NSWCPD Advances AI for Predictive Maintenance in Naval Machinery
NSWCPD is developing machine learning models for predictive maintenance of high-pressure air compressors, crucial for submarine operations. This initiative is part of the Navy's Condition-Based Maintenance Plus program, aiming to enhance equipment reliability and operational efficiency.
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The Naval Surface Warfare Center, Philadelphia Division (NSWCPD) is testing machine learning algorithms to predict failures in high-pressure air compressors, essential for submarine operations. This project is part of the Navy's Condition-Based Maintenance Plus (CBM+) initiative, which seeks to combine traditional maintenance with AI-driven prognostics to estimate equipment failure timelines.
Engineers have constructed a dedicated test loop to simulate faults and analyze vibration data, identifying key indicators of common failures. The current focus is on developing localized AI processing capabilities due to bandwidth limitations in underwater environments. Future goals include extending these predictive technologies to unmanned systems, enhancing operational readiness and maintenance efficiency across the fleet.
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