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Adaptive Multivariable Grey Prediction Model

机译:自适应多变量灰色预测模型

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摘要

The fault prediction of weapon equipments is getting more difficult for its complex structure, unique operating environment and multi-source faults. Currently although the main fault prediction methods have achieved certain success in practical application, they all fall short in some aspects. Based on the grey prediction modeling theory and with an analysis of the shortages of GM(1,1) model, an adaptive multivariable grey prediction model is proposed, which reconstructs whitening background values and initial conditions in view of the relationship among many related reduction feature informations. The datas of a certain aeroengine are taken as an example for prediction and analysis, and the results show that the model is high practicability and precision.
机译:武器装备的结构复杂,运行环境独特,多源故障,对装备的故障预测越来越困难。目前,尽管主要的故障预测方法在实际应用中已经取得了一定的成功,但在某些方面都存在不足。基于灰色预测建模理论,并分析了GM(1,1)模型的不足,提出了一种自适应多变量灰色预测模型,该模型根据许多相关的还原特征之间的关系,重建了白化背景值和初始条件。信息。以某航空发动机的数据为例进行了预测和分析,结果表明该模型具有较高的实用性和准确性。

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