【摘要】：局部放電檢測是電氣設備故障診斷最有效的方法之一,被廣泛應用于電纜附件故障診斷。但是,由于背景噪聲的存在,尤其是白噪聲的存在使得局部放電在線檢測的靈敏度大大降低。白噪聲的頻率成分遍布整個頻域,時域波形也遍布整個時域,這使得去除局放信號中的白噪聲干擾成為局放信號去噪技術(shù)中的一個難點和熱點研究課題�；谝陨险撌�,本文以電纜終端局部放電檢測為基礎提出了兩種局放信號去噪方法分別用以去除高信噪比和低信噪比下的白噪聲干擾。主要研究內(nèi)容如下:(1)分析了電纜終端發(fā)生故障的主要原因;設計制作了 4種電纜終端典型缺陷模型作為本文試驗部分的試驗對象開展局部放電試驗;采集了 4種電纜終端典型缺陷的局放信號作為本文所提去噪方法的試驗驗證。(2)提出了一種基于峭度和時域能量的局放信號去噪方法,用以解決高信噪比下現(xiàn)有局放信號去噪方法計算速率慢、去噪后脈沖邊沿不清晰的問題。首先通過計算染噪局放信號峭度實現(xiàn)局放脈沖的定位,進而確定局放脈沖峰值在整個數(shù)據(jù)窗中的位置以減小后續(xù)脈沖提取的計算量;其次通過分析白噪聲與局放脈沖信號的時域能量差異,確定時域能量閾值及對應的時窗長度;最后以脈沖峰值為中心采用時域能量搜索的方法向兩邊搜索脈沖的邊沿實現(xiàn)局部放電脈沖邊沿檢測及確定,進而實現(xiàn)局部放電脈沖提取。(3)提出了一種局放信號自適應稀疏分解去噪方法,同時構(gòu)造了與局放信號對應的匹配原子庫,用以提高局放信號去噪過程中MP算法的計算效率和去噪效果�；谛盘柨焖僮V峭度和S變換,迅速獲取局放信號時頻特性,其中包括中心頻率、帶寬、局放發(fā)生起始點和熄滅點的大概位置;利用局放信號的時頻特性優(yōu)化局放信號匹配原子庫的時頻參數(shù),在對染噪局放信號進行MP計算時自適應選擇少量原子進行尋優(yōu)匹配;用各次迭代所得最佳匹配原子對原始局放脈沖信號進行稀疏表示,達到局放信號去噪目的。仿真及試驗表明,本文所提出的兩種局放信號去噪方法有效的解決了現(xiàn)有局放信號去噪方法去噪過程中所存在的去噪程序繁瑣、計算速率慢、去噪不徹底、去噪后波形畸變問題。
[Abstract]:Partial discharge detection is one of the most effective methods for fault diagnosis of electrical equipment and is widely used in cable accessory fault diagnosis. However, because of the background noise, especially the white noise, the sensitivity of PD on-line detection is greatly reduced. The frequency components of white noise are all over the frequency domain, and the waveform of time domain is all over the time domain, which makes the removal of white noise interference from partial discharge signal become a difficult and hot research topic in the denoising technology of partial discharge signal. Based on the above discussion, based on the partial discharge detection of cable terminal, two kinds of partial discharge signal denoising methods are proposed to remove white noise interference at high signal-to-noise ratio and low signal-to-noise ratio respectively. The main research contents are as follows: (1) the main causes of cable terminal failure are analyzed, and four typical defect models of cable terminal are designed and made as the test object of this paper to carry out partial discharge test. Four kinds of partial discharge signals with typical defects of cable terminals are collected as experimental verification of the denoising methods proposed in this paper. (2) A denoising method for partial discharge signals based on kurtosis and time domain energy is proposed. It is used to solve the problem of slow calculation speed and unclear pulse edge of existing partial discharge signal denoising methods under high SNR. Firstly, the location of partial discharge pulse is realized by calculating the kurtosis of local discharge signal, and then the position of peak value of partial discharge pulse in the whole data window is determined to reduce the computation amount of subsequent pulse extraction. Secondly, by analyzing the time domain energy difference between white noise and partial discharge pulse signal, the time domain energy threshold and the corresponding time window length are determined. Finally, using the time-domain energy search method to search the edge of the pulse on both sides, the detection and determination of the partial discharge pulse edge can be realized by taking the peak value of the pulse as the center. Then partial discharge pulse extraction is realized. (3) an adaptive sparse decomposition de-noising method for partial discharge signal is proposed, and a matching atom library corresponding to partial discharge signal is constructed. In order to improve the computational efficiency and denoising effect of MP algorithm in the process of partial discharge signal denoising. Based on the fast spectral kurtosis and S-transform, the time-frequency characteristics of PD signal are obtained, including the center frequency, bandwidth, the starting point of PD and the approximate position of extinguishing point. The time-frequency parameters of the partial discharge signal matching atom library are optimized by using the time-frequency characteristic of partial discharge signal, and a small number of atoms are adaptively selected for optimal matching when MP calculation is carried out on the noisy partial discharge signal. The original PD pulse signal is represented sparsely by the best matching atoms obtained from each iteration to achieve the purpose of de-noising the PD signal. The simulation and experiments show that the two methods proposed in this paper can effectively solve the problem that the existing partial discharge signal denoising methods are complicated in the process of de-noising, slow calculation rate and incomplete de-noising. Waveform distortion after denoising.
【學位授予單位】：西南石油大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM855

【參考文獻】

相關(guān)期刊論文 前10條

1 尚海昆;王坤;李峰;;基于集合經(jīng)驗模態(tài)分解法的局部放電信號去噪[J];東北電力大學學報;2016年04期

2 王恩俊;張建文;馬曉偉;馬鴻宇;;基于CEEMD-EEMD的局部放電閾值去噪新方法[J];電力系統(tǒng)保護與控制;2016年15期

3 何聰;袁川;曾偉;張安安;;XLPE高壓電力電纜局部放電檢測方法[J];電網(wǎng)與清潔能源;2016年05期

4 楊豐源;宋輝;程序;段大鵬;陶詩洋;侯慧娟;;基于改進EEMD和Cohen類的局部放電信號聯(lián)合時頻分析[J];高電壓技術(shù);2016年07期

5 宋亞奇;周國亮;朱永利;李莉;王德文;;云平臺下并行總體經(jīng)驗模態(tài)分解局部放電信號去噪方法[J];電工技術(shù)學報;2015年18期

6 李軍浩;韓旭濤;劉澤輝;李彥明;;電氣設備局部放電檢測技術(shù)述評[J];高電壓技術(shù);2015年08期

7 張宇輝;劉夢婕;黃南天;段偉潤;李天云;;頻率切片小波變換在局部放電信號分析中的應用[J];高電壓技術(shù);2015年07期

8 吳炬卓;牛海清;;基于提升小波分解的小波熵在抑制局部放電白噪聲干擾中的應用[J];高壓電器;2014年12期

9 尚海昆;苑津莎;王瑜;靳松;;平移不變小波跡消噪方法在局部放電檢測中的應用[J];電工技術(shù)學報;2013年10期

10 陳剛;劉志剛;張巧革;;一種基于譜峭度的局部放電信號提取新方法[J];電力自動化設備;2013年08期

相關(guān)碩士學位論文 前7條

1 徐洋濤;基于HHT的電力電纜附件故障診斷技術(shù)研究[D];西南石油大學;2016年

2 魯飛宇;希爾伯特—黃變換在變壓器局部放電信號去噪與模式識別中的應用研究[D];西安電子科技大學;2013年

3 陳偉璇;局部放電信號的去噪算法研究[D];華南理工大學;2012年

4 周力;基于超高頻的電纜及其附件產(chǎn)品局部放電檢測系統(tǒng)的研究[D];湖南大學;2012年

5 紀新宇;XLPE電纜接頭局部放電檢測與模式識別的研究[D];華北電力大學;2012年

6 邵列;局部放電檢測系統(tǒng)中的信號去噪與模式識別的研究[D];西安電子科技大學;2009年

7 張明霞;用小波技術(shù)濾除變壓器局部放電信號中噪聲的方法研究[D];重慶大學;2007年

，

本文編號：2300789