电力电子电路故障诊断方法仿真

Power Electronic Circuit Fault Diagnosis Methods Simulation

研究电力电子电路故障准确诊断问题。一般的电力电子电路中的电子器件工作在与电力相关的高压环境下,负载能力小,损坏速度快,故障发生前征兆极难捕获。传统的根据频率进行故障诊断的方法只能依靠输出波形判断缓变故障,对电力电子快速、突变性故障很难识别。为了准确识别故障,提出了一种粒子群优化算法的电力电子电路故障诊断方法。对粒子群中的所有粒子的速度和空间位置进行更新处理,从而为电力电子电路故障诊断提供准确的数据基础。利用粒子群优化方法,对所有粒子进行迭代运算,从而判断电力电子电路的器件是否存在故障。实验结果表明,利用改进算法进行电力电子电路故障诊断,能够有效提高故障诊断的准确性,取得了理想的效果。

This paper proposed a particle swarm optimization algorithm based on the power electronic circuit fault diagnosis methods. To particle swarm of all the particle＇s velocities and space positions, the update processing was carried out, thus for power electronic circuit fault diagnosis to provide accurate data base. Using particle swarm optimization method for all particles iterative operation, thus power electronic circuit devices were judged for whether there is faults. The experimental results show that this algorithm can effectively improve the accuracy of fault diagnosis, and the result is satisfactory.