Statistical modeling of fiber optic current transducer

Abstract Fiber optic current transducer (FOCT) is a new type of current measurement instrument with high accuracy, large dynamic range, wide frequency range and excellent insulating property. Thus, it has been highly concerned for using in high voltage grid. Although these FOCTs have such crucial advantages, the stochastic errors, mainly including random walk, bias instability, quantization noise, may suddenly degrade the system performance in a short period of time. To evaluate the stochastic error characteristics of fiber optic current transducer (FOCT), traditional solution adopts Allan variance method to plot the curve on the log–log scale. Considering the deficiency of severe shock in Allan variance, total variance methodology is proposed to analyze the stochastic error characteristics of FOCT with the aim of overcoming the deficiency. Total variance method transforms time-offset data to frequency-offset data and extends the data to be a virtual sequence nearly as three times long as the initial data by mapping. Additionally, the least square fitting (LSF) is applied to identify and obtain each coefficient of FOCT stochastic error, which helps to evaluate the stochastic error characteristics of FOCT excellently. Simulation results demonstrate that both Allan variance result and total variance result are nearly equivalent, when correlation time is short. However, when correlation time exceeds half total duration of the measurement, Allan variance estimation values tend to shock increasingly severely and total variance curve always extends steadily. Besides, every stochastic error coefficient is decreased effectively by total variance method, comparing with Allan variance method. Total variance methodology overcomes the deficiency of severe shock in Allan variance successfully, and then optimizes evaluation method of FOCT stochastic error characteristics.