基于健康退化曲线对军用飞机故障预测与健康管理(PHM)技术的内涵、基本功能和能力需求进行探讨,在此基础上,以科学评价PHM(prognostics and health management)系统的诊断和预测能力为目标,从能力需求出发提出PHM系统性能度量方法体系(包括诊断性能度量、预测性能度量以及综合度量),并对各个度量方法的定义和应用进行详细阐述。为PHM系统算法设计、改进及系统能力验证奠定基础,具有一定的工程应用价值。
Research on practical and verifiable prediction methods for the service life of bearings plays a critical role in improving the reliability and safety of aircraft engines. The concept of grade-life （GL） is introduced to de- scribe the service life of bearings. A GL prognostic model for aircraft engine bearings is proposed based on sup- port vector machine （SVM） and fuzzy logic inference. Firstly, the mathematical model is discussed to predict the physics-based GL （PGL）. Then, the diagnostic estimation model based on SVM is presented in detail to predict the empirical GL （EPL）. Thirdly, a fuzzy logic inference is adopted to fuse two GL predicted results. Finally, the GL prognostic model is verified by the run-to-failure data acquired from an accelerated life test of an aircraft bearing. The results show that the model provides a more practical and reliable prediction for the service life of bearings.
