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Practical implementation of Hilbert-Huang Transform algorithm 被引量:35
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作者 黄大吉 赵进平 苏纪兰 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2003年第1期1-14,共14页
Hilbert-Huang Transform (HHT) is a newly developed powerful method for nonlinear and non-stationary time series analysis. The empirical mode decomposition is the key part of HHT, while its algorithm was protected by N... Hilbert-Huang Transform (HHT) is a newly developed powerful method for nonlinear and non-stationary time series analysis. The empirical mode decomposition is the key part of HHT, while its algorithm was protected by NASA as a US patent, which limits the wide application among the scientific community. Two approaches, mirror periodic and extrema extending methods, have been developed for handling the end effects of empirical mode decomposition. The implementation of the HHT is realized in detail to widen the application. The detailed comparison of the results from two methods with that from Huang et al. (1998, 1999), and the comparison between two methods are presented. Generally, both methods reproduce faithful results as those of Huang et al. For mirror periodic method (MPM), the data are extended once forever. Ideally, it is a way for handling the end effects of the HHT, especially for the signal that has symmetric waveform. The extrema extending method (EEM) behaves as good as MPM, and it is better than MPM for the signal that has strong asymmetric waveform. However, it has to perform extrema envelope extending in every shifting process. 展开更多
关键词 hilbert-huang transform (hht) signal processing Empirical Mode Decomposition (EMD)
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Optimization of the End Effect of Hilbert-Huang transform(HHT) 被引量:5
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作者 Chenhuan Lv Jun ZHAO +2 位作者 Chao WU Tiantai GUO Hongjiang CHEN 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2017年第3期732-745,共14页
In fault diagnosis of rotating machinery, Hil- bert-Huang transform (HHT) is often used to extract the fault characteristic signal and analyze decomposition results in time-frequency domain. However, end effect occu... In fault diagnosis of rotating machinery, Hil- bert-Huang transform (HHT) is often used to extract the fault characteristic signal and analyze decomposition results in time-frequency domain. However, end effect occurs in HHT, which leads to a series of problems such as modal aliasing and false IMF (Intrinsic Mode Func- tion). To counter such problems in HHT, a new method is put forward to process signal by combining the general- ized regression neural network (GRNN) with the bound- ary local characteristic-scale continuation (BLCC). Firstly, the improved EMD (Empirical Mode Decompo- sition) method is used to inhibit the end effect problem that appeared in conventional EMD. Secondly, the gen- erated IMF components are used in HHT. Simulation and measurement experiment for the cases of time domain, frequency domain and related parameters of Hilbert- Huang spectrum show that the method described here can restrain the end effect compared with the results obtained through mirror continuation, as the absolute percentage of the maximum mean of the beginning end point offset and the terminal point offset are reduced from 30.113% and 27.603% to 0.510% and 6.039% respectively, thus reducing the modal aliasing, and eliminating the false IMF components of HHT. The proposed method caneffectively inhibit end effect, reduce modal aliasing and false IMF components, and show the real structure of signal components accuratelX. 展开更多
关键词 End effect hilbert-huang transform hht)Modal aliasing Boundary local characteristic-scalecontinuation (BLCC) Generalized regression neuralnetwork (GRNN)
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Transmission Lines Distance Protection Using Differential Equation Algorithm and Hilbert-Huang Transform
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作者 Xingmao Liu Zhengyou He 《Journal of Power and Energy Engineering》 2014年第4期616-623,共8页
This paper proposed the scheme of transmission lines distance protection based on differential equation algorithms (DEA) and Hilbert-Huang transform (HHT). The measured impedance based on EDA is affected by various fa... This paper proposed the scheme of transmission lines distance protection based on differential equation algorithms (DEA) and Hilbert-Huang transform (HHT). The measured impedance based on EDA is affected by various factors, such as the distributed capacitance, the transient response characteristics of current transformer and voltage transformer, etc. In order to overcome this problem, the proposed scheme applies HHT to improve the apparent impedance estimated by DEA. Empirical mode decomposition (EMD) is used to decompose the data set from DEA into the intrinsic mode functions (IMF) and the residue. This residue has monotonic trend and is used to evaluate the impedance of faulty line. Simulation results show that the proposed scheme improves significantly the accuracy of the estimated impedance. 展开更多
关键词 hilbert-huang transform DIFFERENTIAL EQUATION algorithm DISTANCE PROTECTION Transmission LINES
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Efficacy of Hilbert-Huang Transform (HHT) in the Analysis of Instantaneous Low Frequency Waves of Magnetosheath
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作者 Ekong U. Nathaniel Nyakno J. George +1 位作者 Jewel I. Ibanga Aniekan M. Ekanem 《International Journal of Geosciences》 2016年第1期11-19,共9页
The flow of supersonic plasma is accompanied by a highly thermalized region called the Magnetoshealth found after the bow shock. Enclosed within this region are different wave modes associated with classes of boundari... The flow of supersonic plasma is accompanied by a highly thermalized region called the Magnetoshealth found after the bow shock. Enclosed within this region are different wave modes associated with classes of boundaries which have been determined by different methods. The efficacy of Hilbert-Huang transform (HHT) is based on the conditionality of allowing for the local analysis of frequencies, which presents the physical meaning of the original signal at that instant. The observed data have been taken from Cluster II Fluxgate Magnetometer (FGM) instrument that provides advantage for the analysis in three dimensions. The result compares favourably with instantaneous frequencies computed using simple Hilbert transform (SHT) with electric field measurements of Cluster II mission already carried out in literatures. The result of this study has shown that HHT provides the best applicability in the magnetosheath data analysis than the wavelet and Fast Fourier Transform (FFT). The application of HHT based on its advantages over other methods is viewed to be very critical in the analysis of multi-frequency signals where different frequencies could be determined distinctively at a point. 展开更多
关键词 Plasma Waves Instantaneous Frequency Empirical Mode Decomposition (EMD) hilbert-huang transform (hht)
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Efficacy of Hilbert-Huang Transform (HHT) in the Analysis of Instantaneous Low Frequency Waves of Magnetosheath
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作者 Ekong U. Nathaniel Nyakno J. George +1 位作者 Jewel I. Ibanga Aniekan M. Ekanem 《International Journal of Geosciences》 2016年第1期11-19,共9页
The flow of supersonic plasma is accompanied by a highly thermalized region called the Magnetoshealth found after the bow shock. Enclosed within this region are different wave modes associated with classes of boundari... The flow of supersonic plasma is accompanied by a highly thermalized region called the Magnetoshealth found after the bow shock. Enclosed within this region are different wave modes associated with classes of boundaries which have been determined by different methods. The efficacy of Hilbert-Huang transform (HHT) is based on the conditionality of allowing for the local analysis of frequencies, which presents the physical meaning of the original signal at that instant. The observed data have been taken from Cluster II Fluxgate Magnetometer (FGM) instrument that provides advantage for the analysis in three dimensions. The result compares favourably with instantaneous frequencies computed using simple Hilbert transform (SHT) with electric field measurements of Cluster II mission already carried out in literatures. The result of this study has shown that HHT provides the best applicability in the magnetosheath data analysis than the wavelet and Fast Fourier Transform (FFT). The application of HHT based on its advantages over other methods is viewed to be very critical in the analysis of multi-frequency signals where different frequencies could be determined distinctively at a point. 展开更多
关键词 Plasma Waves Instantaneous Frequency Empirical Mode Decomposition (EMD) hilbert-huang transform (hht)
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Analysis of the characteristics of gastrointestinal motility based on Hilbert-Huang transform method 被引量:1
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作者 黄标 Yan Guozheng 《High Technology Letters》 EI CAS 2008年第1期30-34,共5页
Pressure activity data as an important index of gastrointestinal (GI) motility can be obtained from the wireless radiotelemetry capsule. The Hilbert-Huang transform (HHT) method, which is more effective to process... Pressure activity data as an important index of gastrointestinal (GI) motility can be obtained from the wireless radiotelemetry capsule. The Hilbert-Huang transform (HHT) method, which is more effective to process non-stationary signal, is proposed to identify the characteristics of GI motility. We decompose the pressure activity data into intrinsic mode functions (IMFs), calculate the Hi/bert marginal spectrum and attain the peristalsis characteristics of GI tract. The IMFs represent the peristalses modes of GI tract activity embedded in the pressure data. The time-varying characteristic of the method suggests that the HHT is suitable to accommodate other non-stationary biomedical data analysis. 展开更多
关键词 intrinsic mode function empirical mode decomposition (EMD) hilbert-huang transform hht method gastrointestinal (GI) motility
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Pulse Wave Analysis in Patients with Coronary Heart Disease Based on Hilbert-Huang Transformation and Time-domain 被引量:4
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作者 LI Fu-feng WANG Yi-qin +3 位作者 SUN Ren XUE Song YAO Di SHEN Hai-dong 《Chinese Journal of Biomedical Engineering(English Edition)》 2013年第2期47-54,共8页
Objective: To study the characteristics of pulse tracings in CHD, and objectively evaluate the significance of pulse signal in diagnosis and appreciation of therapeutic effect in patients with coronary heart disease(C... Objective: To study the characteristics of pulse tracings in CHD, and objectively evaluate the significance of pulse signal in diagnosis and appreciation of therapeutic effect in patients with coronary heart disease(CHD), and accordingly provide with theoretic proofs for developing non-invasive technique of pulse diagnosis. Methods: By using the pulse detection system, pulse graphs in CHD patients, patients without CHD and "health" adults were collected and compared. Then characters of the pulse signal were analyzed with Hilbert-Huang transformation routine (HHT) and time-domain method respectively. Results: There existed characteristic change in pulse graph in CHD. ① h1,h3,h4,h3/h1,t,t5/t4 in time domain parameters of pulse graph increased and w1 was widened. ② 44% of C2 wave in HHT display showed chaotic and disorderly wave and irregularly wave amplitude in CHD. And 72% of C5 Wave exhibited in irregular wave with average wave amplitude over 10 gram-forces. These changes were significantly different from health adults. Conclusion: Characteristic wave of pulse graph extracted with methods of time domain or HHT routine might be considered as proofs for diagnosis and differentiation in CHD. Our researches prognosticate that pulse diagnosis can be used as an ancillary determination in occurrence of CHD for reasons of the advantage of convenient operation and non-invasion. 展开更多
关键词 coronary heart disease(CHD) pulse graph hilbert-huang transformation(hht) time-domain method
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基于HHT算法的呼吸机运行状态智能监测方法
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作者 张朝 《吉林大学学报(信息科学版)》 2025年第2期309-316,共8页
为确保呼吸机正常工作,提出基于希尔伯特变换(HHT:Hilbert-Huang Transform)算法的呼吸机运行状态智能监测方法。首先采用小波神经网络对呼吸机运行信号实施去噪处理;其次,结合HHT算法将去噪后的呼吸机运行信号进行经验模态分解(EMD:Emp... 为确保呼吸机正常工作,提出基于希尔伯特变换(HHT:Hilbert-Huang Transform)算法的呼吸机运行状态智能监测方法。首先采用小波神经网络对呼吸机运行信号实施去噪处理;其次,结合HHT算法将去噪后的呼吸机运行信号进行经验模态分解(EMD:Empirical Mode Decompostion),并将分解后的内禀模式分量(IMF:Intrinsic Mode Function)进行Hilbert谱变换,以此获取信号频谱作为信号特征。最后,将得到的信号频谱放入MLP(Multi-Layer Perceptron)神经网络分类器中,采用反向传播算法对多层感知器(MLP:Multi-Layer Perceptron)神经网络进行训练,以实现呼吸机运行状态识别。实验结果表明,所提方法的去噪效果较好,且监测到的结果和实际频谱一致。同时监测敏感度在96%以上、运行状态识别准确性在95%以上。表明所提方法可以有效监测呼吸机运行状态,监测性能较好。 展开更多
关键词 hht算法 呼吸机运行状态 小波神经网络 EMD分解 Hilbert谱变换 MLP神经网络分类器
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基于HHT和SVM的运动想象脑电识别 被引量:46
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作者 袁玲 杨帮华 马世伟 《仪器仪表学报》 EI CAS CSCD 北大核心 2010年第3期649-654,共6页
对运动想象脑电信号(EEG)分类识别是脑-机接口(BCI)研究领域的重要问题。本文通过经验模式分解(EMD)将EEG分解为一系列内蕴模式函数(IMF),并对重要IMF的瞬时幅度提取AR模型参数,同时对所有的IMF进行Hilbert变换(HT)得到Hilbert谱,进而... 对运动想象脑电信号(EEG)分类识别是脑-机接口(BCI)研究领域的重要问题。本文通过经验模式分解(EMD)将EEG分解为一系列内蕴模式函数(IMF),并对重要IMF的瞬时幅度提取AR模型参数,同时对所有的IMF进行Hilbert变换(HT)得到Hilbert谱,进而求得瞬时能量(IE)。将得到的AR参数和IE,结合时域均值和中值绝对偏差估计(MAD),组成初始特征,然后利用经遗传算法(GA)优化的支持向量机(SVM)进行分类,得到识别结果。对2008年BCI CompetitionⅣDataset 1中想象左手和脚运动的两组数据进行识别,在仅仅使用少数通道的情况下,识别正确率分别达到84.7%和85.8%,初步验证了该方法的有效性。 展开更多
关键词 hilbert-huang变换(hht) 遗传算法(GA) 支持向量机(SVM) 运动想象 分类识别
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基于HHT和CSSD的多域融合自适应脑电特征提取方法 被引量:36
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作者 李明爱 崔燕 +1 位作者 杨金福 郝冬梅 《电子学报》 EI CAS CSCD 北大核心 2013年第12期2479-2486,共8页
为改善运动想象脑电信号特征提取的自适应性和实时性,提出一种基于希尔伯特-黄变换(HHT)与共空域子空间分解算法(CSSD)的特征提取方法(HCSSD).在对脑电信号进行预处理的基础上,定义一种相对距离准则优选脑电极组合;计算脑电的Hilbert瞬... 为改善运动想象脑电信号特征提取的自适应性和实时性,提出一种基于希尔伯特-黄变换(HHT)与共空域子空间分解算法(CSSD)的特征提取方法(HCSSD).在对脑电信号进行预处理的基础上,定义一种相对距离准则优选脑电极组合;计算脑电的Hilbert瞬时能量谱和边际能量谱,以获取脑电的时-频特征,并基于CSSD提取其空域特征,采用串行特征融合策略得到脑电的时-频-空特征;设计学习矢量量化神经网络分类器,实现脑电数据分类.在训练集与测试集间隔一周且减少导联数量的情况下,基于HCSSD对左手小指和舌头的运动想象ECoG脑电数据的平均识别率为92%.实验结果表明:HCSSD在增强特征提取方法的自适应性、改善实时性的同时,提高了脑电信号识别率,为便携式BCI系统在康复领域的应用创造了条件. 展开更多
关键词 脑机接口 运动想象 希尔伯特-黄变换 共空域子空间分解 特征融合 自适应 brain-computer interface (BCI) motor imagery (MI) hilbert-huang transform (hht) common spatial sub-space decomposition (CSSD )
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微电网HHT谐波检测与时频分析方法 被引量:13
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作者 关维国 姚清志 鲁宝春 《计算机工程与应用》 CSCD 北大核心 2015年第20期198-202,212,共6页
为解决微电网谐波、突变等复杂非平稳信号的精确检测问题,提出一种基于Hilbert-Huang变换(HHT)的微电网谐波检测与时频分析方法。该方法采用保形分段三次埃尔米特插值法拟合极值点曲线,对谐波信号进行经验模态分解(EMD),得到有限个固有... 为解决微电网谐波、突变等复杂非平稳信号的精确检测问题,提出一种基于Hilbert-Huang变换(HHT)的微电网谐波检测与时频分析方法。该方法采用保形分段三次埃尔米特插值法拟合极值点曲线,对谐波信号进行经验模态分解(EMD),得到有限个固有模态分量(IMF)并进行Hilbert变换,最终计算各个IMF分量的瞬时频率和瞬时幅值,实现微电网谐波等非平稳电能信号的时频特性精确检测。仿真结果表明,该方法能够快速、准确地获取谐波信号频率成分、幅度及电压突变时刻。相对于FFT变换及传统HHT方法具有较高的精度和时域区分特性,可满足微电网谐波微机检测的工程应用需求。 展开更多
关键词 微电网 谐波检测 希尔伯特-黄变换(hht) 经验模态分解 瞬时频率 hilbert-huang transform(hht)
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基于HHT和IPSO算法优化RBF神经网络的滚刀磨损状态识别方法 被引量:5
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作者 李国龙 李彪 +2 位作者 蒋林 柯昊 付扬 《吉林大学学报(工学版)》 EI CAS CSCD 北大核心 2020年第6期1998-2009,共12页
针对滚齿加工工艺复杂滚刀磨损状态难以准确识别的难题,提出了一种结合希尔伯特黄变换(HHT)和改进粒子群算法优化的RBF神经网络(IPSO-RBF)识别滚刀磨损状态方法。首先,采集在全生命周期下滚刀加工的主轴Z向振动信号,并用小波阈值方法去... 针对滚齿加工工艺复杂滚刀磨损状态难以准确识别的难题,提出了一种结合希尔伯特黄变换(HHT)和改进粒子群算法优化的RBF神经网络(IPSO-RBF)识别滚刀磨损状态方法。首先,采集在全生命周期下滚刀加工的主轴Z向振动信号,并用小波阈值方法去除其高频噪声成分。其次,采用经验模态分解(EMD)将去噪后信号分解成若干个本征模态函数(IMF)分量,计算并筛选IMF分量的能量值及其边际谱能量值,构造滚刀磨损状态特征向量。然后,改进标准粒子群算法,再用其优化RBF神经网络。最后,将特征向量输入优化后的RBF神经网络进行训练,实现滚刀磨损状态的自动识别。实验结果表明,该方法能够有效识别滚刀的磨损状态,识别率可达98.75%。 展开更多
关键词 滚刀磨损状态 希尔伯特黄变换 小波阈值去噪 改进粒子群算法 RBF神经网络
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基于Hilbert-Huang变换的语音信号分离 被引量:3
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作者 张朝柱 张健沛 孙晓东 《计算机应用》 CSCD 北大核心 2009年第1期227-229,255,共4页
针对短时傅里叶变换不能正确得到非平稳信号的能量频率分布问题,提出了一种基于Hilbert-Huang变换的单信道语音信号分离的算法。该算法首先对分解得到的各内蕴模式函数分量(IMF)进行Hilbert变换,得到混合信号时频面上的Hilbert谱,然后... 针对短时傅里叶变换不能正确得到非平稳信号的能量频率分布问题,提出了一种基于Hilbert-Huang变换的单信道语音信号分离的算法。该算法首先对分解得到的各内蕴模式函数分量(IMF)进行Hilbert变换,得到混合信号时频面上的Hilbert谱,然后对混合信号的Hilbert谱运用独立子空间分析的方法得出代表各个独立源信号的子空间,并对其求逆变换,从而恢复出各个源信号。通过仿真实验验证了此算法的正确性和有效性,且与短时傅里叶变换时频分析法相比较,其分离性能明显得到改善,显示了Hilbert-Huang变换在处理非平稳信号的优越性。 展开更多
关键词 Hilbert—Huang变换 内在模式分解 独立子空间分析 C-均值算法
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基于改进HHT算法的谐波信号分析方法 被引量:5
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作者 徐健 张禹 吴飞飞 《电子测量技术》 2018年第8期30-34,共5页
电能被广泛运用在动力、冶金、照明、通信等各个领域,电力系统中存在大量的非稳态信号,而希尔伯特-黄变换(HHT)算法非常适合对非稳态信号进行时频分析。介绍了HHT的基本原理,并针对其存在的端点效应、模态混叠等问题提出了一种改进HH... 电能被广泛运用在动力、冶金、照明、通信等各个领域,电力系统中存在大量的非稳态信号,而希尔伯特-黄变换(HHT)算法非常适合对非稳态信号进行时频分析。介绍了HHT的基本原理,并针对其存在的端点效应、模态混叠等问题提出了一种改进HHT算法,其基本原理是采用集合经验模态分解(EEMD)将非线性、非平稳的原始信号分解成若干固有模态分量(IMF),再对每个IMF分别进行Hilbert变换获得相应的瞬时特征量,从而建立短时谐波模型。EEMD在信号分解的过程中通过增加白噪声以达到减少频谱混叠的目的,测试值增多必然会使误差减小,精度提高,在一定程度上弥补了经验模态分解(EMD)的不足,并通过实验仿真验证了EEMD分解的可行性和高效性。 展开更多
关键词 hht算法 Hilber1t变换 集合经验模态分解(EEMD) 谐波模型
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基于HHT变换和FOA_LSSVM的电缆故障诊断 被引量:5
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作者 苏立 《计算机与现代化》 2017年第9期96-101,105,共7页
针对现有的地下电缆故障诊断方法存在准确率不高、误差较大的缺点,提出一种基于HHT变换和FOA_LSSVM的地下电缆故障诊断方法。针对地下电缆故障信号,通过HHT变换提取地下电缆故障信号的特征分量,将提取的特征分量和地下电缆故障类型作为F... 针对现有的地下电缆故障诊断方法存在准确率不高、误差较大的缺点,提出一种基于HHT变换和FOA_LSSVM的地下电缆故障诊断方法。针对地下电缆故障信号,通过HHT变换提取地下电缆故障信号的特征分量,将提取的特征分量和地下电缆故障类型作为FOA_LSSVM的输入和输出,实现地下电缆故障类型的识别。以150组地下电缆故障数据为实验对象,结果表明,FOA_LSSVM比GA_LSSVM,PSO_LSSVM和DE_LSSVM具有更高的准确率,更适合地下电缆故障的诊断和识别。 展开更多
关键词 果蝇优化算法 最小二乘支持向量机 电缆故障 hht变换
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HHT方法在轴承故障诊断中的应用 被引量:4
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作者 耶晓东 《陕西理工学院学报(自然科学版)》 2012年第4期9-13,共5页
为研究滚动轴承故障问题,将HHT(Hilbert-Huang transform)分析方法应用于轴承信号故障的提取。用HHT对复合信号进行了仿真分析,表明此方法分析信号的有效性。将HHT方法应用于轴承内外圈的故障诊断,结果表明,所求出的轴承故障的信息特征... 为研究滚动轴承故障问题,将HHT(Hilbert-Huang transform)分析方法应用于轴承信号故障的提取。用HHT对复合信号进行了仿真分析,表明此方法分析信号的有效性。将HHT方法应用于轴承内外圈的故障诊断,结果表明,所求出的轴承故障的信息特征与理论计算吻合,表明了HHT方法能够有效的提取轴承故障的特征信息,提高轴承故障诊断率。这为类似机械零部件的故障诊断提供了参考。 展开更多
关键词 hht(hilbert-huang transform) 故障诊断 轴承
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基于HHT和PSO-C-均值算法的ECoG分类
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作者 吕俊 李胜勇 《武汉理工大学学报》 EI CAS CSCD 北大核心 2008年第1期102-105,共4页
皮层脑电图信号(electrocorticogram,ECoG)非平稳,如何提取有效的特征,设计恰当的分类器是ECoG脑-机接口研究的关键问题。该文提出了基于希尔伯特-黄变换的ECoG窄带特征提取和压缩方法,并且封装了粒子群优化和C-均值算法以调整特征权重... 皮层脑电图信号(electrocorticogram,ECoG)非平稳,如何提取有效的特征,设计恰当的分类器是ECoG脑-机接口研究的关键问题。该文提出了基于希尔伯特-黄变换的ECoG窄带特征提取和压缩方法,并且封装了粒子群优化和C-均值算法以调整特征权重,改善分类效果。采用BCI Competition III数据集I进行实验,结果表明:只需6个电极即可获得93%的分类精度。 展开更多
关键词 ECoG脑-机接口 希尔伯特-黄变换 粒子群优化 C-均值算法
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一种免疫算法与SVR的Hilbert-Huang边界优化 被引量:1
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作者 姚莉 李磊民 黄玉清 《数据采集与处理》 CSCD 北大核心 2012年第2期196-201,共6页
Hilbert-Huang变换(Hilbert-Huang transform,HHT)在对信号进行经验模态分解(Empirical modedecomposition,EMD)和对各内禀模态函数(Intrinsic mode function,IMF)进行Hilbert变换时都会出现边界问题。为了克服该问题,本文提出了基于离... Hilbert-Huang变换(Hilbert-Huang transform,HHT)在对信号进行经验模态分解(Empirical modedecomposition,EMD)和对各内禀模态函数(Intrinsic mode function,IMF)进行Hilbert变换时都会出现边界问题。为了克服该问题,本文提出了基于离散均匀免疫算法(Discrete uniform immune algorithm,DUIA)和支持向量回归(Support vector regression,SVR)的HHT边界优化方法。该方法采用DUIA优化SVR的参数,并利用SVR对数据延拓,以有效分析HHT边界问题。通过对正弦叠加信号和实际信号的仿真分析表明:所提出的算法可有效解决HHT中存在的边界问题,且其效果优于SVR的数据延拓方法。 展开更多
关键词 希尔伯特-黄变换 遗传算法 支持向量回归机
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基于HHT与滤波算法的风电波动平抑策略研究 被引量:12
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作者 徐玉韬 谈竹奎 +1 位作者 肖永 吕黔苏 《电气传动》 北大核心 2019年第2期56-60,共5页
由于一阶低通滤波算法在实际工程中具有较好的实用性,因此用其进行风电功率波动的平抑。首先,应用希尔伯特黄变换(HHT)获取风电的主频率,以此求取初始滤波时间常数。然后,滤波时间常数最小作为目标,以风电并网波动率等为约束,动态调整... 由于一阶低通滤波算法在实际工程中具有较好的实用性,因此用其进行风电功率波动的平抑。首先,应用希尔伯特黄变换(HHT)获取风电的主频率,以此求取初始滤波时间常数。然后,滤波时间常数最小作为目标,以风电并网波动率等为约束,动态调整滤波时间步长,从而实现对风电波动的平抑。再者,以混合储能经济性最优为目标,同时兼顾充放电功率和SOC等约束,实现储能总载荷在蓄电池和超级电容器之间的分配。最后,通过算例验证了控制策略的有效性。 展开更多
关键词 风电波动平抑 一阶低通滤波算法 希尔伯特黄变换 滤波时间常数 储能经济性
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基于HHT的煤矿电网扰动起止时刻检测方法 被引量:1
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作者 万本强 吴中伟 石莹 《工矿自动化》 北大核心 2012年第6期62-67,共6页
针对煤矿电网电能质量扰动复杂、采用小波分析技术解决扰动暂态过程存在小波基选择的问题,提出了一种基于HHT的扰动起止时刻检测方法。该方法以电压缺口为例,在30dB和40dB噪声环境下,首先采用EMD算法对电压缺口信号进行分解,得到IMF1分... 针对煤矿电网电能质量扰动复杂、采用小波分析技术解决扰动暂态过程存在小波基选择的问题,提出了一种基于HHT的扰动起止时刻检测方法。该方法以电压缺口为例,在30dB和40dB噪声环境下,首先采用EMD算法对电压缺口信号进行分解,得到IMF1分量、IMF2分量、IMF3分量和剩余分量R;然后对含有高频部分的信号即原始信号、IMF1分量、IMF2分量进行Hilbert变换,得出通过瞬时幅值曲线中突变点位置可以检测扰动起止时刻的结论;通过对比原始信号、IMF1分量、IMF2分量的扰动起止时刻检测值,最后选用了误差最小的IMF1分量的瞬时幅值进行扰动起止时刻检测。实验结果表明,该方法精度高、抗噪声能力强。 展开更多
关键词 煤矿电网 电能质量 扰动起止时刻检测 hht HILBERT变换 EMD算法 IMF分量
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