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Performance of Continuous Wavelet Transform over Fourier Transform in Features Resolutions
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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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DETECTION OF INCIPIENT LOCALIZED GEAR FAULTS IN GEARBOX BY COMPLEX CONTINUOUS WAVELET TRANSFORM 被引量:6
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作者 HanZhennan XiongShibo LiJinbao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 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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EEG epileptic seizure detection and classification based on dual-tree complex wavelet transform and machine learning algorithms 被引量:4
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作者 Itaf Ben Slimen Larbi Boubchir +1 位作者 Zouhair Mbarki Hassene Seddik 《The Journal of Biomedical Research》 CAS CSCD 2020年第3期151-161,共11页
The visual analysis of common neurological disorders such as epileptic seizures in electroencephalography(EEG) is an oversensitive operation and prone to errors,which has motivated the researchers to develop effective... The visual analysis of common neurological disorders such as epileptic seizures in electroencephalography(EEG) is an oversensitive operation and prone to errors,which has motivated the researchers to develop effective automated seizure detection methods.This paper proposes a robust automatic seizure detection method that can establish a veritable diagnosis of these diseases.The proposed method consists of three steps:(i) remove artifact from EEG data using Savitzky-Golay filter and multi-scale principal component analysis(MSPCA),(ii) extract features from EEG signals using signal decomposition representations based on empirical mode decomposition(EMD),discrete wavelet transform(DWT),and dual-tree complex wavelet transform(DTCWT) allowing to overcome the non-linearity and non-stationary of EEG signals,and(iii) allocate the feature vector to the relevant class(i.e.,seizure class "ictal" or free seizure class "interictal") using machine learning techniques such as support vector machine(SVM),k-nearest neighbor(k-NN),and linear discriminant analysis(LDA).The experimental results were based on two EEG datasets generated from the CHB-MIT database with and without overlapping process.The results obtained have shown the effectiveness of the proposed method that allows achieving a higher classification accuracy rate up to 100% and also outperforms similar state-of-the-art methods. 展开更多
关键词 ELECTROENCEPHALOGRAPHY epileptic seizure detection feature extraction dual-tree complex wavelet transform machine learning
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Quantization-Based Robust Image Watermarking Using the Dual Tree Complex Wavelet Transform 被引量:4
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作者 LIU Jinhua SHE Kun 《China Communications》 SCIE CSCD 2010年第4期1-6,共6页
Conventional quantization index modulation (QIM) watermarking uses the fixed quantization step size for the host signal.This scheme is not robust against geometric distortions and may lead to poor fidelity in some are... Conventional quantization index modulation (QIM) watermarking uses the fixed quantization step size for the host signal.This scheme is not robust against geometric distortions and may lead to poor fidelity in some areas of content.Thus,we proposed a quantization-based image watermarking in the dual tree complex wavelet domain.We took advantages of the dual tree complex wavelets (perfect reconstruction,approximate shift invariance,and directional selectivity).For the case of watermark detecting,the probability of false alarm and probability of false negative were exploited and verified by simulation.Experimental results demonstrate that the proposed method is robust against JPEG compression,additive white Gaussian noise (AWGN),and some kinds of geometric attacks such as scaling,rotation,etc. 展开更多
关键词 Image Watermarking Quantization IndexModulation Dual Tree complex wavelet transform JPEG Compression
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A Dual Tree Complex Discrete Cosine Harmonic Wavelet Transform (ADCHWT) and Its Application to Signal/Image Denoising 被引量:3
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作者 M. Shivamurti S. V. Narasimhan 《Journal of Signal and Information Processing》 2011年第3期218-226,共9页
A new simple and efficient dual tree analytic wavelet transform based on Discrete Cosine Harmonic Wavelet Transform DCHWT (ADCHWT) has been proposed and is applied for signal and image denoising. The analytic DCHWT ha... A new simple and efficient dual tree analytic wavelet transform based on Discrete Cosine Harmonic Wavelet Transform DCHWT (ADCHWT) has been proposed and is applied for signal and image denoising. The analytic DCHWT has been realized by applying DCHWT to the original signal and its Hilbert transform. The shift invariance and the envelope extraction properties of the ADCHWT have been found to be very effective in denoising speech and image signals, compared to that of DCHWT. 展开更多
关键词 ANALYTIC DISCRETE COSINE Harmonic wavelet transform ANALYTIC wavelet transform Dual TREE complex wavelet transform DCT Shift Invariant wavelet transform wavelet transform Denoising
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Parseval Theory of Complex Wavelet Transform for Wavelet Family Including Rotational Parameters 被引量:1
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作者 ZHOU Nan-Run JIA Fang 《Communications in Theoretical Physics》 SCIE CAS CSCD 2008年第9期598-602,共5页
A rotational parameter Rθ has been introduced to complex wavelet transform (CWT). The rotational CWT (RCWT) corresponds to a matrix element 〈φ|U2(θ;μ;κ)[F〉 in the context of quantum mechanics, where U2(... A rotational parameter Rθ has been introduced to complex wavelet transform (CWT). The rotational CWT (RCWT) corresponds to a matrix element 〈φ|U2(θ;μ;κ)[F〉 in the context of quantum mechanics, where U2(θ;μ;κ) is a two-mode rotational displacing-squeezing operator in the 〈η| representation. Based on this, the Parseval theorem and the inversion formula of RCWT have been proved. The concise proof not only manifestly shows the merit of Dirac's representation theory but also leads to a new orthogonal property of complex mother wavelets in parameter space. 展开更多
关键词 complex wavelet transform representation theory quantum mechanics
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Application of Bipartite Entangled States to Quantum Mechanical Version of Complex Wavelet Transforms 被引量:1
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作者 FAN Hong-Yi LU Hai-Liang XU Xue-Fen 《Communications in Theoretical Physics》 SCIE CAS CSCD 2006年第4期609-613,共5页
We introduce the bipartite entangled states to present a quantum mechanical version of complex wavelet transform. Using the technique of integral within an ordered product of operators we show that the complex wavelet... We introduce the bipartite entangled states to present a quantum mechanical version of complex wavelet transform. Using the technique of integral within an ordered product of operators we show that the complex wavelet transform can be studied in terms of various quantum state vectors in two-mode Fock space. In this way the creterion for mother wavelet can be examined quantum-mechanically and therefore more deeply. 展开更多
关键词 entangled states complex wavelet transform
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一种基于优化VMD-CWT-CNN的柱塞泵配流盘磨损状态识别方法
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作者 吕尚杰 谷立臣 耿宝龙 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2024年第1期43-53,共11页
为解决一维振动信号难以充分挖掘表达状态特征信息以及柱塞泵配流盘磨损早期识别问题,基于卷积神经网络(Convolutional neural networks,CNN)优秀的图像处理能力,提出了一个优化VMD-CWT-CNN模型。首先,采用连续小波变换(Continuous wave... 为解决一维振动信号难以充分挖掘表达状态特征信息以及柱塞泵配流盘磨损早期识别问题,基于卷积神经网络(Convolutional neural networks,CNN)优秀的图像处理能力,提出了一个优化VMD-CWT-CNN模型。首先,采用连续小波变换(Continuous wavelet transform,CWT)对信号进行预处理,得到信号的二维时频图,作为CNN模型的一路输入,将状态识别问题转化为CNN图像识别问题。其次,基于相关系数对变分模态分解(Variational mode decomposition,VMD)参数优化后,利用优化VMD对振动信号进行预处理,再以相关系数和峭度值最大为优选原则,甄选出三组蕴含故障特征的本征模态函数(Intrinsic mode function,IMF),将其重组为三通道一维信号,作为CNN模型的另一路输入。最后,在CNN模型中将两路信息汇聚并得到柱塞泵配流盘磨损状态识别分类结果。实验中,此方法分别采用优化VMD和CWT对振动信号预处理,再结合CNN对磨损状态进行分类。实验结果表明,该方法对于配流盘磨损的三种状态的识别效果显著优于单路输入的CNN模型以及典型的深度学习方法和机器学习分类器。因此,优化的VMD-CWT-CNN方法可以更准确地实现柱塞泵配流盘磨损状态识别。 展开更多
关键词 柱塞泵配流盘磨损 振动信号 卷积神经网络 变分模态分解 连续小波变换
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Monitoring of Wind Turbine Blades Based on Dual-Tree Complex Wavelet Transform 被引量:1
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作者 LIU Rongmei ZHOU Keyin YAO Entao 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2021年第1期140-152,共13页
Structural health monitoring(SHM)in-service is very important for wind turbine system.Because the central wavelength of a fiber Bragg grating(FBG)sensor changes linearly with strain or temperature,FBG-based sensors ar... Structural health monitoring(SHM)in-service is very important for wind turbine system.Because the central wavelength of a fiber Bragg grating(FBG)sensor changes linearly with strain or temperature,FBG-based sensors are easily applied to structural tests.Therefore,the monitoring of wind turbine blades by FBG sensors is proposed.The method is experimentally proved to be feasible.Five FBG sensors were set along the blade length in order to measure distributed strain.However,environmental or measurement noise may cover the structural signals.Dual-tree complex wavelet transform(DT-CWT)is suggested to wipe off the noise.The experimental studies indicate that the tested strain fluctuate distinctly as one of the blades is broken.The rotation period is about 1 s at the given working condition.However,the period is about 0.3 s if all the wind blades are in good conditions.Therefore,strain monitoring by FBG sensors could predict damage of a wind turbine blade system.Moreover,the studies indicate that monitoring of one blade is adequate to diagnose the status of a wind generator. 展开更多
关键词 wind turbine blade structural health monitoring(SHM) fiber Bragg grating(FBG) dual-tree complex wavelet transform(DT-cwt)
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基于DT-CWT和SVD的变电站直流系统接地故障检测技术研究
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作者 李能俊 杨海成 +2 位作者 许显科 李书山 高玉玲 《电气传动》 2024年第5期80-85,共6页
变电站直流系统的状态直接关系到变电站的正常运行,为了对变电站直流系统出现的接地故障快速、准确定位,提出了一种双树复小波变换(DT-CWT)和奇异值分解(SVD)相结合的变电站直流系统接地故障检测新方法。该方法首先利用DT-CWT对支路电... 变电站直流系统的状态直接关系到变电站的正常运行,为了对变电站直流系统出现的接地故障快速、准确定位,提出了一种双树复小波变换(DT-CWT)和奇异值分解(SVD)相结合的变电站直流系统接地故障检测新方法。该方法首先利用DT-CWT对支路电流信号进行分解来构建Hankel矩阵;然后对Hankel矩阵进行SVD分解,得到一系列奇异特征值;再次,利用相邻奇异值差值构建奇异值差分谱,通过奇异值差分谱最大峰值来保留有效的奇异值个数;最后,利用保留的奇异值来重构低频信号。算例分析结果表明,该方法能够准确地从支路电流信号中提取出低频交流信号,可以对变电站直流系统接地故障进行准确定位,很大程度上减小对地电容对检测精度的影响。 展开更多
关键词 直流系统 接地故障检测 双树复小波变换 奇异值分解
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Image inpainting using complex 2-D dual-tree wavelet transform
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作者 YANG Jian-bin 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2011年第1期70-76,共7页
The dual-tree complex wavelet transform is a useful tool in signal and image process- ing. In this paper, we propose a dual-tree complex wavelet transform (CWT) based algorithm for image inpalnting problem. Our appr... The dual-tree complex wavelet transform is a useful tool in signal and image process- ing. In this paper, we propose a dual-tree complex wavelet transform (CWT) based algorithm for image inpalnting problem. Our approach is based on Cai, Chan, Shen and Shen's framelet-based algorithm. The complex wavelet transform outperforms the standard real wavelet transform in the sense of shift-invariance, directionality and anti-aliasing. Numerical results illustrate the good performance of our algorithm. 展开更多
关键词 Image inpainting dual-tree complex wavelet transform wavelet shrinkage method.
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Inversion formula and Parseval theorem for complex continuous wavelet transforms studied by entangled state representation
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作者 胡利云 范洪义 《Chinese Physics B》 SCIE EI CAS CSCD 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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Seismic signal analysis based on the dual-tree complex wavelet packet transform
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作者 XIE Zhou-min(谢周敏) WANG En-fu(王恩福) +2 位作者 ZHANG Guo-hong(张国宏) ZHAO Guo-cun(赵国存) CHEN Xu-geng(陈旭庚) 《Acta Seismologica Sinica(English Edition)》 CSCD 2004年第z1期117-122,共6页
We tried to apply the dual-tree complex wavelet packet transform in seismic signal analysis. The complex wavelet packet transform (CWPT) combine the merits of real wavelet packet transform with that of complex contin... We tried to apply the dual-tree complex wavelet packet transform in seismic signal analysis. The complex wavelet packet transform (CWPT) combine the merits of real wavelet packet transform with that of complex continuous wavelet transform (CCWT). It can not only pick up the phase information of signal, but also produce better ″focal- izing″ function if it matches the phase spectrum of signals analyzed. We here described the dual-tree CWPT algo- rithm, and gave the examples of simulation and actual seismic signals analysis. As shown by our results, the dual-tree CWPT is a very effective method in analyzing seismic signals with non-linear phase. 展开更多
关键词 dual-tree complex wavelet packet transform instantaneous characteristics seismicsignalanalysis
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Defects Recognition of 3D Braided Composite Based on Dual-Tree Complex Wavelet Packet Transform
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作者 贺晓丽 王瑞 《Journal of Donghua University(English Edition)》 EI CAS 2015年第5期749-752,共4页
Textile-reinforced composites,due to their excellent highstrength-to-low-mass ratio, provide promising alternatives to conventional structural materials in many high-tech sectors. 3D braided composites are a kind of a... Textile-reinforced composites,due to their excellent highstrength-to-low-mass ratio, provide promising alternatives to conventional structural materials in many high-tech sectors. 3D braided composites are a kind of advanced composites reinforced with 3D braided fabrics; the complex nature of 3D braided composites makes the evaluation of the quality of the product very difficult. In this investigation,a defect recognition platform for 3D braided composites evaluation was constructed based on dual-tree complex wavelet packet transform( DT-CWPT) and backpropagation( BP) neural networks. The defects in 3D braided composite materials were probed and detected by an ultrasonic sensing system. DT-CWPT method was used to analyze the ultrasonic scanning pulse signals,and the feature vectors of these signals were extracted into the BP neural networks as samples. The type of defects was identified and recognized with the characteristic ultrasonic wave spectra. The position of defects for the test samples can be determined at the same time. This method would have great potential to evaluate the quality of 3D braided composites. 展开更多
关键词 3D braided composite dual-tree complex wavelet packet transform(DT-CWPT) ultrasonic wave
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基于DTCWT-VAE的弹道中段目标RCS识别
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作者 王彩云 张慧雯 +2 位作者 王佳宁 吴钇达 常韵 《系统工程与电子技术》 EI CSCD 北大核心 2024年第7期2269-2275,共7页
针对弹道目标雷达信号易受环境影响、目标识别准确率低的问题,提出了一种基于双树复小波变换(dual-tree complex wavelet transform,DTCWT)和变分自编码器(variational autoencoder,VAE)的弹道目标雷达散射截面(radar cross section,RCS... 针对弹道目标雷达信号易受环境影响、目标识别准确率低的问题,提出了一种基于双树复小波变换(dual-tree complex wavelet transform,DTCWT)和变分自编码器(variational autoencoder,VAE)的弹道目标雷达散射截面(radar cross section,RCS)识别法。首先,采用DTCWT对弹道目标RCS动态数据进行预处理,再利用VAE提取目标的隐变量特征,最后用支持向量机(support vector machine,SVM)分类器进行识别。实验结果表明,与已有方法相比,该方法具有更高的识别概率,且鲁棒性较好。 展开更多
关键词 弹道目标 目标识别 雷达散射截面 双树复小波变换 变分自编码器
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A Complex Wavelet Transform Approach for 1 Dimensional Signal
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作者 Mukund Gokhale Daljeet Kaur Khanduja 《通讯和计算机(中英文版)》 2010年第8期62-72,共11页
关键词 复小波变换 信号途径 一维 离散小波变换 小波滤波器 平移不变性 复杂系数 标准制定
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基于DTCWT的运动想象脑电特征提取 被引量:2
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作者 汤伟 耿逸飞 《计算机应用与软件》 北大核心 2023年第4期80-84,106,共6页
针对脑电信号采用单一特征识别存在自适应性差和识别率低等问题,提出一种基于双树复小波(DTCWT)的多特征融合的左右手运动想象脑电特征提取方法。对原始脑电信号进行DTCWT变换提取最佳时频段;对所提取的信号频段进行希尔伯特变换与Lempe... 针对脑电信号采用单一特征识别存在自适应性差和识别率低等问题,提出一种基于双树复小波(DTCWT)的多特征融合的左右手运动想象脑电特征提取方法。对原始脑电信号进行DTCWT变换提取最佳时频段;对所提取的信号频段进行希尔伯特变换与Lempel-Ziv复杂度计算,将得到的时-频域特征与非线性特征组合为特征向量;采用线性判别分析(LDA)完成运动想象任务的分类。实验采用BCI CompetitionⅢ竞赛数据对该方法进行验证,仿真结果表明其识别准确率明显提高,最高可达89.84%。 展开更多
关键词 脑电信号 运动想象 双树复小波变换 Lempel-Ziv复杂度
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Investigation on the automatic parameters extraction of pulse signals based on wavelet transform 被引量:8
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作者 WANG Hui-yan ZHANG Pei-yong 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2007年第8期1283-1289,共7页
This paper analyses a key problem in the quantification of pulse diagnosis. Due to the subjectivity and fuzziness of pulse diagnosis,quantitative methods are needed. To extract the parameters of pulse signals,the prer... This paper analyses a key problem in the quantification of pulse diagnosis. Due to the subjectivity and fuzziness of pulse diagnosis,quantitative methods are needed. To extract the parameters of pulse signals,the prerequisite is to detect the corners of pulse signals correctly. Up to now,the pulse parameters are mostly acquired by marking the pulse corners manually,which is an obstacle to modernize pulse diagnosis. Therefore,a new automatic parameters extraction approach for pulse signals using wavelet transform is presented. The results testified that the method we proposed is feasible and effective and can detect corners of pulse signals accurately,which can be expected to facilitate the modernization of pulse diagnosis. 展开更多
关键词 Pulse signal Feature extraction complex wavelet transform Quantitative diagnosis
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NEW METHOD OF EXTRACTING WEAK FAILURE INFORMATION IN GEARBOX BY COMPLEX WAVELET DENOISING 被引量:19
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作者 CHEN Zhixin XU Jinwu YANG Debin 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2008年第4期87-91,共5页
Because the extract of the weak failure information is always the difficulty and focus of fault detection. Aiming for specific statistical properties of complex wavelet coefficients of gearbox vibration signals, a new... Because the extract of the weak failure information is always the difficulty and focus of fault detection. Aiming for specific statistical properties of complex wavelet coefficients of gearbox vibration signals, a new signal-denoising method which uses local adaptive algorithm based on dual-tree complex wavelet transform (DT-CWT) is introduced to extract weak failure information in gear, especially to extract impulse components. By taking into account the non-Gaussian probability distribution and the statistical dependencies among wavelet coefficients of some signals, and by taking the advantage of near shift-invariance of DT-CWT, the higher signal-to-noise ratio (SNR) than common wavelet denoising methods can be obtained. Experiments of extracting periodic impulses in gearbox vibration signals indicate that the method can extract incipient fault feature and hidden information from heavy noise, and it has an excellent effect on identifying weak feature signals in gearbox vibration signals. 展开更多
关键词 Dual-tree complex wavelet transform Signal-denoising Gear fault diagnosis Early fault detection
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