摘要
介质损耗角是反映变电站容性设备绝缘程度的重要指标,在线监测处理方法采用数字化测量技术。依据绝缘特性的老化机理,监测数据具有一定的分散性和冗余性,因此,提出采用压缩比可变的嵌入式零树小波算法,对数据进行有效的压缩,提高信息管理的效率;利用最优相关滤波电路,滤除锯齿状波动和剔点等虚假信号,并将此信号转换成频域信号,通过小波重构方法进行特征值的提取。通过仿真分析验证,结果表明:对特征值的提取,可以提高容性设备绝缘诊断的准确性,实验验证该方法可行。
Dielectric loss angle is an important index reflecting insulation degree of substation capaci- tive equipment. On-line monitoring and processing method uses the digital measurement technology. This paper proposes an embedded zero tree wavelet algorithm with variable compression ratio designed for over- coming dispersion and redundancy in monitoring data due to aging mechanism of insulation characteristic. This algorithm works by effectively compressing data, improving the efficiency of information manage- ment, filtering out false signals such as serrated wave and faulty value using optimal related filter circuit, and transforming the signal to the frequency domain signal, and extracting the eigenvalues by the method of wavelet reconstruction. Both simulation and verification show that the algorithm affords an improved ac- curacy of capacitive equipment insulation diagnosis.
出处
《黑龙江科技大学学报》
CAS
2016年第2期187-191,共5页
Journal of Heilongjiang University of Science And Technology
基金
黑龙江省教育厅科学技术研究项目(12541697)
关键词
嵌入式零树小波算法
最优相关滤波
小波重构
介质损耗角
在线监测
embedded zerotree wavelet algorithm
optimization correlative filter
wavelet reconstruction
dielectric loss angle
on-line monitoring