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基于LMNN的航空发动机维修等级决策
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中央高校基本科研业务费项目(3122016C003)


Maintenance level decisionmaking for aeroengine based on large margin nearest neighbor algorithm
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    摘要:

    针对航空发动机维修等级之间界限模糊、决策准确度较低的问题,提出一种基于大间隔近邻(LMNN)算法和K近邻算法的发动机维修等级决策方法。首先以发动机历史维修数据为基础,通过大间隔近邻算法获取变换矩阵;再利用变换矩阵将发动机监测数据映射到最优的特征空间;最后采用K近邻算法以优化后的数据为训练样本建立决策模型,对发动机下发时的状态进行评估确定其维修等级。采用某型航空发动机的状态参数和维修等级数据验证了该方法的有效性,其决策准确度高于常用的支持向量机模型和神经网络模型。

    Abstract:

    Aiming at the problem of fuzzy boundaries between aeroengine maintenance levels and low accuracy of decisionmaking, a decisionmaking method of engine maintenance levels based on large margin nearest neighbor algorithm and knearest neighbor algorithm is proposed. Firstly, the large margin nearest neighbor(LMNN) algorithm is adopted to obtain the transformation matrix based on the historical maintenance data of the engine. Then, the engine monitoring data is mapped to the optimal feature space by the transformation matrix. Finally, the Knearest neighbor algorithm is utilized to establish the decisionmaking model with the optimized data as the training samples, which determines the maintenance level by the evaluation of the state of the engine before it is removed from the aircraft. The method is verified using the performance parameters and maintenance level data of an aeroengine, and its decision accuracy is higher than the support vector machine model and neural network model which are commonly used.

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彭鸿博,蒋雄伟.基于LMNN的航空发动机维修等级决策[J].机床与液压,2020,48(18):52-58.
Hong-bo PENG, Xiong-wei JIANG. Maintenance level decisionmaking for aeroengine based on large margin nearest neighbor algorithm[J]. Machine Tool & Hydraulics,2020,48(18):52-58

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  • 在线发布日期: 2020-10-15
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