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针对目前航空发动机的剩余寿命预测研究没有综合考虑非线性与多阶段的问题,提出了基于多阶段非线性维纳过程的航空发动机实时剩余寿命预测的方法。该方法融合了同类型发动机的历史性能退化监测数据与个体发动机的实时监测数据。首先考虑了发动机性能退化非线性的特点,并采用多阶段维纳过程建立航空发动机的性能退化模型。然后,根据发动机的历史性能监测数据,利用极大似然估计和一维搜索方法进行参数先验分布的估计。其次,根据监测的个体发动机实时性能退化数据,运用Bayes方法对模型参数进行更新。最后,得到个体发动机剩余寿命的实时预测值。通过实例验算,与传统的基于单阶段线性Wiener过程的剩余寿命预测进行对比,结果表明该方法预测结果更准确。
Aiming at the problem that the remaining life prediction of aeroengine is not comprehensively considering the problem of nonlinearity and multi-stage, a method of real-time residual life prediction of aeroengine based on multi-stage nonlinear Wiener process is proposed. The method combines the historical performance degradation monitoring data of the same type of engine and the real-time monitoring data of the individual engine. Firstly, the non-linearity of engine performance degradation was considered, and a multi-stage Wiener process was used to establish the performance degradation model of aeroengine. Then, based on the historical performance monitoring data of the engine, the estimation of the prior distribution of the parameters is performed by using the maximum likelihood estimation and the one-dimensional search method. Secondly, based on the monitored real-time engine performance degradation data, Bayes method is used to update the model parameters. Finally, the real-time prediction of the remaining life of the individual engine is obtained. Comparing with the traditional residual life prediction based on the single-stage linear Wiener process, the results show that the method is more accurate.