Assessing Structural Health Monitoring Alternatives Utilizing a Value-Focused Thinking Model

Current Air Force operations are undergoing significant changes necessitated by increasing fiscal constraints, increasing aircraft age, and recent drawdown in personnel to perform maintenance, repair, and other necessary functions. In order to deal with these challenges, the Air Force must effectively improve current operations. This paper explores potential structural health monitoring (SHM) solutions to some of the challenges facing aircraft maintenance and repair operations. As with any problem, a variety of solutions exist and this paper explores the potential solutions and limitations of various options. Aircraft SHM is an intriguing concept with potential capability to revolutionize current Air Force maintenance operations. However, this capability needs to be balanced with the total life cycle cost associated with training personnel, and with developing, integrating, maintaining, and disposing of the SHM system. This thesis develops and implements a value-focused thinking model as a decision-making tool to analyze several potential solutions to SHM problems

Machine learning requirements for the airworthiness of structural health monitoring systems in aircraft

In the evolving realm of airworthiness and aircraft maintenance task scheduling, the introduction of data-driven Predictive Maintenance (PdM) and Structural Health Monitoring (SHM) has prompted a paradigm shift, which underscores the profound implications of innovative sensing techniques within damage and operational monitoring. Concurrently, the role of avionics in data acquisition and processing has drawn renewed focus, with machine learning (ML) algorithms facilitating pattern recognition, trend analysis, and anomaly detection. This paper discusses the diagnostic sequence in SHM systems, the necessity for damage information, and delves into active and passive sensing techniques within damage and operational monitoring. The role of avionics is also emphasized, especially in data acquisition and processing for operational monitoring. The utilization of ML algorithms for efficient use within SHM is explored, alongside supervised and unsupervised learning methods. The paper underlines how integrating ML in aircraft systems applications can optimize maintenance schedules and lay a solid foundation for SHM integration in aircraft health systems. The study also covers the application of ML techniques for detection, localization, and assessment of structural damage. It reviews research implementations using ML, statistical, and hybrid approaches in monitoring and predicting aircraft damage. The incorporation of non- exclusive ML in SHM to minimize environmental feature uncertainty and enable trackable model behaviour is illustrated. Lastly, the paper discusses evolving regulatory requirements and standards for ML application in aviation SHM, provided by authorities and workgroups like EASA and the SAE G-34 AI in Aviation Committee, respectively, and concludes with an overview of the future trends and standards in this dynamic domain. The aim is to spotlight the transformative potential of PdM and SHM, and their critical roles in boosting the operational efficiency of the aviation industry

Assessment of the State of the Art of Integrated Vehicle Health Management Technologies as Applicable to Damage Conditions

A survey of literature from academia, industry, and other Government agencies assessed the state of the art in current integrated vehicle health management (IVHM) aircraft technologies. These are the technologies that are used for assessing vehicle health at the system and subsystem level. This study reports on how these technologies are employed by major military and commercial platforms for detection, diagnosis, prognosis, and mitigation. Over 200 papers from five conferences from the time period of 2004 to 2009 were reviewed. Over 30 of these IVHM technologies are then mapped into the 17 different adverse event damage conditions identified in a previous study. This study illustrates existing gaps and opportunities for additional research by the NASA IVHM Project

A Concept of Operations for an Integrated Vehicle Health Assurance System

This document describes a Concept of Operations (ConOps) for an Integrated Vehicle Health Assurance System (IVHAS). This ConOps is associated with the Maintain Vehicle Safety (MVS) between Major Inspections Technical Challenge in the Vehicle Systems Safety Technologies (VSST) Project within NASA s Aviation Safety Program. In particular, this document seeks to describe an integrated system concept for vehicle health assurance that integrates ground-based inspection and repair information with in-flight measurement data for airframe, propulsion, and avionics subsystems. The MVS Technical Challenge intends to maintain vehicle safety between major inspections by developing and demonstrating new integrated health management and failure prevention technologies to assure the integrity of vehicle systems between major inspection intervals and maintain vehicle state awareness during flight. The approach provided by this ConOps is intended to help optimize technology selection and development, as well as allow the initial integration and demonstration of these subsystem technologies over the 5 year span of the VSST program, and serve as a guideline for developing IVHAS technologies under the Aviation Safety Program within the next 5 to 15 years. A long-term vision of IVHAS is provided to describe a basic roadmap for more intelligent and autonomous vehicle systems

Aeronautical Engineering: A continuing bibliography, supplement 120

This bibliography contains abstracts for 297 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980

Program of Research in Aeronautics

A prospectus of the educational and research opportunities available at the Joint Institute for Advancement of Flight Sciences, operated at NASA Langley Research Center in conjunction with George Washington University's School of Engineering and Applied Sciences is presented. Requirements of admission to various degree programs are given as well as the course offerings in the areas of acoustics, aeronautics, environmental modelling, materials science, and structures and dynamics. Research facilities for each field of study are described. Presentations and publications (including dissertations and theses) generated by each program are listed as well as faculty members visting scientists and engineers

Through the looking glass: The future for NDE?

Nondestructive testing (NDT) is a mature industry, with global equipment sales fast moving towards $2B. per year. The use of conventional NDT will grow in developing countries and in developed countries the challenges will include those associated with maintaining aging infrastructure. For some systems the future will move to structural health monitoring (SHM) and for others into integration of online measurements in manufacturing. Nondestructive Evaluation (NDE) is a multi-disciplinary area of endeavor that has its origins in materials science and NDT. It seeks to provide an adequate science base for NDT to become a quantitative science. It was seen to be necessary to better detect, size and type defects, improve the reliability of inspection, and probability of detection (POD). There is particular interest in estimating the potential defects could have on performance or potential for loss of structural integrity, under various loading or stressor conditions, and ultimately implement risk-based reliability assessments. NDE must be seen more as a part of the wide field of engineering, as an interdisciplinary endeavor, that brings together the expertise of materials science and metrology, together with the underlying physics for inspection methods, as well as statistics, computers, robotics and software. The adoption of advanced manufacturing, will require new metrology tools and methods to provide data for assessing new materials including powder metals, as used in additive manufacturing, and various composites. The lessons from the past proceedings of this conference series include that the problems faced today are harder than was expected during the first decade of quantitative NDE research. Even with new types of transducers and much improved A/D and powerful computers new approaches and more basic measurement physics being understood, new insights are needed to provide the data needed to solve many real-world NDE problems, to understand and measure early degradation and to give the required data for remaining safe life or prognostic prediction

State-of-the-Art Review and Synthesis: A Requirement-based Roadmap for Standardized Predictive Maintenance Automation Using Digital Twin Technologies

Recent digital advances have popularized predictive maintenance (PMx), offering enhanced efficiency, automation, accuracy, cost savings, and independence in maintenance. Yet, it continues to face numerous limitations such as poor explainability, sample inefficiency of data-driven methods, complexity of physics-based methods, and limited generalizability and scalability of knowledge-based methods. This paper proposes leveraging Digital Twins (DTs) to address these challenges and enable automated PMx adoption at larger scales. While we argue that DTs have this transformative potential, they have not yet reached the level of maturity needed to bridge these gaps in a standardized way. Without a standard definition for such evolution, this transformation lacks a solid foundation upon which to base its development. This paper provides a requirement-based roadmap supporting standardized PMx automation using DT technologies. A systematic approach comprising two primary stages is presented. First, we methodically identify the Informational Requirements (IRs) and Functional Requirements (FRs) for PMx, which serve as a foundation from which any unified framework must emerge. Our approach to defining and using IRs and FRs to form the backbone of any PMx DT is supported by the track record of IRs and FRs being successfully used as blueprints in other areas, such as for product development within the software industry. Second, we conduct a thorough literature review spanning fields to determine the ways in which these IRs and FRs are currently being used within DTs, enabling us to point to the specific areas where further research is warranted to support the progress and maturation of requirement-based PMx DTs.Comment: (1)This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Aeronautical Engineering: A continuing bibliography with indexes, supplement 104

This bibliography lists 532 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in December 1978

Structural health monitoring: closing the gap between research and industrial deployment

There has been a large volume of research on structural health monitoring since the 1970s but this research effort has yielded relatively few routine industrial applications. Structural health monitoring can include applications on very different structures with very different requirements; this article splits the subject into four broad categories: rotating machine condition monitoring, global monitoring of large structures (structural identification), large area monitoring where the area covered is part of a larger structure, and local monitoring. The capabilities and potential applications of techniques in each category are discussed. Condition monitoring of rotating machine components is very different to the other categories since it is not strictly concerned with structural health. However, it is often linked with structural health monitoring and is a relatively mature field with many routine applications, so useful lessons can be read across to mainstream structural health monitoring where there are many fewer industrial applications. Reasons for the slow transfer from research to practical application of structural health monitoring include lack of attention to the business case for monitoring, insufficient attention to how the large data flows will be handled and the lack of performance validation on real structures in industrial environments. These issues are discussed and ways forward proposed; it is concluded that given better focused research and development considering the key factors identified here, structural health monitoring has the potential to follow the path of rotating machine condition monitoring and become a widely deployed technology