配电网单相接地故障产生的高频信号可以用于接地故障选线.利用馈线零序电流特征频带(SFB),提出一种连续小波变换(CWT)系数的均方根(Root Mean Square,RMS)值与人工神经网络(ANN)相结合的故障选线方法.通过对各条馈线故障后5ms时零序电...配电网单相接地故障产生的高频信号可以用于接地故障选线.利用馈线零序电流特征频带(SFB),提出一种连续小波变换(CWT)系数的均方根(Root Mean Square,RMS)值与人工神经网络(ANN)相结合的故障选线方法.通过对各条馈线故障后5ms时零序电流进行CWT变换,剔除工频信号,并根据能量和最大原则选出故障特征频带.将各条馈线特征频带上CWT系数的均方根值作为ANN选线的输入样本属性,故障馈线编号作为输出样本属性,构造智能选线网络.该方法不需要提出明确的故障选线判据,利用ANN非线性拟合和记忆功能进行故障选线.大量的实验仿真数据表明,该方法选线结果准确可靠.展开更多
Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform （CWT） has been successfully used in the field of fault diagnosis. The principle of ...Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform （CWT） has been successfully used in the field of fault diagnosis. The principle of scale selection in CWT is discussed. Based on genetic algorithm, an optimization strategy for the waveform parameters of the mother wavelet is proposed with wavelet entropy as the optimization target. Based on the optimized waveform parameters, the wavelet scalogram is used to analyze the simulated acoustic emission （AE） signal and real AE signal of rolling bearing. The results indicate that the proposed method is useful and efficient to improve the quality of CWT.展开更多
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
文摘配电网单相接地故障产生的高频信号可以用于接地故障选线.利用馈线零序电流特征频带(SFB),提出一种连续小波变换(CWT)系数的均方根(Root Mean Square,RMS)值与人工神经网络(ANN)相结合的故障选线方法.通过对各条馈线故障后5ms时零序电流进行CWT变换,剔除工频信号,并根据能量和最大原则选出故障特征频带.将各条馈线特征频带上CWT系数的均方根值作为ANN选线的输入样本属性,故障馈线编号作为输出样本属性,构造智能选线网络.该方法不需要提出明确的故障选线判据,利用ANN非线性拟合和记忆功能进行故障选线.大量的实验仿真数据表明,该方法选线结果准确可靠.
基金This project is supported by National Natural Science Foundation of China (No. 50105007)Program for New Century Excellent Talents in University, China.
文摘Morlet wavelet is suitable to extract the impulse components of mechanical fault signals. And thus its continuous wavelet transform （CWT） has been successfully used in the field of fault diagnosis. The principle of scale selection in CWT is discussed. Based on genetic algorithm, an optimization strategy for the waveform parameters of the mother wavelet is proposed with wavelet entropy as the optimization target. Based on the optimized waveform parameters, the wavelet scalogram is used to analyze the simulated acoustic emission （AE） signal and real AE signal of rolling bearing. The results indicate that the proposed method is useful and efficient to improve the quality of CWT.
文摘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.
