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Remaining useful life prognostics of aircraft engine based on fusion algorithm

机译:基于融合算法的飞机发动机剩余使用寿命预测

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Prognostics on remaining useful life is a difficult technical challenge in aircraft engine health management. The paper introduces the principle of HSMM, similarity-based, and SVM algorithm, and their detailed structure and method applied to the prognostics. Apply these three algorithms to C-MAPSS data released by NASA and get the life prognostics result correspondingly, then fuse these results by average fusion and comentropy fusion. Compare and evaluate the consequence among the result of these three single algorithm and the fusion algorithm, finally summarize the characteristic and the usable range of each algorithm.
机译:剩余使用寿命的预测是飞机发动机健康管理中的一项艰巨的技术挑战。本文介绍了HSMM,基于相似度和支持向量机算法的原理,以及它们的详细结构和方法在预测中的应用。将这三种算法应用于美国宇航局发布的C-MAPSS数据,并相应地获得生命预测结果,然后通过平均融合和联合皮层融合将这些结果融合在一起。在这三种算法和融合算法的结果之间进行比较和评估,最后总结出每种算法的特点和适用范围。

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