4.6 Review

Advances in Integrated System Health Management for mission-essential and safety-critical aerospace applications

Journal

PROGRESS IN AEROSPACE SCIENCES
Volume 128, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.paerosci.2021.100758

Keywords

Avionics; Integrated system health management; Prognostics; Diagnostics; Health and usage monitoring systems; Artificial intelligence; Machine learning; Intelligent health and mission management; Unmanned aircraft system; UAS; Satellite systems; UAS Traffic management; UTM; Distributed satellite systems

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Integrated System Health Management (ISHM) utilizes sensor data and historical health information to make intelligent decisions regarding aerospace systems, focusing on health assessment, early failure detection, and maximizing diagnosis and prognosis reliability through AI techniques. ISHM enhances system performance, safety, and reliability, while also optimizing maintenance through predictive capabilities.
Integrated System Health Management (ISHM) is a promising technology that fuses sensor data and historical state-of-health information of components and subsystems to provide actionable information and enable intelligent decision-making regarding the operation and maintenance of aerospace systems. ISHM fundamentally relies on assessments and predictions of system health, including the early detection of failures and estimation of Remaining Useful Life (RUL). Model-based, data-driven or hybrid reasoning techniques can be utilized to maximise the timeliness and reliability of diagnosis and prognosis information. The benefits of ISHM include enhancing the maintainability, reliability, safety and performance of systems. The next evolution of the ISHM concept, Intelligent Health and Mission Management (IHMM), delves deeper into the utilization of on-line system health predictions to modify mission profiles to ensure safety and reliability, as well as efficiency through predictive integrity. This concept is particularly important for Trusted Autonomous System (TAS) applications, where an accurate assessment of the current and future system state-of-health to make operational decisions (with or without human intervention) is integral to both flight safety and mission success. IHMM systems introduce the capability of predicting degradation in the functional performance of subsystems, with sufficient time to dynamically identify which appropriate restorative or reconfiguration actions to take in order to ensure that the system can perform at an acceptable level of operational capability before the onset of a failure event. This paper reviews some of the key advancements and contributions to knowledge in the field of ISHM for the aerospace industry, with a particular focus on various architectures and reasoning strategies involving the use of artificial intelligence. The paper also discusses the key challenges faced in the development and deployment of ISHM systems in the aerospace industry and highlights the safety-critical role that IHMM will play in future cyber-physical and autonomous system applications (both vehicle and ground support systems), such as Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Urban Air Mobility (UAM) and Distributed Satellite Systems (DSS).

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