Fault Diagnosis Based on Hybrid State Estimation
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摘要: 如果将故障的发生视为一个离散事件,则存在故障可能的系统可以看作随机混合系 统,那么故障诊断问题就可转化为混合系统的离散状态估计问题.文中试图从这个角度研究 在非高斯噪声环境下非线性系统的故障诊断问题.在发生故障后的系统模型是已知的假定条 件下,使用随机混合自动机对系统建模,并利用基于粒子滤波的混合估计算法估计出混合状 态,从而完成故障诊断.仿真结果表明,所提的方法是可行的,可以处理某类故障诊断.Abstract: If a fault's occurrence is thought of as a discrete event. the system suffered from faults could be regarded as a stochastic hybrid system. So fault diagnosis is transformed into the discrete states estimation problem for such a stochastic hybrid system. Fault diagnosis problem of nonlinear system in arbitrary noise environment is studied with this point of view. If assumed that models after faults' occurrence are known, the system subject to these faults can be modeled with a stochastic hybrid automaton. Then hybrid states in such a stochastic hybrid system are estimated by particle filtering-based algorithm. Consequently, fault diagnosis task is accomplished. The feasibility of proposed approach is shown by simulation results, and it is suitable in diagnosing some type faults.
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Key words:
- Fault diagnosis /
- hybrid system /
- particle filtering /
- stochastic hybrid automaton
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