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.: evidence from wavelet analysis

Alper ASLAN, Nicholas APERGIS, Selim YILDIRIM

《能源前沿（英文）》 2014年第8卷第1期页码 1-8 doi: 10.1007/s11708-013-0290-6

摘要： This study investigates the dynamic causal relationship between energy consumption and economic growth in the U.S. at different time scales. The main novelty of the study is that this paper complements the existing studies on the nexus between energy consumption and economic growth by employing the wavelet transformation to obtain different time scales in order to investigate causality between energy consumption and economic growth. This method is first developed by Ramsey and Lampart. Their approach consists of first decomposing the series into time scales by wavelet filters and testing causality of each time scale with the pertinent time scale of the other series separately. The data span from 1973q1 to 2012q1 on a quarterly basis. The main empirical insight is that the causal relationship is stronger at finer time scales, whereas the relationship is less and less apparent at longer time horizons. The results indicate that energy consumption causes economic growth, while the reverse is not true at the original frequency of the data. At the very finest scale the same result arises. However, at coarser scales feedback is observed. In particular, at intermediate time scales the evidence indicates that energy consumption causes economic growth, while the reverse is also true. These empirical findings are expected to be of high importance in terms of the effective design and implementation of energy and environmental policies, especially when a number of countries in the pursuit of high economic growth targets do not pay any serious attention on environmental issues.

关键词： energy consumption economic growth wavelet analysis granger causality

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基于纹理及小波分析的车牌定位方法

黄卫,路小波,余彦翔,凌小静

《中国工程科学》 2004年第6卷第3期页码 19-24

摘要：

提出了一种基于纹理和小波分析的车牌定位方法。针对图像背景复杂，且车牌所占比例较小的特点，提出了一种确定基元分类阈值的二值化方法；根据车牌字符分布规律，提出了二值纹理基元分析方法，提取车牌候选区域；基于小波分析提取车牌区域竖笔画特征，采用隶属度定量表征车牌竖笔画特征、位置特征及形状特征，给出综合这些特征、从候选区域提取车牌区域的方法。测试结果表明，该方法正确定位率超过96%

关键词：纹理小波分析基元车牌定位

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Prediction of characteristic blast-induced vibration frequency during underground excavation by using wavelet

Tae Un PAK; Guk Rae JO; Un Chol HAN

《结构与土木工程前沿（英文）》 2022年第16卷第8期页码 1029-1039 doi: 10.1007/s11709-022-0861-x

摘要： Blast-induced vibration produces a very complex signal, and it is very important to work out environmental problems induced by blasting. In this study, blasting vibration signals were measured during underground excavation in carbonaceous shale by using vibration pickup CB-30 and FFT analyzer AD-3523. Then, wavelet analysis on the measured results was carried out to identify frequency bands reflecting changes of blasting vibration parameters such as vibration velocity and energy in different frequency bands. Frequency characteristics are then discussed in view of blast source distance and charge weight per delay. From analysis of results, it can be found that peak velocity and energy of blasting vibration in frequency band of 62.5–125 Hz were larger than ones in other bands, indicating the similarity to characteristics in the distribution band (31–130 Hz) of main vibration frequency. Most frequency bands were affected by blasting source distance, and the frequency band of 0–62.5 Hz reflected the change of charge weight per delay. By presenting a simplified method to predict main vibration frequency, this research may provide significant reference for future blasting engineering.

关键词： wavelet analysis blast-induced vibration frequency characteristics underground excavation

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基于分形和小波的几何型面加工误差综合分析

廖小云,唐倩,赵英,郑世泽

《中国工程科学》 2002年第4卷第5期页码 75-78

摘要：

对几何型面加工误差提出并建立了基于分形和小波的综合分析方法，可以精细分析几何型面加工误差的微细成分，并重构出型面轮廓加工误差曲线，以便进行公差与性能关系分析以及加工过程质量监控等相关工作。应用实例表明，该方法是非常有效的。

关键词：机加工加工误差分析分形几何小波分析

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A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

《环境科学与工程前沿（英文）》 2023年第17卷第2期 doi: 10.1007/s11783-023-1622-3

摘要：

● A novel deep learning framework for short-term water demand forecasting.

关键词： Short-term water demand forecasting Long-short term memory neural network Convolutional Neural Network Wavelet multi-resolution analysis Data-driven models

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Combustion instability detection using the wavelet detail of pressure fluctuations

JI Junjie, LUO Yonghao

《能源前沿（英文）》 2008年第2卷第1期页码 116-120 doi: 10.1007/s11708-008-0019-0

摘要： A combustion instability detection method that uses the wavelet detail of combustion pressure fluctuations is put forward. To confirm this method, combustion pressure fluctuations in a stoker boiler are recorded at stable and unstable combustion with a pressure transducer. Daubechies one-order wavelet is chosen to obtain the wavelet details for comparison. It shows that the wavelet approximation indicates the general pressure change in the furnace, and the wavelet detail magnitude is consistent with the intensity of turbulence and combustion noise. The magnitude of the wavelet detail is nearly constant when the combustion is stable, however, it will fluctuate much when the combustion is unstable.

关键词： comparison wavelet approximation pressure transducer general pressure consistent

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一类高维随机系统的小波分析

夏学文

《中国工程科学》 2004年第6卷第11期页码 43-46

摘要：

利用小波分析研究了线性随机系统在小波变换下的平均功率、稠度、小波展开及展开系数的相关性等。

关键词：随机系统小波分析平均功率稠度相关性

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子波分析在声辐射和声散射中的应用

文立华,任兴民

《中国工程科学》 2002年第4卷第8期页码 63-68

摘要：

文章提出将子波分析用于求解声学中的边界积分方程，能提高现有边界元方法解决工程问题的能力。在子波分析于声辐射和声散射的应用研究中，提出了把积分核函数用级数展开，建立频率响应函数计算的频率迭代技术，大大提高了频率响应函数的计算效率。讨论了子波分析在声学工程数值计算中的研究前景。

关键词：子波分析声辐射和散射结构声耦合频率响应函数

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Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet

Yun KONG, Tianyang WANG, Zheng LI, Fulei CHU

《机械工程前沿（英文）》 2017年第12卷第3期页码 406-419 doi: 10.1007/s11465-017-0419-0

摘要：

Planetary transmission plays a vital role in wind turbine drivetrains, and its fault diagnosis has been an important and challenging issue. Owing to the complicated and coupled vibration source, time-variant vibration transfer path, and heavy background noise masking effect, the vibration signal of planet gear in wind turbine gearboxes exhibits several unique characteristics: Complex frequency components, low signal-to-noise ratio, and weak fault feature. In this sense, the periodic impulsive components induced by a localized defect are hard to extract, and the fault detection of planet gear in wind turbines remains to be a challenging research work. Aiming to extract the fault feature of planet gear effectively, we propose a novel feature extraction method based on spectral kurtosis and time wavelet energy spectrum (SK-TWES) in the paper. Firstly, the spectral kurtosis (SK) and kurtogram of raw vibration signals are computed and exploited to select the optimal filtering parameter for the subsequent band-pass filtering. Then, the band-pass filtering is applied to extrude periodic transient impulses using the optimal frequency band in which the corresponding SK value is maximal. Finally, the time wavelet energy spectrum analysis is performed on the filtered signal, selecting Morlet wavelet as the mother wavelet which possesses a high similarity to the impulsive components. The experimental signals collected from the wind turbine gearbox test rig demonstrate that the proposed method is effective at the feature extraction and fault diagnosis for the planet gear with a localized defect.

关键词： wind turbine planet gear fault feature extraction spectral kurtosis time wavelet energy spectrum

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Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration

null

《机械工程前沿（英文）》 2014年第9卷第2期页码 130-141 doi: 10.1007/s11465-014-0298-6

摘要：

Fault diagnosis of rolling element bearings requires efficient signal processing techniques. For this purpose, the performances of envelope detection with fast Fourier transform (FFT) and continuous wavelet transform (CWT) of vibration signals produced from a bearing with defects on inner race and rolling element, have been examined at low signal to noise ratio. Both simulated and experimental signals from identical bearings have been considered for the purpose of analysis. The bearings have been modeled as spring-mass-dashpot systems and the simulated signals have been obtained considering transfer functions for the bearing systems subjected to impulsive loads due to the defects. Frequency B spline wavelets have been applied for CWT and a discussion on wavelet selection has been presented for better effectiveness. Results show that use of CWT with the proposed wavelets overcomes the short coming of FFT while processing a noisy vibration signals for defect detection of bearings.

关键词： Fault detection spline wavelet continuous wavelet transform fast Fourier transform

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难加工材料高速切削力非线性特征规律的最大熵谱分析与小波分析

龙震海,王西彬,王好臣

《中国工程科学》 2004年第6卷第10期页码 28-31

摘要：

在切削速度范围157～1000 m/min内，综合应用析因试验与速度单因素试验，对航空用难加工材料2Cr13马氏体不锈钢进行了高速干式铣削试验。在分析其切削力显著性影响因素的基础上，对切削力随机信号进行了现代谱分析与小波分析。研究结果表明，高速切削马氏体不锈钢材料时，切削速度和每齿进给量之间的交互作用对切削力有显著影响；铣削深度和每齿进给量之间的交互作用在切削力响应信号中表现为低频周期信号；低频周期信号与高频信号叠加后，其波形的振幅将会增大。

关键词：难加工材料高速切削析因设计 Meyer小波变换 Mallat算法

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Detection for transverse corner cracks of steel plates’ surface using wavelet

Qiong ZHOU, Qi AN

《机械工程前沿（英文）》 2009年第4卷第2期页码 224-227 doi: 10.1007/s11465-009-0017-x

摘要： An algorithm is presented for detecting transverse corner cracks at a steel plate surface using wavelet transform. According to characteristics of transverse corner crack images, the wavelet transform is used for the multi-scale analysis of detecting the image edges and disintegrating the image into four directions at the same time. The proper threshold value is chosen to segment the image into vertical components to obtain the final detection result. The experiment shows that transverse corner cracks of steel plates can be more effectively extracted by the proposed method than the other two common methods.

关键词： transverse corner cracks defect detection multi-scales wavelet analysis

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自适应小波阈值去噪在重力仪信号处理中的应用

赵立业,周百令,李坤宇

《中国工程科学》 2006年第8卷第3期页码 49-52

摘要：

为了有效地消除各种外界干扰噪声对高精度海洋重力仪测量值的影响，提高重力异常测量值的精度，在分析了小波阈值及自适应小波阈值去噪算法的基础上，将其应用到高精度海洋重力仪系统数据处理中，并与自适应卡尔曼滤波做了对比，以处理后信号的信噪比作为衡量3种数据处理方法优劣的依据。理论分析和仿真实验表明，自适应小波阈值去噪方法、传统的小波阈值去噪方法和自适应卡尔曼滤波都能在一定程度上消除噪声信号对重力仪测量信号的影响，但在相同情况下，自适应小波阈值去噪方法具有明显的优越性。

关键词：重力仪信号处理小波变换自适应阈值去噪自适应卡尔曼滤波

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Fault diagnosis of spur gearbox based on random forest and wavelet packet decomposition

Diego CABRERA,Fernando SANCHO,René-Vinicio SÁNCHEZ,Grover ZURITA,Mariela CERRADA,Chuan LI,Rafael E. VÁSQUEZ

《机械工程前沿（英文）》 2015年第10卷第3期页码 277-286 doi: 10.1007/s11465-015-0348-8

摘要：

This paper addresses the development of a random forest classifier for the multi-class fault diagnosis in spur gearboxes. The vibration signal’s condition parameters are first extracted by applying the wavelet packet decomposition with multiple mother wavelets, and the coefficients’ energy content for terminal nodes is used as the input feature for the classification problem. Then, a study through the parameters’ space to find the best values for the number of trees and the number of random features is performed. In this way, the best set of mother wavelets for the application is identified and the best features are selected through the internal ranking of the random forest classifier. The results show that the proposed method reached 98.68% in classification accuracy, and high efficiency and robustness in the models.

关键词： fault diagnosis spur gearbox wavelet packet decomposition random forest

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De-noising of diesel vibration signal using wavelet packet and singular value decomposition

DUAN Li-xiang, ZHANG Lai-bin, WANG Zhao-hui

《机械工程前沿（英文）》 2006年第1卷第4期页码 443-447 doi: 10.1007/s11465-006-0055-6

摘要： The vibration signals of diesel include excess noise that must be eliminated before extraction of characteristic parameters. Firstly, the effects of vibration-signal de-noising among Fourier transform, wavelet decomposition and wavelet packet decomposition are compared. Secondly, singular value decomposition is applied to de-noising vibration signals. Finally, a new de-noise method integrated with wavelet packet and singular value is presented. In this method, vibration signals are decomposed by wavelet packet, and the wavelet packet coefficient is de-noised by singular value decomposition again. The results indicate that the new de-noising method is the best. The SNR (signal-to-noise ratio) of the vibration signals of a diesel cylinder lid is the highest. The diesel vibration waveforms of combustion and valve become clear and the extracted characteristic parameters become more precise.

关键词： coefficient de-noised cylinder signal-to-noise wavelet decomposition