TY - JOUR
T1 - Advances in Integrated System Health Management for mission-essential and safety-critical aerospace applications
AU - Ranasinghe, Kavindu
AU - Sabatini, Roberto
AU - Gardi, Alessandro
AU - Bijjahalli, Suraj
AU - Kapoor, Rohan
AU - Fahey, Thomas
AU - Thangavel, Kathiravan
N1 - Publisher Copyright:
© 2021 The Authors
PY - 2022/1/1
Y1 - 2022/1/1
N2 - 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).
AB - 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).
KW - Artificial intelligence
KW - Avionics
KW - Diagnostics
KW - Distributed satellite systems
KW - Health and usage monitoring systems
KW - Integrated system health management
KW - Intelligent health and mission management
KW - Machine learning
KW - Prognostics
KW - Satellite systems
KW - UAS
KW - UAS Traffic management
KW - Unmanned aircraft system
KW - UTM
UR - http://www.scopus.com/inward/record.url?scp=85119255881&partnerID=8YFLogxK
U2 - 10.1016/j.paerosci.2021.100758
DO - 10.1016/j.paerosci.2021.100758
M3 - Review article
AN - SCOPUS:85119255881
SN - 0376-0421
VL - 128
JO - Progress in Aerospace Sciences
JF - Progress in Aerospace Sciences
M1 - 100758
ER -