航空发动机滑油消耗率计算与预测方法.

A Calculation and Prediction Method of Lubricating Oil Consumption Rates for Aeroengines.

Since the measurement of oil quantity in aviation engine lubrication systems is susceptible to multiple parameters, it is difficult to calculate and predict oil consumption rates. We propose an improved method for extracting oil quantity data and predicting oil consumption rates. Engine data are cleansed using density-based clustering algorithms, including density based spatial clustering of applications with noise (DBSCAN), to obtain stable oil quantity data during steady flight conditions. By the least squares method, oil consumption rates are derived with an average fitting goodness of 0.86. Subsequently, a multi-layer perception (MLP) is employed to establish the relationship between oil consumption rates and flight status parameters, resulting in a predicted average absolute percentage error of 1.15%, compared to actual values. The proposed method meets practical engineering requirements, providing a reliable reference for assessing the health status of aviation engine lubrication systems. [ABSTRACT FROM AUTHOR]

针对航空发动机滑油箱油量测量值易受多个参数影响导致滑油消耗率难以计算和预测的问题, 提出了一 种改进的滑油量数据提取规则和滑油消耗率预测方法。基于密度聚类算法 (Density‑based spatial clustering of applications with noise, DBSCAN) 等方法对发动机数据进行了清洗，获取平稳飞行状态下滑油量数据。使用最 小二乘法对滑油量进行拟合, 得到了滑油消耗率, 平均拟合优度达到了 0.86。在此基础上, 利用多层感知器 （Multi‑layer perception, MLP）建立了滑油消耗率与飞行状态参数之间的关系, 预测结果与实际值的平均绝对百 分比误差为 1.15%。本文提出的方法能够满足实际工程需求, 为评估航空发动机滑油系统的健康状况提供了可 靠参考。 [ABSTRACT FROM AUTHOR]

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