小波消噪在10kV金属氧化物避雷器在线检测中的应用

发布时间：2018-03-13 20:09

本文选题：金属氧化物避雷器　切入点：在线监测　出处：《高电压技术》2014年03期 　论文类型：期刊论文

【摘要】：针对金属氧化物避雷器(MOA)泄漏电流检测信号包含噪声的问题,提出了一种将新阈值法和平移不变小波相结合的消噪方法。该方法对含噪的金属氧化物避雷器在线检测信号进行小波分解,对分解后不同尺度下的小波信号进行平移,并同时按新阈值法进行处理,最后重构信号。将所提出的小波消噪方法用于10 kV金属氧化物避雷器的在线监测,提取去噪前后的泄漏电流检测信号波形进行分析对比。结果表明,该方法的消噪效果显著,消噪能力远优于传统的软、硬阈值消噪法。经小波消噪后的泄漏电流波形变得明显清晰,很容易从波形上对正常避雷器和老化避雷器进行区分,可以作为10 kV配电网MOA在线监测的依据。
[Abstract]:Aiming at the problem of noise in the leakage current detection signal of metal oxide arrester (MOA), A new de-noising method is proposed, which combines the new threshold method with the translational invariant wavelet, which decomposes the on-line detection signal of the metal oxide arrester with noise and translates the wavelet signal at different scales after decomposition. At the same time, the signal is reconstructed according to the new threshold method. The proposed wavelet de-noising method is applied to the on-line monitoring of 10 kV MOA. The waveform of leakage current detection signal before and after de-noising is analyzed and compared. The results show that this method has a remarkable effect on de-noising, and the de-noising ability is far better than that of the traditional soft. Hard threshold de-noising method. The leakage current waveform after wavelet de-noising becomes clear and it is easy to distinguish the normal arrester from the aging arrester from the waveform, which can be used as the basis for on-line monitoring of MOA in 10 kV distribution network.
【作者单位】：重庆市电力公司市区供电局;重庆市电力公司检修分公司;广东电网公司东莞供电局;重庆大学输配电装备及系统安全与新技术国家重点实验室;
【分类号】：TM862.1

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