Integration of Remote Sensing and Risk Analysis for Airframe Structural Integrity Assessment



D. Cope J. Cronenberger K. Kozak K. Schrader L. Smith C. Thwing


Southwest Research Institute (SwRI) investigated the feasibility of integrating remote sensing technology with probability of failure analyses into a monitoring system capable of assessing the structural integrity of critical airframe components. The project demonstrated the viability of remote sensing to discern structural flaw growth along with the integration of sensor data with crack growth analyses in order to assess the health and integrity of a critical structural component. The demonstration was performed on a complicated aircraft structural component that has limited accessibility with realistic loading. The technical approach employed for developing the structural health monitoring system included (1) detailed stress analyses of a critical structural component, (2) crack growth analyses to predict the structural component’s fatigue life, (3) a damage sensor system to monitor the structural components and capture degradation mechanisms during fatigue testing, (4) reasoning algorithms to integrate damage sensor data with crack growth analyses in order to assess the current structural health and integrity of the component, and (5) predictions of the component’s structural capability and remaining useful life on a periodic basis. Researchers used Bayesian principles to estimate flaw sizes based on both sensor readings and crack growth analyses, which were then used for periodic structural health and integrity assessments. Results validated how fatigue life predictions and probability of failure assessments can be improved with more accurate estimates of actual flaw sizes and continual structural health monitoring.

How to Cite

Cope, D. ., Cronenberger, J. ., Kozak, K. ., Schrader, K., Smith, L. ., & Thwing, C. . (2010). Integration of Remote Sensing and Risk Analysis for Airframe Structural Integrity Assessment. Annual Conference of the PHM Society, 2(1).
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damage detection, damage propagation model, materials damage prognostics, model based diagnostics, probability of failure, risk assessment, sensor validation, applications: aviation, Structural Integrity

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