This paper describes the Distributed Health Monitoring System for Reusable Liquid Rocket Engines, consisting of a flexible, modular, and distributed architecture with embedded processing at multiple levels, and serving as a platform for real-time failure detection and identification (FDI). The utilization of a multi-level framework has been motivated by the computational requirements in providing an integrated awareness of the condition of every element of interest for complex systems such as reusable liquid rocket engines. In particular, there is a need at NASA Stennis Space Center for solutions that determine anomalies, examine their causes, and make predictive statements. The foundation of the architecture is a network of Advanced Embedded Smart Sensors with intelligent functions for performing self-diagnostics, self-healing, and self-calibration. On the other hand, at the highest level is a man machine interface for providing health monitoring access and control as well as maintenance actions. Within this framework, a comprehensive approach to FDI exists that is based on optimized neural networks with fast learning capable of on-line real-time health monitoring. Another key attribute of the system includes an IEEE 1451.x environment for compatibility with NASA's Integrated System Health Management platforms. Copyright © 2010 by Ching-Fang Lin, Fernando Figueroa, Tasso Politopoulos, and Stephen Oonk.