提升双树复小波在GIS局部放电监测白噪声抑制的应用

发布时间：2019-06-24 10:00

【摘要】：GIS局部放电在线监测过程中原本就微弱的放电信号往往会被白噪声所淹没,因此抑制白噪声是GIS局部放电在线监测工作中必不可少的环节。为了更加有效且快速地抑制局放在线监测中白噪声的干扰,针对第1代小波去噪算法存在着去噪效果不佳、计算效率低等不足之处,结合双树复小波变换良好的去噪能力和提升小波变换高效的计算能力,提出对双树复小波变换进行提升,得到第二代双树复小波变换,应用提升双树复小波变换进行白噪声抑制研究,并且在局部放电在线监测软件系统中引入该算法,应用于现场监测实验。仿真和实验结果表明,较之其他去噪算法,提升双树复小波变换算法的运算速度提高了83%,内存占用降低了将近50%,信噪比得到了提高,且波形相似系数更接近1,更能满足GIS局部放电在线监测的实时性要求,在工程实践中具有更高的应用价值。
[Abstract]:In the process of on-line monitoring of partial discharge of GIS, the weak discharge signal is often inundated by white noise, so the suppression of white noise is an essential part in the on-line monitoring of partial discharge of GIS. in ord to more effectively and quickly suppress that interference of white noise in line monitoring, the first generation wavelet de-noising algorithm has the disadvantages of poor de-noising effect, low calculation efficiency and the like, and combines the good denoising capability of the double-tree complex wavelet transform and the high-efficiency computing capability of the wavelet transform, The two-tree complex wavelet transform is improved to get the second-generation double-tree complex wavelet transform, and the white noise suppression research is carried out by using the improved double-tree complex wavelet transform, and the algorithm is introduced in the local discharge on-line monitoring software system and applied to the field monitoring experiment. The simulation and experimental results show that, compared with other de-noising algorithms, the operation speed of the double-tree complex wavelet transform algorithm is improved by 83%, the memory occupation is reduced by nearly 50%, the signal-to-noise ratio is improved, and the waveform similarity coefficient is closer to 1, The method can meet the real-time requirement of the on-line monitoring of partial discharge of GIS, and has higher application value in engineering practice.
【作者单位】：国网湖南省电力公司电力科学研究院;湖南大学电气与信息工程学院;国网湖南省电力公司;
【基金】：国家自然科学基金(61102039) 国家重点基础技术研究发展计划(973计划)(2012CB215106) 国家高技术研究发展计划(863计划)(2014AA052600) 教育部新世纪优秀人才支持计划(NCET-11-0130)~~
【分类号】：TM855

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