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针对粒子滤波算法在故障预报中的大计算量和粒子退化问题,提出一种基于随机摄动粒子滤波器的故障预报算法.当粒子退化严重时,对粒子用随机摄动方式进行再采样,一方面可改进样本的多样性,缓解粒子退化;另一方面可缩短再采样时间,减少计算量,从而提高粒子滤波算法的跟踪能力.仿真结果表明该算法可行,能及时准确地对系统故障进行预报.
Aiming at the large computational cost and particle degeneration problem of particle filter in fault prediction, a fault prediction algorithm based on stochastic perturbation particle filter is proposed. When the particle degenerates seriously, the particle is resampled by stochastic perturbation method. On the other hand, it can shorten the time of resampling and reduce the computational complexity, so as to improve the tracking ability of the particle filter algorithm.The simulation results show that the algorithm is feasible and can timely and accurately predict system faults .