Leak Detection and Localization in Pressurized Space Structures Using Bayesian Inference: Theory and Practice

Impact from micrometeoroids and orbital debris (MMOD) can cause severe damage to space vehicles. The crew habitat can begin to leak precious oxygen, critical systems can be punctured causing fatal failures, and an accumulation of impacts by MMOD can decrease the lifetime of any and all devices in space. Due to these and other potential dangers, MMODs have been considered the third largest threat to spacecraft after launch and re-entry. Many satellites and other spacecraft face this very problem inherent in all space travel on a daily basis, but often times they can be repaired. A major hurdle is to first be able to identify the presence of a leak. Many times an impact and subsequent leak is not discovered until it has caused a problem. A complete system is needed to detect and localize the impact to improve longevity of the habitat or other pressurized space structures. In this work, a system for detection and localization of air leaks using air-borne acoustic waves is proposed. The system uses microelectromechanical systems (MEMS) microphone sensors to detect and record high frequency noise in an environment, angle of arrival (AOA) calculations to estimate possible leak locations, and a Bayesian tree-search filter to detect and more accurately localize a leak. This work includes proof of concept, simulations, and physical prototypes as steps to creation of a complete system. Data from deployed flight test using said prototypes are analyzed. Modeling the effects of environmental reflections on the accuracy of localization is also studied