【作者】 陈青；

【导师】 朱永利；

【作者基本信息】 华北电力大学 ， 计算机应用技术， 2011， 硕士

【摘要】 研究发现绝缘泄漏电流与绝缘子故障关系密切,能够科学地表征绝缘子绝缘水平。绝缘子泄漏电流尤其在闪络放电过程中含有大量高频脉冲分量,对信号的采样速率和处理速度要求很高,其庞大的采集数据量给数据通信和存储造成了严重的负担。研究发现绝缘子泄漏电流在某一变换域下是稀疏的,课题研究分析压缩传感理论实现对绝缘子泄漏电流的数据压缩。压缩传感以远远低于奈奎斯特采样定理的频率实现对高频绝缘子泄漏电流的采集,从而降低数据通信和存储负担,使高频信号采集成为可能。本文研究分析傅立叶变换与小波变换对绝缘子泄漏电流的稀疏表示的效果,求出具有局部分辨性的小波变换较之全局性的傅立叶变换,更能简洁表示泄漏电流信号。对高斯测量矩阵的测量数与泄漏电流的稀疏度的关系进行深入研究,结合实验数据,得出测量数与稀疏度的大致关系。围绕压缩传感理论对输电线路绝缘子泄漏电流先进行小波变换的稀疏表示,然后经过高斯测量矩阵线性投影获取测量值,最后由正交匹配追踪算法恢复原始信号。实验结果表明,由少量的测量值能够高精度地恢复原始信号,不仅降低对传感器采样频率的要求,而且极大地降低了数据存储和传输代价。为了进一步提高信号重构的速度,在小波稀疏变换基础上,引入经验模态(EMD)分解方法对绝缘泄漏电流进行平稳化处理。改进方法得到实验结果与原有算法的结果对比,可以看出优化后的算法在提高重构运算速度的同时,也能够精确的重构原始信号。更多还原

【Abstract】 Research finds that leakage current is closely related to flashover discharge, it can characterize external insulation status of insulator scientifically. Insulator leakage current especially in the flashover discharge process contains a lot of high-frequency pulse component,it requires the signal sampling rate and processing speed higher. So the huge data collection caused great burden on the data communication and storage.Found that leakage current is sparse under a certain transform domain, insulator leakage current was compressed in the subject based on compressed sensing theory. Sampling frequency that compressed sensing sampled high-frequency leakage current is far below the Nyquist sampling theorem,thus it reduces the burden of data communication and storage, making high-frequency signal acquisition possibly.In this paper,we analyse insulation leakage current sparsity between the wavelet and fourier transform.From these results, wavelet transform represents the leakage current signal more succinct than fourier transform.Relation has be made study of the measurement and the sparsity in a deep-going way. We have found the approximate relationship between measurement and sparity by combining experimental data.The simulation experiment encloses insulator leakage current in the transmission line based on compressed sensing, it first represents the non-stationary insulation leakage current sparse by wavelet transform, and then projects linear measurement by Gaussian measurement matrix, and finally adopts orthogonal matching pursuit algorithm to restore original signal.Experimental results show that the original signal can be recovered by a few of measurements with high precision.The algorithm not only reduces the required sampling frequency of the sensor, but also the data storage and transmission costs.To further improve the reconstruction speed, empirical mode decomposition method is induced to process insulation leakage current stably after the analysis of limitations from the wavelet and Fourier transform processing non-stationary signals . Compressed sensing was applied to compression simulation experiment. We can see that the optimized algorithm not only improved reconstruction computing speed but also reconstructed original signal precisely by contrasting experimental results of original algorithm.更多还原