TY - JOUR
T1 - An adaptive fault detection method based on atom sparse and evidence fusion for the small current to ground system
AU - Wang, Xiaowei
AU - Wei, Xiangxiang
AU - Yang, Dechang
AU - Gao, Jie
AU - Sun, Xue
AU - Song, Guobing
N1 - Publisher Copyright:
© 2018, © The Author(s) 2018.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - An adaptive fault detection method for the small current to ground system is proposed based on the atom sparse and evidence fusion theory. Firstly, the two cycles of transient zero-sequence current are obtained when occur fault, which is decomposed by the matching pursuit algorithm, and the iterations are set to four, then, according to the correlation analysis, the best three atoms of maximum correlation are chosen and which are sorted by the correlation coefficients. Secondly, we obtained the determine fault measure (DFM) values by calculating the atomic energy entropy, and selected the atomic fault trust (FT) function by revising the DFM. Finally, the FT values are integrated by the D-S (Dempster–Shafer) evidence theory, then the fault comprehensive trust values are gained, the selection results are output. Simulation results show that the method of fault line detection is accurate and reliable.
AB - An adaptive fault detection method for the small current to ground system is proposed based on the atom sparse and evidence fusion theory. Firstly, the two cycles of transient zero-sequence current are obtained when occur fault, which is decomposed by the matching pursuit algorithm, and the iterations are set to four, then, according to the correlation analysis, the best three atoms of maximum correlation are chosen and which are sorted by the correlation coefficients. Secondly, we obtained the determine fault measure (DFM) values by calculating the atomic energy entropy, and selected the atomic fault trust (FT) function by revising the DFM. Finally, the FT values are integrated by the D-S (Dempster–Shafer) evidence theory, then the fault comprehensive trust values are gained, the selection results are output. Simulation results show that the method of fault line detection is accurate and reliable.
KW - D-S evidence theory
KW - Fault detection
KW - correlation analysis
KW - energy entropy
KW - fault trust function
KW - matching pursuit algorithm
UR - https://www.scopus.com/pages/publications/85044047451
U2 - 10.1177/0142331216686402
DO - 10.1177/0142331216686402
M3 - 文章
AN - SCOPUS:85044047451
SN - 0142-3312
VL - 40
SP - 1579
EP - 1592
JO - Transactions of the Institute of Measurement and Control
JF - Transactions of the Institute of Measurement and Control
IS - 5
ER -