The soft fault induced by parameter variation is one of the most challenging problems in the domain of fault diagnosis for analog circuits.A new fault location and parameter prediction approach for soft-faults diagnos...The soft fault induced by parameter variation is one of the most challenging problems in the domain of fault diagnosis for analog circuits.A new fault location and parameter prediction approach for soft-faults diagnosis in analog circuits is presented in this paper.The proposed method extracts the original signals from the output terminals of the circuits under test(CUT) by a data acquisition board.Firstly,the phase deviation value between fault-free and faulty conditions is obtained by fitting the sampling sequence with a sine curve.Secondly,the sampling sequence is organized into a square matrix and the spectral radius of this matrix is obtained.Thirdly,the smallest error of the spectral radius and the corresponding component value are obtained through comparing the spectral radius and phase deviation value with the trend curves of them,respectively,which are calculated from the simulation data.Finally,the fault location is completed by using the smallest error,and the corresponding component value is the parameter identification result.Both simulated and experimental results show the effectiveness of the proposed approach.It is particularly suitable for the fault location and parameter identification for analog integrated circuits.展开更多
低压台区拓扑信息的准确记录是进行台区线损分析、三相不平衡治理等工作的基础。针对目前拓扑档案排查成本高且效率低的问题,提出一种基于自适应k近邻(adaptive k nearest neighbor,AKNN)异常检验和自适应密度峰值(adaptive density pea...低压台区拓扑信息的准确记录是进行台区线损分析、三相不平衡治理等工作的基础。针对目前拓扑档案排查成本高且效率低的问题,提出一种基于自适应k近邻(adaptive k nearest neighbor,AKNN)异常检验和自适应密度峰值(adaptive density peaks clustering,ADPC)聚类的低压台区拓扑识别方法。该方法利用动态时间弯曲(dynamic time warping,DTW)距离度量低压台区用户间电压序列的相似性,通过AKNN异常检验算法检验并校正异常的用户与变压器之间的关系(简称“户变关系”),在得到正确户变关系的基础上,采用ADPC聚类算法对台区内用户进行相位识别;最后,通过实际台区算例分析验证了该方法不需要人为设置参数,能有效实现低压台区的拓扑识别,具有较高的适用性与准确性。展开更多
The single-line-to-ground faults with line breaks(SLGFs-LBs)occur more and more frequently in distribution networks and can cause major safety accidents.It is difficult to distinguish the single-line-to-ground faults(...The single-line-to-ground faults with line breaks(SLGFs-LBs)occur more and more frequently in distribution networks and can cause major safety accidents.It is difficult to distinguish the single-line-to-ground faults(SLGFs)in resonant grounding systems and ungrounding systems due to the same electrical characteristics on the source side and uncertain operation conditions of distribution networks.This paper proposes a method for distinguishing SLGFs-LBs and SLGFs.First,the source-side and load-side voltage characteristics of SLGFs and SLGFs-LBs are analyzed,and the phase difference between the voltages of the fault phase and non-fault phase on the load side is selected as the identification criterion.Phasor measurement units(PMUs)are selected as measuring devices.Then,the effects of operation conditions and external devices in distribution networks on the proposed method are discussed,and the phase errors caused by them are calculated to correct the identification method.Finally,the field testing and simulation experiments are conducted to verify the effectiveness and robustness of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61371049
文摘The soft fault induced by parameter variation is one of the most challenging problems in the domain of fault diagnosis for analog circuits.A new fault location and parameter prediction approach for soft-faults diagnosis in analog circuits is presented in this paper.The proposed method extracts the original signals from the output terminals of the circuits under test(CUT) by a data acquisition board.Firstly,the phase deviation value between fault-free and faulty conditions is obtained by fitting the sampling sequence with a sine curve.Secondly,the sampling sequence is organized into a square matrix and the spectral radius of this matrix is obtained.Thirdly,the smallest error of the spectral radius and the corresponding component value are obtained through comparing the spectral radius and phase deviation value with the trend curves of them,respectively,which are calculated from the simulation data.Finally,the fault location is completed by using the smallest error,and the corresponding component value is the parameter identification result.Both simulated and experimental results show the effectiveness of the proposed approach.It is particularly suitable for the fault location and parameter identification for analog integrated circuits.
文摘低压台区拓扑信息的准确记录是进行台区线损分析、三相不平衡治理等工作的基础。针对目前拓扑档案排查成本高且效率低的问题,提出一种基于自适应k近邻(adaptive k nearest neighbor,AKNN)异常检验和自适应密度峰值(adaptive density peaks clustering,ADPC)聚类的低压台区拓扑识别方法。该方法利用动态时间弯曲(dynamic time warping,DTW)距离度量低压台区用户间电压序列的相似性,通过AKNN异常检验算法检验并校正异常的用户与变压器之间的关系(简称“户变关系”),在得到正确户变关系的基础上,采用ADPC聚类算法对台区内用户进行相位识别;最后,通过实际台区算例分析验证了该方法不需要人为设置参数,能有效实现低压台区的拓扑识别,具有较高的适用性与准确性。
基金supported in part by National Science Foundation of China(No.51707117)。
文摘The single-line-to-ground faults with line breaks(SLGFs-LBs)occur more and more frequently in distribution networks and can cause major safety accidents.It is difficult to distinguish the single-line-to-ground faults(SLGFs)in resonant grounding systems and ungrounding systems due to the same electrical characteristics on the source side and uncertain operation conditions of distribution networks.This paper proposes a method for distinguishing SLGFs-LBs and SLGFs.First,the source-side and load-side voltage characteristics of SLGFs and SLGFs-LBs are analyzed,and the phase difference between the voltages of the fault phase and non-fault phase on the load side is selected as the identification criterion.Phasor measurement units(PMUs)are selected as measuring devices.Then,the effects of operation conditions and external devices in distribution networks on the proposed method are discussed,and the phase errors caused by them are calculated to correct the identification method.Finally,the field testing and simulation experiments are conducted to verify the effectiveness and robustness of the proposed method.