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Linked challenge: Autonomous Predictive Maintenance Agent for Hypersonic Propulsion Systems

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Linked challenge

Autonomous Predictive Maintenance Agent for Hypersonic Propulsion Systems

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Initialize a Mastra AI project using Claude 4 Opus. Define an agent called 'EngineHealthAgent' that has access to a tool for calculating moving averages on telemetry data and a RAG tool for propulsion manuals. Show the imports and the agent initialization block.

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Linked challenge

Autonomous Predictive Maintenance Agent for Hypersonic Propulsion Systems

Inspired by Venus Aerospace's scaling of rocket engine technology and Rolls-Royce's UltraFan developments, this challenge focuses on building a sophisticated diagnostic agent. You will develop a system capable of ingesting high-frequency telemetry from a hypersonic rocket engine (RDRE) and identifying pre-failure signatures before they escalate into catastrophic anomalies. The agent must process multi-modal data including pressure transients, thermal gradients, and vibration acoustics. Using the Mastra AI framework, you will orchestrate a workflow that combines real-time sensor analysis with a RAG-enhanced diagnostic engine. The engine will query technical specifications and historical failure logs to provide actionable maintenance recommendations. The system must handle the 'Physics of Failure' by integrating a simplified structural health model with the LLM's reasoning capabilities to ensure recommendations align with aerospace safety standards.

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