基于权值选优粒子滤波器的故障预测算法

样本贫化现象会严重影响再采样粒子滤波故障预测算法对故障的预测能力,是粒子滤波算法在故障预测应用中的一个主要障碍。针对上述问题,提出了一种基于权值选优粒子滤波器的故障预测算法。按照粒子权值的大小,从大量的粒子中选择出比较好的粒子用于滤波,以增加样本的多样性,从而缓解样本贫化问题,提高再采样粒子滤波故障预测算法的跟踪能力。仿真结果显示所提出的算法是可行的。

Fault prediction algorithm based on weight selected particle filter

The predicting ability of the fault prediction algorithm based on SIR particle filter will be badly influenced by sample impoverishment,which is one of the main disadvantages for the application of particle filter in fault prediction.A fault prediction algorithm based on weight selected particle filter is proposed to resolve the above problem.According to their weights,the better particles are selected from a vast amount of particles to improve the diversity of samples.As a result,the problem of sample impoverishment is ameliorated and the tracking ability of the fault prediction algorithm based on SIR particle filter is improved.Simulation results demonstrate that the fault prediction algorithm based on weight selected particle filter is feasible.