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Fault Diagnosis of On-Load Tap Changer Based on Optimized Empirical Modal Decomposition Algorithm

机译:基于优化经验模态分解算法的有载分接开关故障诊断

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In order to effectively monitor the operation of the on-load tape-changer (OLTC) online, an optimized empirical mode decomposition algorithm based on improved mask signal is proposed to analyze the vibration signals on the surface of the switched on load changers. An improved mask signal is added to the collected original signal, which can effectively eliminate the modal aliasing in the process of Empirical Mode Decomposition. Then the maximum power characteristic matrix is obtained according to the decomposed intrinsic mode function (IMF), further monitoring condition of the on-load tap switch. The results show that the maximum power characteristic matrix of OLTC in different operating states has obvious difference. When different typical faults occur in OLTC, the interval maximum power characteristic matrix index can effectively discriminate the degree of vibration signal difference.
机译:为了有效地在线监测带载换带器的运行情况,提出了一种基于改进的屏蔽信号的经验模式优化分解算法,以分析带载换带器表面的振动信号。将改进的屏蔽信号添加到收集的原始信号中,可以有效消除经验模态分解过程中的模态混叠。然后根据分解后的本征模式函数(IMF)获得最大功率特性矩阵,并进一步监视有载分接开关的状态。结果表明,不同工作状态下OLTC的最大功率特性矩阵存在明显差异。当OLTC中发生不同的典型故障时,区间最大功率特性矩阵指标可以有效地区分振动信号的差异程度。

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