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Efficient method for location and detection of partial discharge in transformer oil by DOA estimation of circular array of ultrasonic sensors

机译:超声波传感器圆形阵列DOA估计变压器油中局部放电的位置和检测方法

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摘要

The electrical insulation failures in oil transformers are mainly occurs due to the inappropriate placing of Partial Discharge (PD) sources. In order to eliminate the insulation defects and also to locate the PD sources in an appropriate location, a new approach called circular array of ultrasonic sensors (CAUS) with various analysis is proposed. At first de-noise the PD signal from the CAUS using the fast independent component analysis (Fast ICA) algorithm. Secondly,the wide band signal from CAUS is converted into narrow band signal by using the total least square algorithm (TLS). Third, parse representation of array covariance vector (SRACV) technique is utilized to separate DOA (Direction of Arrival) in three directions from PD to CAUS. Finally,the PD sources are placed in an appropriate location by using the pitch and azimuth angles of those three DOAs and the exact coordination of three planes are calculated by using the particle swarm optimization algorithm. The simulation result demonstrates the effectiveness of proposed approach in terms of PD location in transformer oil.
机译:由于局部放电(PD)源的放置不适当,油变压器中的电气绝缘故障主要发生。为了消除绝缘缺陷并且还在适当位置定位PD源,提出了一种具有各种分析的新方法称为圆形超声传感器(GAN)的圆形传感器阵列。首先通过快速独立分量分析(FAST ICA)算法,从此发出噪声来自原因的PD信号。其次,通过使用总体最小方算法(TLS)将来自原因的宽带信号转换为窄带信号。第三,阵列协方差向量(SRACV)技术的解析表示用于将DOA(到达方向)与PD的三个方向分开。最后,通过使用这三个DOA的间距和方位角,通过使用粒子群优化算法计算三个平面的精确协调,PD源放置在适当的位置。仿真结果表明了在变压器油中PD位置方面提出的方法的有效性。

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