文章摘要
李大华,孔凌风,高强,于晓,杜洋.基于三次相关改进的广义互相关时延估计法在局部放电超声波定位中的研究[J].声学技术,2022,41(5):774~781
基于三次相关改进的广义互相关时延估计法在局部放电超声波定位中的研究
Study on cubic correlation improvement based generalized cross correlation time delay estimation method of supersonic waves detection method for location partial discharge
投稿时间:2021-05-28  修订日期:2021-07-15
DOI:10.16300/j.cnki.1000-3630.2022.05.021
中文关键词: 局部放电  超声波定位法  到达时间差  时延估计算法
英文关键词: partial discharge  ultrasonic positioning method  time difference of arrival  time delay estimation algorithm
基金项目:
作者单位E-mail
李大华 天津理工大学电气电子工程学院, 天津 300384  
孔凌风 天津理工大学电气电子工程学院, 天津 300384 2302375864@qq.com 
高强 天津理工大学电气电子工程学院, 天津 300384  
于晓 天津理工大学电气电子工程学院, 天津 300384  
杜洋 天津三源电力智能科技有限公司, 天津 300409  
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中文摘要:
      在现有的开关柜等电气设备局部放电超声波定位技术中,到达时间差定位法(Time Difference of Arrival,TDOA)在定位精度与技术实现等方面有着一定的优势,得到了广泛的使用,是目前常用的方法,其中的时延估计算法对整个系统起着关键作用。文章首先对目前现有的基本相关、广义相关、二次相关等时延估计算法进行了分析。其次,在二次相关基础上再进行一次相关,并设计了新型的加权函数,将三次相关与广义互相关结合在一起,成为一种新的方法,即广义三次相关时延估计法。最后,搭建了相应的开关柜实验平台并对以上方法进行了实验及对比,分析了各算法的性能。结果表明,广义三次相关时延估计法在相对强噪声环境中较其他算法抗噪性能更强,具有更好的优越性。
英文摘要:
      In the existing ultrasonic positioning method of partial discharge for switchgear cabinet and other electrical equipment, time difference of arrival (TDOA) method has been widely used due to the advantage in positioning accuracy and technical implementation. Considering that the time delay estimation algorithm plays a leading role in the whole positioning system, the basic correlation, generalized correlation, quadratic correlation and other time delay estimation algorithms are analyzed in this paper. Then, based on the quadratic correlation, a new method, named the generalized cubic correlation time delay estimation method is presented by performing once more correlation again with new designed weighting functions. Finally, an experimental platform of switch cabinet is built to test the above methods and make comparative analyses. The performances of various algorithms are analyzed and compared. The results show that the generalized cubic correlation time delay estimation method has better advantages and better antinoise performance than other algorithms in relatively strong noise environment.
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