SansEC Wireless Strain Sensor for Softgood Habitats and Inflatable Space Structures

A primary concern for astronauts living in inflatable softgood structures during long duration missions is the restraint strap’s steady creep while under load which could lead to catastrophic failure. To ensure astronaut safety, a mitigation method is needed to monitor the strap’s strain to know when safety margins are being breached. This report summarizes an investigation to use SansEC sensor data incorporated with machine learning to predict the strap’s strain while under load conditions to provide diagnostic and prognostic monitoring of the strap’s integrity. SansEC sensor measurements were collected on a 12,500-pound rated Vectran strap to infer axial strain while it was loaded repeatedly between 5000- and 8000-pound loads. DIC measurements were simultaneously collected to provide true strain values to coincide with the SansEC response. Three industry partners (ResCon Technologies, VOLT AI, and Sierra Turbines) participated in this study to develop machine learning models to predict axial strain based on the SansEC measurements. All three partners successfully modeled the strap behavior and achieved an R² above 0.97. This study has shown that SansEC sensors are able to measure strain on the Vectran strap and should be considered a candidate sensor to provide structural health diagnostic and prognostic monitoring for inflatable habitats.