Bladecare Platform
Know the Life of Every Blade — Before It Fails.
Bladecare turns operating data, physics models and AI into quantified remaining life and early damage alerts for turbine blades and vanes. Move from run-to-limit to predictive maintenance.
Platform Core
One Platform. Three Insights.
Physics-based & data-driven hybrid model delivering actionable intelligence for turbine life management.
Physics-Based Data-Driven Hybrid Model
Combining first-principles physics models with machine learning to deliver accurate, interpretable life predictions under real operating conditions.
Remaining Useful Life
Quantified RUL estimates for turbine blades and vanes, enabling planned maintenance instead of reactive replacement.
Early Damage Prediction
Detect incipient damage patterns before they escalate — from micro-cracks to coating spallation — with actionable lead time.
Capabilities
Core Functions
Eight integrated monitoring and analysis capabilities covering the full spectrum of turbine blade life management.
Real-Time Monitoring
Continuous tracking of operating parameters and environmental conditions across the turbine fleet.
Subsystem Health
Holistic health assessment of each turbine subsystem, identifying degradation trends early.
Damage Accumulation
Track cumulative damage over each component's service life using physics-based damage models.
Life Consumption History
Complete historical record of life consumption for every tracked component, fully auditable.
Critical Locations
Pinpoint high-stress zones and thermal gradients where damage initiates and propagates.
Anomaly History
Log and correlate past anomalies with operating events to build predictive failure patterns.
Circumferential Uneven Damage Monitoring
Detect and quantify circumferential damage variation around the blade ring for targeted intervention.
Creep and Fatigue Damage Breakdowns
Detailed decomposition of creep (partial load, full load, overload) and fatigue (normal start-stop, fast start, load fluctuation, trip) damage mechanisms.