A Multilayered and Multifactorial Health Assessment Method for Launch Vehicle Engine under Vibration Conditions

Sixty percent of the failures launch vehicles in ascending phase occur propulsion system. Among them, vibration generated by engine is an important factor occurrence failure. At present, health assessment methods aerospace field are mostly for specific equipment, and scholars assess real-time status vehicle engines which can only reflect current vehicle. Existing cannot be applied to different there a lack research on assessments fuzzy complex mechanical systems. In this article, we propose multi-layer multi-factor predictive evaluation method system conduct experiments real data rockets. First, divide level according that affect normal operation rocket. Secondly, obtain future trend signals based five prediction calculate interval rocket engine’s working conditions boxplot method. same time, single set every signal. We weights each value analytic hierarchy process (AHP). The optimization step avoids over-reliance expert experience. Finally, complete comprehensive from bottom up final value. minimum error 0.0193% test Long March series engine, shows proposed successfully predict evaluate engine.