航空发动机单元体送修等级决策方法研究

摘要

为对发动机单元体送修等级提供决策支持,在对状态参数与单元体送修等级间的模糊关系进行特征提取的基础上,从性能衰退角度提出通过状态参数组合变化确定单元体送修等级的决策方法.针对现有的数据规则有限的问题,建立模糊综合评价模型,采用BP神经网络训练各参数对不同送修等级的隶属函数,采用熵权法衡量状态参数在单元体送修等级确定中的权重.最后以高压涡轮单元体送修的仿真结果证明了该决策方法的有效性,能够为更多状态参数组合提供一种便捷高效确定送修等级的方法.%A decision-making method of maintenance level from the view point of performance degradation for aeroengine module is proposed to support the determination on maintenance level for the aeroengine module based on feature extraction of fuzzy relation between state parameter and module maintenance level.To solve the problem of limited existing data rules,a mathematical model of fuzzy comprehensive evaluation is established.The back propagation (BP) neural network is built to train the membership function of each parameter for different maintenance level.The entropy weight method is adopted to measure the weight of the state parameter in decisionmaking.Finally,the computer simulation result of the high-pressure turbine module verify that the proposed decision-making method is effective and capable of providing a efficient method for making maintenance level decision for the case with more state parameter combinations.