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一种基于弱化算子改进的灰色模型故障预测方法

An Improved Grey Model Fault Prediction Method Based on Weakening Operator

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针对航空装备故障预测需求,在对灰色GM(1,1)基本模型分析研究的基础上,通过引入弱化算子对该故障预测模型进行改进,并以某直升机滑油温度控制盒峰值电压数据为对象进行应用分析,结果表明弱化算子改进模型可降低故障预测误差、提高预测精度;同时,将基于弱化算子改进模型的算法分别与序列平均变化率算子、新陈代谢模型两种算法进行组合,也验证了基于弱化算子改进模型可以提高预测精度,这对提高航空装备故障预判与维修保障能力具有重要参考借鉴价值.
In order to solve the aviation equipment fault prediction program,based on the analysis of the basic GM(1,1)model,the weakening operator is introduced to improve the fault prediction model.As an application example,a helicopter oil temperature control box's peak voltage data has been analyse by the improved fault prediction model.The results show that the improved model of grey weakening operator can reduce the fault prediction error and improve the prediction accuracy.Also the paper give two combi-natorial algorithms,one is the weakening operator combined with the the average change rate of the se-quence,the other is the weakening operator combined with the metabolism model,all of them proved the weakening operator can improve the prediction accuracy.It has important reference value for improving the fault prediction and maintenance support ability of aviation equipment.

Grey modelWeakening operatorFault predictionGM(1,1)

丛晓、陈勇、薛鲁强、张光轶

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山东商务职业学院智能制造学院,山东烟台 264003

海军装备部,北京 100067

烟台理工学院人工智能学院,山东烟台 264003

灰色模型 弱化算子 故障预测 GM(1,1)

2024

中国电子科学研究院学报
中国电子科学研究院

中国电子科学研究院学报

影响因子:0.663
ISSN:1673-5692
年,卷(期):2024.19(1)
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