Fast wavelet multi-resolution analysis (wavelet MRA) provides a effective tool for analyzing and canceling disturbing components in original signal. Because of its exponential frequency axis, this method isn't s...Fast wavelet multi-resolution analysis (wavelet MRA) provides a effective tool for analyzing and canceling disturbing components in original signal. Because of its exponential frequency axis, this method isn't suitable for extracting harmonic components. The modified exponential time-frequency distribution ( MED) overcomes the problems of Wigner distribution( WD) ,can suppress cross-terms and cancel noise further more. MED provides high resolution in both time and frequency domains, so it can make out weak period impulse components fmm signal with mighty harmonic components. According to the 'time' behavior, together with 'frequency' behavior in one figure,the essential structure of a signal is revealed clearly. According to the analysis of algorithm and fault diagnosis example, the joint of wavelet MRA and MED is a powerful tool for fault diagnosis.展开更多
Wavelet-fractal based SAR （synthetic aperture radar） image processing is one of the advanced technologies in image processing. The main concept of analysis is that after wavelet transformation, multifractal spectrum...Wavelet-fractal based SAR （synthetic aperture radar） image processing is one of the advanced technologies in image processing. The main concept of analysis is that after wavelet transformation, multifractal spectrum of the signal is different from that of noise. This difference is used to alleviate the noise produced by SAR image.The method to denoise SAR image using the process based on wavelet-fractai analysis is discussed in detail. Essentially, the present method focuses on adjusting the Hoelder exponent α of multifractal spectrum. After simulation, α should be adjusted to 1.72-1.73. The more the value of α exceeds 1.73, the less distinctive the edges of SAR image become. According to the authors denoising is optimal at α=1.72-1.73. In other words, when α =1.72-1.73, a smooth and denoised SAR image is produced.展开更多
Based upon empirical mode decomposition (EMD) method and Hilbert spectrum, a method for fault diagnosis of roller bearing is proposed. The orthogonal wavelet bases are used to translate vibration signals of a roller b...Based upon empirical mode decomposition (EMD) method and Hilbert spectrum, a method for fault diagnosis of roller bearing is proposed. The orthogonal wavelet bases are used to translate vibration signals of a roller bearing into time-scale representation, then, an envelope signal can be obtained by envelope spectrum analysis of wavelet coefficients of high scales. By applying EMD method and Hilbert transform to the envelope signal, we can get the local Hilbert marginal spectrum from which the faults in a roller bearing can be diagnosed and fault patterns can be identified. Practical vibration signals measured from roller bearings with out-race faults or inner-race faults are analyzed by the proposed method. The results show that the proposed method is superior to the traditional envelope spectrum method in extracting the fault characteristics of roller bearings.展开更多
The nonlinear wave forces on vertical cylinders induced by freak wave trains were experimentally investigated. A series of freak wave trains with different wave steepness were modeled in a wave flume. The correspondin...The nonlinear wave forces on vertical cylinders induced by freak wave trains were experimentally investigated. A series of freak wave trains with different wave steepness were modeled in a wave flume. The corresponding wave forces on vertical cylinders of different diameters were measured. The experimental wave forces were also compared with the predicted results based on Morison formula. Particular attentions were paid to the effects of wave steepness on the dimensionless peak forces, asymmetry characteristics of the impact forces and high-frequency force components. Wavelet-based analysis methods were employed in revealing the local energy structures and quadratic phase coupling in the freak wave forces.展开更多
Based on the brief introduction of the principles of wavelet analysis, this paper gives a summary of several typical wavelet bases from the point of view of perfect reconstruction of signals and emphasizes that design...Based on the brief introduction of the principles of wavelet analysis, this paper gives a summary of several typical wavelet bases from the point of view of perfect reconstruction of signals and emphasizes that designing wavelet bases which are used to decompose the signal into a two-band form is equivalent to designing a two-band filter bank with perfect or nearly perfect property. The generating algorithm corresponding to Daubechies bases and some simulated results are also given in the paper.展开更多
This paper investigated approaches to supporting effective and efficient retrieval of image based on principle component analysis. First, it extracted the image content, texture and color. Gabor wavelet transforms wer...This paper investigated approaches to supporting effective and efficient retrieval of image based on principle component analysis. First, it extracted the image content, texture and color. Gabor wavelet transforms were used to extract texture feature of the image and the average color was used to extract the color features. The principle component of the feature vector of image can be constructed. Content based image retrieval was performed by comparing the feature vector of the query image with the projection feature vector of the image database on the principle component space of the query image. By this technique, it can reduce the dimensionality of feature vector, which in turn reduce the searching time.展开更多
The problem of seismic danger estimate in Japan after Tohoku mega-earthquake 11 March of 2011 is considered. The estimates are based on processing low-frequency seismic noise wave-forms from broadband network F-net. A...The problem of seismic danger estimate in Japan after Tohoku mega-earthquake 11 March of 2011 is considered. The estimates are based on processing low-frequency seismic noise wave-forms from broadband network F-net. A new method of dynamic estimate of seismic danger is used for this problem. The method is based on calculating multi-fractal properties and minimum entropy of squared orthogonal wavelet coefficients for seismic noise. The analysis of the data using notion of “spots of seismic danger” shows that the seismic danger in Japan remains at high level after 2011. 03. 11 within north-east part of Philippine plate—at the region of Nankai Though which traditionally is regarded as the place of strongest earthquakes. It is well known that estimate of time moment of future shock is the most difficult problem in earthquake prediction. In this paper we try to find some peculiarities of the seismic noise data which could extract future danger time interval by analogy with the behavior before Tohoku earthquake. Two possible precursors of this type were found. They are the results of estimates within 1-year moving time window: based on correlation between 2 mean multi-fractal parameters of the noise and based on cluster analysis of annual clouds of 4 mean noise parameters. Both peculiarities of the noise data extract time interval 2013-2014 as the danger.展开更多
The sense of being within a three-dimensional （3D） space and interacting with virtual 3D objects in a computer-generated virtual environment （VE） often requires essential image, vision and sensor signal processing...The sense of being within a three-dimensional （3D） space and interacting with virtual 3D objects in a computer-generated virtual environment （VE） often requires essential image, vision and sensor signal processing techniques such as differentiating and denoising. This paper describes novel implementations of the Gaussian filtering for characteristic signal extraction and waveletbased image denoising algorithms that run on the graphics processing unit （GPU）. While significant acceleration over standard CPU implementations is obtained through exploiting data parallelism provided by the modern programmable graphics hardware, the CPU can be freed up to run other computations more efficiently such as artificial intelligence （AI） and physics. The proposed GPU-based Gaussian filtering can extract surface information from a real object and provide its material features for rendering and illumination. The wavelet-based signal denoising for large size digital images realized in this project provided better realism for VE visualization without sacrificing real-time and interactive performances of an application.展开更多
基于时间序列方法能够对短时间的电离层总电子含量(Total Electron Content,TEC)进行较好预测,但由于电离层TEC受各种因素影响,直接使用原始TEC序列数据会受到各种噪声的干扰,影响其预测精度。本文利用小波方法的良好去噪效果,提出一种...基于时间序列方法能够对短时间的电离层总电子含量(Total Electron Content,TEC)进行较好预测,但由于电离层TEC受各种因素影响,直接使用原始TEC序列数据会受到各种噪声的干扰,影响其预测精度。本文利用小波方法的良好去噪效果,提出一种基于小波去噪和时间序列分析的电离层TEC组合模型预测方法,采用欧洲定轨中心(CODE)发布的2021年数据对其进行分析。结果表明,对于高、中低纬度,使用组合模型的预测精度分别为96.14%、92.34%和85.09%。与传统的时间序列方法预测的结果相比,在高、中纬度的精度都有所提高,而低纬度精度相当,实验结果可验证本方法的有效性。展开更多
文摘Fast wavelet multi-resolution analysis (wavelet MRA) provides a effective tool for analyzing and canceling disturbing components in original signal. Because of its exponential frequency axis, this method isn't suitable for extracting harmonic components. The modified exponential time-frequency distribution ( MED) overcomes the problems of Wigner distribution( WD) ,can suppress cross-terms and cancel noise further more. MED provides high resolution in both time and frequency domains, so it can make out weak period impulse components fmm signal with mighty harmonic components. According to the 'time' behavior, together with 'frequency' behavior in one figure,the essential structure of a signal is revealed clearly. According to the analysis of algorithm and fault diagnosis example, the joint of wavelet MRA and MED is a powerful tool for fault diagnosis.
文摘Wavelet-fractal based SAR （synthetic aperture radar） image processing is one of the advanced technologies in image processing. The main concept of analysis is that after wavelet transformation, multifractal spectrum of the signal is different from that of noise. This difference is used to alleviate the noise produced by SAR image.The method to denoise SAR image using the process based on wavelet-fractai analysis is discussed in detail. Essentially, the present method focuses on adjusting the Hoelder exponent α of multifractal spectrum. After simulation, α should be adjusted to 1.72-1.73. The more the value of α exceeds 1.73, the less distinctive the edges of SAR image become. According to the authors denoising is optimal at α=1.72-1.73. In other words, when α =1.72-1.73, a smooth and denoised SAR image is produced.
基金This project is supported by National Natural Science Foundation of China (No.50205050).
文摘Based upon empirical mode decomposition (EMD) method and Hilbert spectrum, a method for fault diagnosis of roller bearing is proposed. The orthogonal wavelet bases are used to translate vibration signals of a roller bearing into time-scale representation, then, an envelope signal can be obtained by envelope spectrum analysis of wavelet coefficients of high scales. By applying EMD method and Hilbert transform to the envelope signal, we can get the local Hilbert marginal spectrum from which the faults in a roller bearing can be diagnosed and fault patterns can be identified. Practical vibration signals measured from roller bearings with out-race faults or inner-race faults are analyzed by the proposed method. The results show that the proposed method is superior to the traditional envelope spectrum method in extracting the fault characteristics of roller bearings.
基金financially supported by the National Natural Science Foundation of China(Grant No.51779141)the China Postdoctoral Science Foundation(Grant No.2018M630996)the State Key Laboratory of Ocean Engineering(Grant No.1710)
文摘The nonlinear wave forces on vertical cylinders induced by freak wave trains were experimentally investigated. A series of freak wave trains with different wave steepness were modeled in a wave flume. The corresponding wave forces on vertical cylinders of different diameters were measured. The experimental wave forces were also compared with the predicted results based on Morison formula. Particular attentions were paid to the effects of wave steepness on the dimensionless peak forces, asymmetry characteristics of the impact forces and high-frequency force components. Wavelet-based analysis methods were employed in revealing the local energy structures and quadratic phase coupling in the freak wave forces.
文摘Based on the brief introduction of the principles of wavelet analysis, this paper gives a summary of several typical wavelet bases from the point of view of perfect reconstruction of signals and emphasizes that designing wavelet bases which are used to decompose the signal into a two-band form is equivalent to designing a two-band filter bank with perfect or nearly perfect property. The generating algorithm corresponding to Daubechies bases and some simulated results are also given in the paper.
文摘This paper investigated approaches to supporting effective and efficient retrieval of image based on principle component analysis. First, it extracted the image content, texture and color. Gabor wavelet transforms were used to extract texture feature of the image and the average color was used to extract the color features. The principle component of the feature vector of image can be constructed. Content based image retrieval was performed by comparing the feature vector of the query image with the projection feature vector of the image database on the principle component space of the query image. By this technique, it can reduce the dimensionality of feature vector, which in turn reduce the searching time.
文摘The problem of seismic danger estimate in Japan after Tohoku mega-earthquake 11 March of 2011 is considered. The estimates are based on processing low-frequency seismic noise wave-forms from broadband network F-net. A new method of dynamic estimate of seismic danger is used for this problem. The method is based on calculating multi-fractal properties and minimum entropy of squared orthogonal wavelet coefficients for seismic noise. The analysis of the data using notion of “spots of seismic danger” shows that the seismic danger in Japan remains at high level after 2011. 03. 11 within north-east part of Philippine plate—at the region of Nankai Though which traditionally is regarded as the place of strongest earthquakes. It is well known that estimate of time moment of future shock is the most difficult problem in earthquake prediction. In this paper we try to find some peculiarities of the seismic noise data which could extract future danger time interval by analogy with the behavior before Tohoku earthquake. Two possible precursors of this type were found. They are the results of estimates within 1-year moving time window: based on correlation between 2 mean multi-fractal parameters of the noise and based on cluster analysis of annual clouds of 4 mean noise parameters. Both peculiarities of the noise data extract time interval 2013-2014 as the danger.
基金supported by Research Funding of Huddersfield University:GPU-based High Performance Computing for Signal Processing (No. 1008/REU117)
文摘The sense of being within a three-dimensional （3D） space and interacting with virtual 3D objects in a computer-generated virtual environment （VE） often requires essential image, vision and sensor signal processing techniques such as differentiating and denoising. This paper describes novel implementations of the Gaussian filtering for characteristic signal extraction and waveletbased image denoising algorithms that run on the graphics processing unit （GPU）. While significant acceleration over standard CPU implementations is obtained through exploiting data parallelism provided by the modern programmable graphics hardware, the CPU can be freed up to run other computations more efficiently such as artificial intelligence （AI） and physics. The proposed GPU-based Gaussian filtering can extract surface information from a real object and provide its material features for rendering and illumination. The wavelet-based signal denoising for large size digital images realized in this project provided better realism for VE visualization without sacrificing real-time and interactive performances of an application.
文摘基于时间序列方法能够对短时间的电离层总电子含量(Total Electron Content,TEC)进行较好预测,但由于电离层TEC受各种因素影响,直接使用原始TEC序列数据会受到各种噪声的干扰,影响其预测精度。本文利用小波方法的良好去噪效果,提出一种基于小波去噪和时间序列分析的电离层TEC组合模型预测方法,采用欧洲定轨中心(CODE)发布的2021年数据对其进行分析。结果表明,对于高、中低纬度,使用组合模型的预测精度分别为96.14%、92.34%和85.09%。与传统的时间序列方法预测的结果相比,在高、中纬度的精度都有所提高,而低纬度精度相当,实验结果可验证本方法的有效性。
