车辆悬架减振器引致的车内异响问题严重削弱了车内声品质,该异响声信号为非平稳信号且带宽特殊,致使传统的心理声学客观评价指标难以准确提取其异响特征信息。而小波分析作为一种有效的非平稳信号分析方法,能够有效克服心理声学客观评...车辆悬架减振器引致的车内异响问题严重削弱了车内声品质,该异响声信号为非平稳信号且带宽特殊,致使传统的心理声学客观评价指标难以准确提取其异响特征信息。而小波分析作为一种有效的非平稳信号分析方法,能够有效克服心理声学客观评价指标的上述缺陷,经实践得以验证。但是由于经典的小波分析根植于特定基函数的叠加,导致单个基函数导出的小波函数族难以在不同尺度上准确地逼近局部信号特征。为此,在小波分析的基础上,结合经验模态分解(EMD)和Wigner-Ville分布的优点,并引入相关分析去噪的概念,提出并建立了新的减振器异响声品质评价参数SQCIMF-WVD(Sound Quality base on Choosing IMF and then proceed WVD),其与主观评价的相关系数进一步提高,更能准确反映减振器异响声品质的特点。展开更多
提出一种WVD(Wigner Ville distribution)的改进方法。应用离散余弦谐波小波变换对多分量信号进行分解,计算分解后得到的单分量信号的WVD,将单分量信号的WVD沿频率轴串联得到整个信号的WVD,抑制分布的交叉项。应用修改群延时函数减少因...提出一种WVD(Wigner Ville distribution)的改进方法。应用离散余弦谐波小波变换对多分量信号进行分解,计算分解后得到的单分量信号的WVD,将单分量信号的WVD沿频率轴串联得到整个信号的WVD,抑制分布的交叉项。应用修改群延时函数减少因WVD核函数截断而产生的波动效应,改善分布的时频分辨率。通过算例中的线性调频信号和应用实例中轴承振动信号验证表明,改进后的WVD有满意的时频分辨率和明显的交叉项抑制能力,能够通过离散余弦变换实现其快速算法,算法快速、简单,适合非平稳工程信号的时频分析。展开更多
In the time-frequency analysis of seismic signals, the matching pursuit algorithm is an effective tool for non-stationary signals, and has high time-frequency resolution and a transient structure with local self-adapt...In the time-frequency analysis of seismic signals, the matching pursuit algorithm is an effective tool for non-stationary signals, and has high time-frequency resolution and a transient structure with local self-adaption. We expand the time-frequency dictionary library with Ricker, Morlet, and mixed phase seismic wavelets, to make the method more suitable for seismic signal time-frequency decomposition. In this paper, we demonstrated the algorithm theory using synthetic seismic data, and tested the method using synthetic data with 25% noise. We compared the matching pursuit results of the time-frequency dictionaries. The results indicated that the dictionary which matched the signal characteristics better would obtain better results, and can reflect the information of seismic data effectively.展开更多
This paper presents the methodology, properties and processing of the time-frequency techniques for non-stationary signals, which are frequently used in biomedical, communication and image processing fields. Two class...This paper presents the methodology, properties and processing of the time-frequency techniques for non-stationary signals, which are frequently used in biomedical, communication and image processing fields. Two classes of time-frequency analysis techniques are chosen for this study. One is short-time Fourier Transform (STFT) technique from linear time-frequency analysis and the other is the Wigner-Ville Distribution (WVD) from Quadratic time-frequency analysis technique. Algorithms for both these techniques are developed and implemented on non-stationary signals for spectrum analysis. The results of this study revealed that the WVD and its classes are most suitable for time-frequency analysis.展开更多
文摘车辆悬架减振器引致的车内异响问题严重削弱了车内声品质,该异响声信号为非平稳信号且带宽特殊,致使传统的心理声学客观评价指标难以准确提取其异响特征信息。而小波分析作为一种有效的非平稳信号分析方法,能够有效克服心理声学客观评价指标的上述缺陷,经实践得以验证。但是由于经典的小波分析根植于特定基函数的叠加,导致单个基函数导出的小波函数族难以在不同尺度上准确地逼近局部信号特征。为此,在小波分析的基础上,结合经验模态分解(EMD)和Wigner-Ville分布的优点,并引入相关分析去噪的概念,提出并建立了新的减振器异响声品质评价参数SQCIMF-WVD(Sound Quality base on Choosing IMF and then proceed WVD),其与主观评价的相关系数进一步提高,更能准确反映减振器异响声品质的特点。
文摘提出一种WVD(Wigner Ville distribution)的改进方法。应用离散余弦谐波小波变换对多分量信号进行分解,计算分解后得到的单分量信号的WVD,将单分量信号的WVD沿频率轴串联得到整个信号的WVD,抑制分布的交叉项。应用修改群延时函数减少因WVD核函数截断而产生的波动效应,改善分布的时频分辨率。通过算例中的线性调频信号和应用实例中轴承振动信号验证表明,改进后的WVD有满意的时频分辨率和明显的交叉项抑制能力,能够通过离散余弦变换实现其快速算法,算法快速、简单,适合非平稳工程信号的时频分析。
文摘In the time-frequency analysis of seismic signals, the matching pursuit algorithm is an effective tool for non-stationary signals, and has high time-frequency resolution and a transient structure with local self-adaption. We expand the time-frequency dictionary library with Ricker, Morlet, and mixed phase seismic wavelets, to make the method more suitable for seismic signal time-frequency decomposition. In this paper, we demonstrated the algorithm theory using synthetic seismic data, and tested the method using synthetic data with 25% noise. We compared the matching pursuit results of the time-frequency dictionaries. The results indicated that the dictionary which matched the signal characteristics better would obtain better results, and can reflect the information of seismic data effectively.
文摘This paper presents the methodology, properties and processing of the time-frequency techniques for non-stationary signals, which are frequently used in biomedical, communication and image processing fields. Two classes of time-frequency analysis techniques are chosen for this study. One is short-time Fourier Transform (STFT) technique from linear time-frequency analysis and the other is the Wigner-Ville Distribution (WVD) from Quadratic time-frequency analysis technique. Algorithms for both these techniques are developed and implemented on non-stationary signals for spectrum analysis. The results of this study revealed that the WVD and its classes are most suitable for time-frequency analysis.
