电子技术》 北大核心 2026年第2期95-102,共8页
针对电力变压器一维油色谱特征数据输入限制深度学习模型性能,以及单一数据转换方法无法充分反映原始序列数据重要特征,从而影响故障诊断准确率等问题,提出一种基于GASF-CWT转换和特征融合的变压器故障诊断方法。首先,使用格拉姆求和角... 针对电力变压器一维油色谱特征数据输入限制深度学习模型性能,以及单一数据转换方法无法充分反映原始序列数据重要特征,从而影响故障诊断准确率等问题,提出一种基于GASF-CWT转换和特征融合的变压器故障诊断方法。首先,使用格拉姆求和角场(GASF)、连续小波变换(CWT)将一维变压器故障样本数据转换为特征图像。其次,以ResNet50网络作为基础模型,并在其特征提取层添加特征融合模块,将转换后的两种图像同时输入模型,为模型提供更全面的特征信息;最后,在模型的残差结构中添加高效通道注意力(ECA)模块,增强网络对重要特征的关注并抑制无关特征,实现高效特征提取的变压器故障诊断方法。实验结果表明,所提方法的故障诊断准确率达到94.64%,相比于性能最好的常用RF方法提升6.38%,具有较好的诊断能力,可为电力变压器安全可靠运行提供重要参考。 展开更多
关键词 电力变压器 故障诊断 格拉姆求和角场 连续小波变换 特征融合 高效通道注意力
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基于CWT时频编码与双分支特征融合的滚动轴承故障诊断 认领 引用
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作者 刘楠 苑宇 徐奕 《自动化与仪表》 2026年第6期70-75,共6页
针对传统卷积神经网络难以有效捕捉振动信号时频图像中长距离依赖关系的问题,提出一种基于CWT时频编码与双分支特征融合的滚动轴承故障诊断模型CWT-SwinCNNGAM。首先,利用连续小波变换将一维振动信号编码为二维时频图像;随后将图像分别... 针对传统卷积神经网络难以有效捕捉振动信号时频图像中长距离依赖关系的问题,提出一种基于CWT时频编码与双分支特征融合的滚动轴承故障诊断模型CWT-SwinCNNGAM。首先,利用连续小波变换将一维振动信号编码为二维时频图像;随后将图像分别输入Swin Transformer和CNN-GAM分支,前者提取全局语义信息与长距离依赖关系,后者提取局部纹理特征,并引入全局注意力机制强化关键区域响应,两条分支特征在通道维度融合,实现全局与局部特征的互补增强。最后通过Softmax层实现故障分类。在CWRU数据集上平均诊断准确率达99.9%,在大连交通大学轴承数据集上展现出优异的诊断性能,充分验证了所提模型卓越的诊断性能与良好的泛化能力。 展开更多
关键词 滚动轴承 故障诊断 连续小波变换 Swin Transformer 注意力机制
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Study of the Functions of Wavelet Packet Transform (WPT) and Continues Wavelet Transform (CWT) in Recognizing the Damage Specification 认领 引用 被引量：5
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作者 Mahdi Koohdaragh M. A. Loffollahi Yaghin +1 位作者 S. Sepehr F. Hosseyni 《Journal of Civil Engineering and Architecture》 2011年第9期856-859,共4页
Modem and efficient methods focus on signal analysis and have drawn researchers＇ attention to it in recent years. These methods mainly include Continuous Wavelet and Wavelet Packet transforms. The main advantage of t... Modem and efficient methods focus on signal analysis and have drawn researchers＇ attention to it in recent years. These methods mainly include Continuous Wavelet and Wavelet Packet transforms. The main advantage of the application of these Wavelets is their capacity to analyze the signal position in different occasions and places. However, in sites with high frequencies its resolution becomes much more difficult. Wavelet packet transform is a more advanced form of continuous wavelets and can make a perfect level by level resolution for each signal. Although very few studies have been done in the field. In order to do this, in the present study, f^st there was an attempt to do a modal analysis on the structure by the ANSYS finite elements software, then using MATLAB, the wavelet was investigated through a continuous wavelet analysis. Finally the results were displayed in 2-D location-coefficient figures. In the second form, transient-dynamic analysis was done on the structure to find out the characteristics of the damage and the wavelet packet energy rate index was suggested. The results indicate that suggested index in the second form is both practical and applicable, and also this index is sensitive to the intensity of the damage. 展开更多
关键词 Wavelet packet transform continues wavelet transform dynamic analysis energy rate index.
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基于CWT-CNN-SVM模型的地铁列车转向架轴箱轴承故障诊断 认领 引用
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作者 孙强 姚猛 +2 位作者 王泽红 薛晏 徐少男 《高速铁路新材料》 CSCD 2026年第3期13-19,共7页
为提升地铁列车转向架轴箱轴承故障诊断的可靠性与故障类别识别精度,提出一种融合连续小波变换(CWT)、卷积神经网络(CNN)和支持向量机(SVM)的故障诊断模型。首先,通过CWT将原始振动信号转换为时频图像,实现信号时域-频域特征的联合表征... 为提升地铁列车转向架轴箱轴承故障诊断的可靠性与故障类别识别精度,提出一种融合连续小波变换(CWT)、卷积神经网络(CNN)和支持向量机(SVM)的故障诊断模型。首先,通过CWT将原始振动信号转换为时频图像,实现信号时域-频域特征的联合表征;随后将时频图像输入CNN模型,完成自适应故障特征的深度挖掘与提取;最后采用SVM对提取的高维特征进行分类,实现故障类别的精准识别。以美国凯斯西储大学轴承数据集与北京交通大学BJTU-RAO地铁转向架轴箱轴承数据集为试验基础,对该模型开展系统的试验验证。结果表明:该CWT-CNN-SVM模型的故障诊断准确率可达99%以上,识别精度显著优于其他对比模型;同时该方法在小样本与噪声干扰工况下均表现出良好的适应性,展现出优异的鲁棒性与泛化能力,为地铁列车转向架轴箱轴承的故障诊断提供了有效方法。 展开更多
关键词 地铁 转向架 滚动轴承 故障诊断 连续小波变换 卷积神经网络 支持向量机
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Performance of Continuous Wavelet Transform over Fourier Transform in Features Resolutions 认领 引用
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作者 Michael K. Appiah Sylvester K. Danuor Alfred K. Bienibuor 《International Journal of Geosciences》 CAS 2024年第2期87-105,共19页
This study presents a comparative analysis of two image enhancement techniques, Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT), in the context of improving the clarity of high-quality 3D seismic d... This study presents a comparative analysis of two image enhancement techniques, Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT), in the context of improving the clarity of high-quality 3D seismic data obtained from the Tano Basin in West Africa, Ghana. The research focuses on a comparative analysis of image clarity in seismic attribute analysis to facilitate the identification of reservoir features within the subsurface structures. The findings of the study indicate that CWT has a significant advantage over FFT in terms of image quality and identifying subsurface structures. The results demonstrate the superior performance of CWT in providing a better representation, making it more effective for seismic attribute analysis. The study highlights the importance of choosing the appropriate image enhancement technique based on the specific application needs and the broader context of the study. While CWT provides high-quality images and superior performance in identifying subsurface structures, the selection between these methods should be made judiciously, taking into account the objectives of the study and the characteristics of the signals being analyzed. The research provides valuable insights into the decision-making process for selecting image enhancement techniques in seismic data analysis, helping researchers and practitioners make informed choices that cater to the unique requirements of their studies. Ultimately, this study contributes to the advancement of the field of subsurface imaging and geological feature identification. 展开更多
关键词 Continuous Wavelet Transform (CWT) Fast Fourier Transform (FFT) Reservoir Characterization Tano Basin Seismic Data Spectral Decomposition
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COMPUTATION OF CONTINUOUS WAVELET TRANSFORM AT DYADIC SCALES BY SUBDIVISION SCHEME 认领 引用
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作者 S.Riemenschneider S.Xu 《Analysis in Theory and Applications》 1996年第4期26-45,共20页
A new algorithm to compute continuous wavelet transforms at dyadic scales is proposed here. Our approach has a similar implementation with the standard algorithme a trous and can coincide with it in the one dimensiona... A new algorithm to compute continuous wavelet transforms at dyadic scales is proposed here. Our approach has a similar implementation with the standard algorithme a trous and can coincide with it in the one dimensional lower order spline case.Our algorithm can have arbitrary order of approximation and is applicable to the multidimensional case.We present this algorithm in a general case with emphasis on splines anti quast in terpolations.Numerical examples are included to justify our theorerical discussion. 展开更多
关键词 Th COMPUTATION OF CONTINUOUS WAVELET TRANSFORM AT DYADIC SCALES BY SUBDIVISION SCHEME CWT Morlet
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基于Transform-BiGRU和Swin-Transform-CBAM模型的双通道滚动轴承故障诊断 认领 引用
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作者 徐纪龙 陈蕊 +1 位作者 孟召杰 袁长慧 《电子设计工程》 2026年第6期109-114,共6页
针对滚动轴承故障诊断中单通道特征提取不足的问题,提出一种基于连续小波变换的双通道轴承故障诊断模型。该模型构建了堆叠重构的信号通道与连续小波变换的二维图像通道;采用Transform-BiGRU网络提取时序特征,通过Swin-Transformer提取... 针对滚动轴承故障诊断中单通道特征提取不足的问题,提出一种基于连续小波变换的双通道轴承故障诊断模型。该模型构建了堆叠重构的信号通道与连续小波变换的二维图像通道;采用Transform-BiGRU网络提取时序特征,通过Swin-Transformer提取空间特征,并引入CBAM注意力机制强化关键信息;通过对两个通道提取的特征拼接融合,进行故障诊断。基于CWRU轴承测试集的实验表明,该模型的诊断准确率达到99.83%;通过对比实验表明,相较于传统的故障诊断模型,该文模型诊断准确率提升了7.99%~21.29%,验证了该模型在滚动轴承故障诊断中的有效性。 展开更多
关键词 滚动轴承 连续小波变换 双通道 深度学习 故障诊断
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The Continuous Wavelet Transform Associated with a Dunkl Type Operator on the Real Line 认领 引用
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作者 E. A. Al Zahrani M. A. Mourou 《Advances in Pure Mathematics》 2013年第5期443-450,共8页
We consider a singular differential-difference operator Λ on R which includes as a particular case the one-dimensional Dunkl operator. By using harmonic analysis tools corresponding to Λ, we introduce and study a ne... We consider a singular differential-difference operator Λ on R which includes as a particular case the one-dimensional Dunkl operator. By using harmonic analysis tools corresponding to Λ, we introduce and study a new continuous wavelet transform on R tied to Λ. Such a wavelet transform is exploited to invert an intertwining operator between Λ and the first derivative operator d/dx. 展开更多
关键词 Differential-Difference Operator Generalized Wavelets Generalized Continuous Wavelet Transform
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