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Simultaneous location of two partial discharge sources in power transformers based on acoustic emission using the modified binary partial swarm optimisation algorithm

机译:使用改进的二进制局部群优化算法,基于声发射的电力变压器中两个局部放电源的同时定位

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摘要

One of the main methods for partial discharge (PD) source localisation in power transformers is acoustic emission measurements. This study describes a new method for detection and location of two simultaneous partial discharge sources in three-phase power transformer. In this method, acoustic signals are detected by sensors first and are then denoised using a wavelet transform. Finally, the two PD sources are localised using the modified binary partial swarm optimisation (MBPSO) method. To prove the efficiency of the two simultaneous PD localisations, the proposed algorithm is used to localise PD sources of the arc furnace transformer at Isfahan??s Mobarakeh steel company. For this purpose, the PD localisation problem converts to an optimisation problem. To prove the efficiency of the MBPSO algorithm, its performance is compared with a genetic algorithm. The PD localisation results confirm the efficiency of the proposed method for the detection and location of PD sources.
机译:电力变压器中局部放电(PD)源定位的主要方法之一是声发射测量。这项研究描述了一种检测和定位三相电力变压器中两个同时部分放电源的新方法。在这种方法中,声波信号首先由传感器检测,然后使用小波变换进行消噪。最后,使用改进的二进制部分群优化(MBPSO)方法对两个PD源进行了本地化。为了证明两个同时局部放电定位的效率,提出的算法用于对伊斯法罕Mobarakeh钢铁公司的电弧炉变压器的局部放电源进行定位。为此,PD定位问题转换为优化问题。为了证明MBPSO算法的效率,将其性能与遗传算法进行了比较。 PD定位结果证实了所提出方法对PD源的检测和定位的效率。

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