基于支持向量机的饱和铁心型超导限流器励磁系统传感器故障诊断

In this paper, a fault diagnosis method of SVM about sensors is presented based on the control system model of superconducting fault current limiter(SFCL) with saturated iron core. It is mainly about the state estimation of the bias current of the field system. In this paper, a Support Vector Machine is used to approximate the nonlinear function between ac voltage, ac current of SFCL, ac impedance of SFCL and dc bias current. It works like an inverse model to estimate the dc bias current through the ac current and ac impedance. If the error between estimated value of dc bias current and the sample value of current sensor is beyond some threshold value, it shows a fault occurs on the current sensor. Through simulation, this kind of fault diagnosis method based on SVM is effective.