某型涡扇发动机测量数据融合模型

为提高传感器测量数据的有效性、可信性,基于共同工作方程,采用原始对偶内点法对某型涡扇发动机测量数据进行了融合分析。通过案例研究了当可测量参数存在误差时融合模型对流量、温度及压力等参数的预测效果;使用两种初值更新法,测试了不同工况下的物理运算时间;研究了约束违反程度对数据融合效果的影响;测试了关键传感器失效情况下,动态数据融合模型对缺失参数的预测效果,提出了进一步加快计算速度的方法。结果表明:通过数据融合,测量数据和未测量参数的不确定度下降到1%以内;通过算法优化,运算时间减小到5s,为发动机状态监控、传感器维护和传感器失效情况下发动机控制策略的制定提供了支持。

Measured data reconciliation model for a certain type of turbofan engine

To improve the validity and reliability of the measured data, primal-dual interior point method was used to reconcile the measured data for a certain type of turbofan engine based on cooperative working equations. The performance of the model on reconciling mass flow rate, temperature and pressure was stidoed bu case when measured data had errors. The physical computation time was also tested using two starting value update methods under various flight conditions. The influence of constraint violation threshold on the precision of data reconciliation was studied. The predictive effect of dynamic data reconciliation on missing parameters was tested, and an approach to make further improvement of computation speed was proposed. Results showed that the uncertainties of measured and unmeasured data could be reduced to less than 1%, meanwhile, the processing time could also be reduced to 5s, providing a support for aero-engine state monitoring, sensor maintenance and generation of aero-engine control strategy in case of sensor failures.