Against the performance degradation and failure risks that reusable launch
vehicles (RLV) encounter over multiple mission cycles, together with the absence
of a unified quantitative foundation for pre-launch health assessment, fault
diagnosis validation, and remaining useful life (RUL) prediction verification,
this paper presents a health management (HM) indicator system construction and
allocation method tailored for RLV. Consistent with international standards for
health management and test engineering, the method uses a “core capability
decomposition—hierarchical metric mapping” framework to develop a
two-dimensional metric system spanning functional and physical domains. Centered
on fault detection, fault isolation, and fault prognosis, the approach breaks
down top-level HM requirements into concrete technical indicators at the
vehicle, system, and component levels, with explicit definitions, calculation
formulas, and validation approaches to ensure engineering measurability and
comparability. Integrating system criticality analysis and expert judgment, this
work adopts the analytic hierarchy process (AHP) and a weight allocation scheme
to decompose system-level indicators to critical subsystems including propulsion
and flight control systems. A data-driven validation environment is established
using a custom HM prototype and high-fidelity simulation platform.
Multi-scenario simulation and fault injection yield labeled operational data for
computing subsystem-level performance metrics. Comparing bottom-up aggregated
indicators with top-down allocated targets forms a complete engineering closed
loop from indicator allocation to system implementation and performance
verification. Sensitivity analysis confirms that vehicle-level indicators remain
within design thresholds under moderate weight perturbations, demonstrating
robustness. Results show the method is feasible and consistent in simulation,
offering solid support for the design and validation of RLV health management
systems.