基于CEEMD-EEMD的局部放电阈值去噪新方法
为了解决局部放电信号去噪过程中自适应性不足,提出了基于完全经验模态分解和总体平均经验模态分解（CEEMD-EEMD）的局部放电阈值去噪新方法。首先将放电信号进行CEEMD分解,其次对分解出来的固有模态函数进行EEMD分解,根据数理统计的知识将分解后的信号进行阈值去噪。利用该算法对局部放电的仿真信号和实测信号进行去噪处理,并与常规的小波去噪算法比较分析。仿真和实验的去噪结果表明,基于CEEMD-EEMD的局部放电阈值去噪方法取得了良好的去噪效果,验证了该方法的有效性,从而为局部放电信号的预处理提供了一种新思路。...
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| Published in | 电力系统保护与控制 Vol. 44; no. 15; pp. 93 - 98 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国矿业大学信息与电气工程学院,江苏徐州,221008
2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1674-3415 |
| DOI | 10.7667/PSPC151487 |
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| Abstract | 为了解决局部放电信号去噪过程中自适应性不足,提出了基于完全经验模态分解和总体平均经验模态分解（CEEMD-EEMD）的局部放电阈值去噪新方法。首先将放电信号进行CEEMD分解,其次对分解出来的固有模态函数进行EEMD分解,根据数理统计的知识将分解后的信号进行阈值去噪。利用该算法对局部放电的仿真信号和实测信号进行去噪处理,并与常规的小波去噪算法比较分析。仿真和实验的去噪结果表明,基于CEEMD-EEMD的局部放电阈值去噪方法取得了良好的去噪效果,验证了该方法的有效性,从而为局部放电信号的预处理提供了一种新思路。 |
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| AbstractList | 为了解决局部放电信号去噪过程中自适应性不足,提出了基于完全经验模态分解和总体平均经验模态分解（CEEMD-EEMD）的局部放电阈值去噪新方法。首先将放电信号进行CEEMD分解,其次对分解出来的固有模态函数进行EEMD分解,根据数理统计的知识将分解后的信号进行阈值去噪。利用该算法对局部放电的仿真信号和实测信号进行去噪处理,并与常规的小波去噪算法比较分析。仿真和实验的去噪结果表明,基于CEEMD-EEMD的局部放电阈值去噪方法取得了良好的去噪效果,验证了该方法的有效性,从而为局部放电信号的预处理提供了一种新思路。 为了解决局部放电信号去噪过程中自适应性不足,提出了基于完全经验模态分解和总体平均经验模态分解(CEEMD-EEMD)的局部放电阈值去噪新方法.首先将放电信号进行CEEMD分解,其次对分解出来的固有模态函数进行EEMD分解,根据数理统计的知识将分解后的信号进行阈值去噪.利用该算法对局部放电的仿真信号和实测信号进行去噪处理,并与常规的小波去噪算法比较分析.仿真和实验的去噪结果表明,基于CEEMD-EEMD的局部放电阈值去噪方法取得了良好的去噪效果,验证了该方法的有效性,从而为局部放电信号的预处理提供了一种新思路. |
| Author | 王恩俊 张建文 马晓伟 马鸿宇 |
| AuthorAffiliation | 中国矿业大学信息与电气工程学院,江苏徐州221008 |
| AuthorAffiliation_xml | – name: 中国矿业大学信息与电气工程学院,江苏徐州,221008 |
| Author_FL | MA Xiaowei WANG Enjun ZHANG Jianwen MA Hongyu |
| Author_FL_xml | – sequence: 1 fullname: WANG Enjun – sequence: 2 fullname: ZHANG Jianwen – sequence: 3 fullname: MA Xiaowei – sequence: 4 fullname: MA Hongyu |
| Author_xml | – sequence: 1 fullname: 王恩俊 张建文 马晓伟 马鸿宇 |
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| DocumentTitleAlternate | A new threshold denoising algorithm for partial discharge based on CEEMD-EEMD |
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| Keywords | thresholding denoising 局部放电 完全经验模态分解 EEMD 阈值去噪 wavelet denoising CEEMD 总体平均经验模态分解 小波去噪 partial discharge |
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| Notes | WANG Enjun,ZHANG Jianwen,MA Xiaowei,MA Hongyu（School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou 221008, China） To solve the problem that the adaptability of partial discharge signals is not insufficient in denoising process, a new algorithm of partial discharge thresholding denoising based on complete ensemble empirical mode decomposition and ensemble empirical mode decomposition is proposed. Firstly, the discharge signals should be decomposed by CEEMD. Secondly, the intrinsic mode functions which have been broken out by CEEMD should be decomposed by EEMD. Thirdly, the thresholding denoising of decomposed signals is carried on based on the knowledge of mathematical statistics. This paper makes use of the new algorithm to denoise for simulation signals and measured signals and to compare with the conventional wavelet denoising algorithm. The simulation results and experimental results show that the thresholding denoising algorithm for partial discharge based on |
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| PublicationTitle | 电力系统保护与控制 |
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| PublicationTitle_FL | Power System Protection and Control |
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| Publisher | 中国矿业大学信息与电气工程学院,江苏徐州,221008 |
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| SubjectTerms | 完全经验模态分解 小波去噪 局部放电 总体平均经验模态分解 阈值去噪 |
| Title | 基于CEEMD-EEMD的局部放电阈值去噪新方法 |
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