Date of Award
Doctor of Philosophy (PhD)
Department of Systems Engineering and Management
David R. Jacques, PhD.
Structural Health Monitoring (SHM) systems face many obstacles and gaps that have resulted in the slow implementation in real-world applications. These obstacles include technology performance, implementation issues and a solid business case that justifies the investment in a SHM system. The presentation of a solid business case for the SHM system is a great challenge and arguably is the main factor contributing to the slow implementation of this technology. The research intent of this dissertation is to focus on the business case by providing a tool to aid decision makers. Simulated aging aircraft flight data are used in this effort due to the fact that many aging military aircraft will be flying beyond their initially intended design life. An analytical model was developed to address the business case and the integration of the SHM system into Condition Based Maintenance (CBM). The model aids the calculation of the cost of Life Cycle (LC) events resulting from the implementation of the SHM system on an aging aircraft. In addition, the model captures the events and effect on aircraft availability due to different SHM detection threshold settings and replacement of degraded sensors. The model captures false alarm rates, crack growth, probability of detection, and sensor degradation amongst other parameters. The proposed analytical model is a useful tool that provides the decision makers the confidence to either implement the SHM system on an aging military aircraft or not. Two models were developed; one was the SHM system model with no degradation and the second was the SHM system model with simulated degrading sensors. Three major subcomponents of the SHM model will be the sensor detection component, the crack growth component and the sensor degradation component (second model only).
DTIC Accession Number
Albinali, Salman A., "Structural Health Monitoring System Trade Space Analysis Tool with Consideration for Crack Growth, Sensor Degradation and a Variable Detection Threshold" (2014). Theses and Dissertations. 554.