Investigation on Fault Characteristics and Intelligent Diagnosis of a DC Superconducting Fault Current Limiter

Yaxiong Tan, Jiajun Pan, Chao Sheng, Leishi Xiao, Quan Zhou, Jian Li
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Abstract

The fault characteristics of superconducting fault current limiter (SFCL) are dynamic and nonlinear, which makes it difficult to recognize the failure state accurately. In this paper, the fault characteristics of a DCSFCL were investigated and an intelligent diagnostic method was proposed. We present mathematical formulations and a simulation model with COMSOL for transient analysis of DC power systems. The model consists of non-inductive superconducting coils, liquid nitrogen vessel. The value variation regularities of temperature, pressure and liquid level under different fault states were studied. In addition, kriging interpolation method was applied to solve convergence problem during thermal calculating. The correlations between characteristic parameters and operating status were analyzed. Framework for fault diagnosis of SFCL based on fault tree model was established and identification of the fault is carried out by comparison of obtained operating parameters with preset values. The results show that the fault type was determined by fault tree analysis. Moreover, the seriousness of fault is affected by the fault characteristic quantities, which provides an early warning of faults and benefit the condition-based maintenance.
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直流超导故障限流器故障特征及智能诊断研究
超导故障限流器(SFCL)的故障特征是动态的、非线性的,这给准确识别故障状态带来了困难。研究了DCSFCL的故障特征,提出了一种智能诊断方法。本文给出了直流电力系统暂态分析的数学公式和COMSOL仿真模型。该模型由无感超导线圈、液氮容器组成。研究了不同故障状态下温度、压力和液位的数值变化规律。此外,采用kriging插值方法解决了热计算过程中的收敛问题。分析了特征参数与运行状态的相关性。建立了基于故障树模型的SFCL故障诊断框架,将得到的运行参数与预设值进行比较,进行故障识别。结果表明,通过故障树分析可以确定故障类型。此外,故障特征量还会影响故障的严重程度,为故障预警和状态维护提供依据。
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