Browse Topic: Vehicle health management (VHM)

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Joint Estimation of Inputs and States for Multi-Axis Vibration Environment Testing2026-01-06836/20/2026
Monitoring inputs and states of a structural dynamic system is often challenging, as direct measurements are costly or even infeasible. A virtual sensing methodology is presented for jointly estimating the input and state of a structure when subjected to multi-directional base excitations. The approach uses a tuned Kalman Filter combined with a model-order reduction of the system model to ensure a low computational cost whilst allowing accurate estimation from a limited number of acceleration measurements. This enables real-time virtual health monitoring strategies and reduction in instrumentation during data acquisition without additional information such as location and direction of application about the inputs. The proposed methodology is validated numerically and experimentally using a notched aluminum beam excited on a multi-directional shaker table, driven simultaneously in two in-plane directions. The study demonstrates accurate full-field estimation of multiple responses along the beam as well as a joint-input-estimation. The results highlight the relevance of multi-axis vibration environments and the importance of multiple-input-multiple-output testing for dynamic characterization and structural health monitoring applications.
Salazar Colunga, Rodrigo, Pandiya, Nimish, Dindorf, Christian, Naets, Frank
Design and Run-Time Information Exchange for Health-Ready ComponentsJA6268_202303 (Current)5/26/2026
This Surface Vehicle & Aerospace Recommended Practice offers best practices and a methodology by which IVHM functionality relating to components and subsystems should be integrated into vehicle or platform level applications. The intent of the document is to provide practitioners with a structured methodology for specifying, characterizing and exposing the inherent IVHM functionality of a component or subsystem using a common functional reference model, i.e., through the exchange of design-time data and the application of standard vehicle data communications interfaces. This document includes best practices and guidance related to the specification of the information that must be exchanged between the functional layers in the IVHM system or between lower-level components/subsystems and the higher-level control system to enable health monitoring and tracking of system degradation severity. The intent is to provide an IVHM system that can robustly report the degradation of a given component before it reaches the point where it goes outside its operational performance envelope by providing sufficient advance notice to deal with the issue. This document does not specify or address how each layer in the IVHM system produces or uses the data available for exchange.
HM-1 Integrated Vehicle Health Management Committee
Using a System Reliability Model to Optimize Maintenance Costs A Best Practices GuideJA6097_201905 (Current)5/26/2026
SAE JA6097 (“Using a System Reliability Model to Optimize Maintenance”) shows how to determine which maintenance to perform on a system when that system requires corrective maintenance to achieve the lowest long-term operating cost. While this document may focus on applications to Jet Engines and Aircraft, this methodology could be applied to nearly any type of system. However, it would be most effective for systems that are tightly integrated, where a failure in any part of the system causes the entire system to go off-line, and the process of accessing a failed component can require additional maintenance on other unrelated components.
HM-1 Integrated Vehicle Health Management Committee
Implementation of Field-Ready SHM Systems for Manned and Unmanned Aircraft (Presentation Only)F-0082-2026-03385/5/2026
This presentation discusses the evolution of SMART Layer, based SHM system from a targeted inspection aid to a key enabler of IVHM and CBM strategies. Lessons learned from fielded rotorcraft applications are discussed, along with a practical path for integrating the SHM system components into both sustainment programs and future aircraft designs. The role of automation, data management, and health-state awareness in supporting aircraft readiness and lifecycle optimization is will also be discussed.
Chang, Fu-Kuo, Wang, Lujun, Li, Franklin, Chang, Grant, Kumar, Amrita
Sensitivity Analysis and Development Approach of HV Battery Lifetime for Complete Vehicle Integration2026-01-03954/7/2026
The lifetime and aging of the high voltage battery is one of the major discussion points for the end-customer to decide between buying a car with an electric powertrain or still using a conventional powertrain. Therefore, the provision of adequate vehicles to the end-customer, the aging of the high voltage battery become an important topic for the complete vehicle development. In addition, also legal regulations (e.g. EU7) will preset minimum requirements for the warranty of the high voltage battery. These circumstances define the lifetime / aging of the HV battery to be a complete vehicle development target, which needs to be developed. The paper will present a method for the development process of a lifetime target from complete vehicle perspective. The method is based on the generation of a representative monthly power profile and temperature profile. Depending on a monthly user routine, ambient temperature profile and charging behavior, the vehicle specific battery power profile will be generated using energy flow simulation. In addition, the simulation of the HV battery SoC and temperature is included, too. Second, using a generic battery cell aging model, the impact on the state of health will be estimated using the power and temperature profile for the lifetime of the battery. The aging behavior over lifetime of the HV battery can be estimated. Using the tools, several sensitivity studies have been performed (e.g. impact on charging behavior, ambient temperature, vehicle operating strategy) to understand the main impacts on battery aging. The simulation tool as well as the results of the sensitivity analysis will be presented in the paper.
Martin, Michael
Dynamic Stiffness Prediction in Cracked Cantilever Beams Using Enhanced ANN Techniques2026-28-00502/12/2026
This research paper provides a comprehensive study on how Artificial Neural Networks (ANNs) can be deployed to predict the stiffness characteristics of a cantilever beam with a crack of various depths and positions. The most destructive source of failure is considered to be vibration, so the major focus of this paper will be on how the cracks affect the modal stiffness. This study has various applications, such as airplane wings, bridges, stadiums, and arenas. A common research gap was noticed amongst the existing studies; the position of the cracks in the cantilever wasn’t considered, but this paper discusses how the location of cracks severely affects the dynamic behaviour of the cantilever. This study was done by carrying out modal analysis on a cantilever of the same dimensions with different crack configurations. Various crack dimensions and orientations were analysed to understand the effects of the crack on the dynamic behaviour of the cantilever. From the modal analysis results, we evaluated the natural frequency of the cantilever beams with various crack depths and locations. A decrease in natural frequency was observed as the crack depth increased, from which we can infer that the cantilever will experience resonance at much lower external vibration, which makes the structure unreliable. Cracks near the support markedly lower natural frequency due to maximum shear force and bending there, whereas free-end cracks have a negligible impact compared to a reference cantilever. Simulation results feed an ANN, enabling it to accurately predict dynamic characteristics for any combination of crack depth and position. The developed ANN model achieved high prediction accuracy with a Mean Squared Error (MSE) of less than 1x10-5 and an R2 value exceeding 0.998 on the test dataset, demonstrating its robustness as a tool for structural health monitoring.
SB, Harshini, Rajkumar, Manjari, R, Krithika, K, Anusha, K, Divya, Bhaskara Rao, Lokavarapu
Self-Supervised Diagnostics & Prognostics Framework for Predictive Maintenance in Electric Vehicles2026-26-06731/16/2026
Predictive maintenance is critical to improving reliability, safety and operational efficiency of connected vehicles. However, classic supervised learning methods for fault prediction rely heavily on large-scale labeled data of failures, which are difficult to obtain and maintain a manually built dataset of failure events in real automotives settings. In this paper, we present a novel self-supervised anomaly detection model that makes predictions on the faults without the need for labeled failures by using only the operational data when the systems or robots are healthy. The method relies on self-supervised pretext tasks, like masked signal reconstruction and future telemetry prediction, to extract nominal multi-sensor dynamics (i.e., temperature, pressure, current, vibration) while jointly minimizing the deviation between encoded/decoded signals and normal patterns in the latent space. A unsupervised anomaly detection model is then used to detect when the learned patterns are violated. This in conjunction with data driven predictive allows for early fault detection on key subsystems such as batteries, electric motors, brake systems, and cooling systems. They tested the framework on some public benchmark datasets, and it’s pretty good at catching early anomalies with high accuracy and recall even better than the usual threshold-based methods. The study points out how important it is to use data from normal, healthy systems to build maintenance strategies that can scale well, adapt easily, and save costs, especially for connected vehicle fleets. Plus, the model helps explain what’s going on by identifying which telemetry signals are behind the anomalies, making it easier to take timely and practical maintenance actions. This work basically offers a new, practical way to keep vehicle health in check ahead of time, helping fleets stay up and running longer while cutting down on surprise breakdowns and expensive repairs.
Kumar, Pankaj, Deole, Kaushik, Hivarkar, Umesh
A Literature Review on Application of Maintenance and Management Strategies for Electric-Vertical Take-Off and Landing Aircraft’s Maintenance, Repair, and Overhaul Organizations01-18-03-001612/18/2025
In the context of emerging technology developed for advanced air mobility concept, its maintenance protocols are not yet mature and existing aviation maintenance systems may not support electric-vertical take-off and landing (e-VTOL) needs. Thus, the operation of e-VTOL aircraft during its deployment stage necessitates the need for qualitative maintenance support. The main purpose of this study is to develop the basic structural principles of the projected new maintenance, repair, and overhaul (MRO) organization for e-VTOL air vehicles, which will support airworthiness through comprehensive maintenance approaches. Thus, the operation of e-VTOL aircraft during its deployment stage necessitates the need for qualitative maintenance support. The importance of the study is to offer standard procedures based on management and maintenance strategies, application of predictive and prescriptive maintenance tools, which pose a significant contribution to ensuring safety, reliability, and cost-effectiveness in e-VTOL operations. The methodology based on leveraging modern management theory in combination with maintenance strategy ensures reaching a goal, creating an effective MRO organization. The findings of the analysis, conducted on the current study, reveal the suitability of the traditional aircraft maintenance approach for e-VTOL air vehicle maintenance processes that can support multi-model aircraft with different design configurations and architectures. To facilitate comprehensive engagement among all relevant stakeholders, the result of the analysis assumes the establishment of an effective aircraft maintenance ecosystem. Effective agreement between e-VTOL operators and MRO providers will contribute to ensuring appropriateness with evolving aircraft architectures in compliance with regulatory standards. This study fills a research gap in the literature relating to aircraft maintenance by proposing a digitally integrated approach and, regulation-compliant framework tailored for e-VTOL aircraft. The suggested multi-strategy maintenance model incorporates predictive analytics, modular diagnostics, and contingency planning tailored for e-VTOL operations, synergizing with AI implementation distinguishes it with its novelty implemented in the modern aviation sector.
Imanov, Tapdig, Bozdereli, Arzu
Design and Development of Fiber Optic Vibration Sensor for Automobile Applications2025-28-037110/30/2025
This work goals at designing and developing a vibration sensor based on fiber optics and it is a component of the Structural Health Monitoring (SHM) system. The main component of the SHM system is a network of sensors (strain, vibration, acoustic, etc.) that can track the physical condition of the structures in real time and assist in identifying the beginning of any damage. During flight, launch vehicles typically experience extreme dynamic stresses such shock, random vibration, aerodynamic, and thermal. The assessment of health and the detection of any part detachment or loosening of sub- assemblies are greatly aided by vibration monitoring. Compared to traditional electrical sensors (such piezoelectric or capacitive), SHM systems based on fiber optic sensors show promise because of their EMI resistance, ease of integration into structures, and widespread sensing capabilities. Multiplexing capability of optical fibers is the main additional benefit for system monitoring the numerous dispersed sensors. Surface- bonded and embedded fiber bragg gratings (FBG) are commonly utilized configurations for aircraft and flight structure monitoring. The frequency of vibration changes, or the frequency signature changes, as structural damage is beginning. Thus, a vibration sensor provides vital information about the structure’s condition before any catastrophic damage occurs.
P, Geetha, Koppala, Neelima, Nagarajan, Sudarson
Fiber Optic Sensing TechnologiesTBMG-5392110/1/2025
Known as FOSS (for fiber optic sensing system), NASA’s patented, award-winning technology portfolio combines advanced sensors and innovative algorithms into a robust package that accurately and cost-effectively monitors a host of critical parameters in real time. These include position/deformation (displacement, twist, rotation), stiffness (bending, torsion, vibration), operational loads (bending moments, shear loads, torques), strength/stress (pressure/fatigue, breakage prediction), and magnetic fields (cracks or other flaws in safety-critical metal structures) for structural health monitoring applications. In addition to monitoring the structure of a tank, FOSS is capable of sensing the tank’s inventory, including amounts, temperatures, and stratification.
Health and Usage Monitoring System Data Interchange SpecificationAS5395A (Current)9/18/2025
This document establishes the Rotorcraft Industry Technology Association (RITA) Health and Usage Monitoring System Data Interchange Specification. The RITA HUMS Data Interchange Specification will provide information exchange within a rotorcraft HUMS and between a rotorcraft HUMS and external entities.
HM-1R Rotorcraft Integrated Vehicle Health Management
Common, Open Data Exchange Format for Rotorcraft Health and Usage Monitoring Systems (CODEX-HUMS)AS7140 (Current)9/16/2025
This SAE Aerospace Standard (AS) provides guidance on the development and implementation of a Common Open Data Exchange (CODEX) format for rotorcraft Health and Usage Monitoring Systems (HUMS). The standard is intended to apply to data generated on board rotorcraft and the transmission of that data, as well as the data ingested by ground stations to facilitate Integrated Vehicle Health Management (IVHM). The standard provides both a conceptual data model (or models) and logical data models for rotorcraft HUMS use cases. However, the intent of the standard is to allow for data schema evolution and does not define the physical data models. The standard provides functional requirements for HUMS data acquisition and HUMS data transfer interfaces. The initial standard is focused primarily on drive train systems but is designed to potentially accommodate other data (e.g., structural fatigue) in future revisions. It is acknowledged that current rotorcraft onboard systems do not generate data in this format and will require a translator for use in other systems. However, the intent is to set the standard and have future onboard systems provide data natively with the CODEX-HUMS format.
HM-1R Rotorcraft Integrated Vehicle Health Management
Utilizing Integrated Vehicle Health Management Systems for Airworthiness CreditARP7122 (Current)5/27/2025
The process detailed within this document is generic and applies to the entire end-to-end health management capability, covering both on-board and on-ground elements in both commercial and military applications throughout their life cycle. While some guidance related to usage of ground-based health management equipment for airworthiness credit exists in certain areas, this document provides a general mechanism to ensure a level of integrity commensurate with the potential aircraft-level consequences of the relevant failure conditions. The practical application of this standardized process is detailed in the form of a checklist. In order to provide some detailed guidance utilizing the process and checklist, some high-level examples of successful cases of approved “Maintenance Credit” applications for airworthiness credit (and one case where the approval is in process in 2024) are included. This document does not teach how to design an IVHM function, how to do a safety or risk analysis, prescribe hardware or software assurance levels, or answer the question, “How much mitigation and evidence are enough?” The criticality level and mitigation methods will be determined between the applicant and the regulator, using existing guidance from SAE International and other sources. Note that the focus of this document is to ensure appropriate process integrity for the creation of a candidate IVHM function, but it may not address all the elements required to operationalize that function. This document uses the term IVHM to refer to any health management function applied to an air vehicle. The SAE standards committees have been using this term for decades; however, other communities within this industry have used terms such as Aircraft Health Management or Monitoring (AHM), Integrated Aircraft Health Management (IAHM), Vehicle Health Management (VHM), and Rotorcraft Health and Usage Monitoring System (HUMS) to refer to the same concept. At the subsystem level, terms such as Structural Health Monitoring (SHM), Equipment Health Management (EHM), Engine Condition Monitoring (ECM), and Engine Health Management (EHM) are also commonly used. It should be understood that all these terms refer to the same function. There are cases where this process is applicable but is not required because of historic precedents. For example, there is a historical precedent for using an off-board health management solution to achieve compliance with extended-range twin-engine operations performance standards (ETOPS) (refer to AC 120-42A).
HM-1 Integrated Vehicle Health Management Committee
Management, Repair, and Overhaul: Vol. 2EPRCOMPV0820244/30/2025
Reeve, Tammy, Phillips, Paul
Health and Condition Monitoring Tool for Real-Time and on-Board Diagnosis of PEM Fuel Cell in Heavy Duty Vehicles2025-01-85564/1/2025
The deployment of PEM fuel cell systems is becoming an increasingly pivotal aspect of the electrification of the transport sector, particularly in the context of heavy-duty vehicles. One of the principal constraints to market penetration is durability of the fuel cell which hardly meets the expected targets set by the vehicle manufacturers and regulatory bodies. Over the years, researchers and companies have faced the challenge of developing reliable diagnostic and condition monitoring tools to prevent early degradation and efficiency losses of fuel cell stack. The diagnostic tools for fuel cell rely usually on model-based, data driven and hybrid approaches. Most of these are mainly developed for stationary and offline applications, with a lack of suitable methods for real-time and vehicle applications. The work presented is divided into two parts: the first part explores the main degradation conditions for a PEMFC and characteristics, advantages, and application limits of the main methodologies for fuel cell diagnostic, while in the second part the features and the development process of an innovative, real-time, and on-board health and condition monitoring system, based on electrochemical impedance spectroscopy (EIS), are presented. The new innovative tool allows to detect, identify and isolate degradation, faults and non-optimal conditions. The computational performance and reliability of the diagnostic tool are tested and validated through experimental tests carried out in the laboratory on single cell and short fuel cell stack over a wide range of operating conditions and under specific sub-optimal/fault states such as drying, flooding and reactants starvation. The condition and health of PEMFC are estimated using specific health indicators for the most common root causes of faults such as drying, flooding, catalyst poisoning and anode/cathode starvation.
Di Napoli, Luca, Mazzeo, Francesco
Forced Vibration Analysis of Cracked Functionally Graded Beams2025-28-01692/7/2025
This study investigates the forced vibration characteristics of a functionally graded material (FGM) beam possessing a square cross-section and featuring a V-shaped crack. The FGM beam exhibits a gradual transition in mechanical composition from a ceramic to a metallic surface. Employing finite element analysis software, a comprehensive numerical analysis is conducted to evaluate the frequencies and mode shapes of the cracked FGM beam under simply supported boundary conditions. The study meticulously explores the effects of various crack parameters, including crack opening width, depth, and location. The findings highlight the significant influence of the crack opening width on the frequencies, indicating that wider cracks result in decreased frequencies across all mode shapes. Conversely, the impact of crack depth and location on the dynamic behavior of the cracked FGM beam within the studied ranges appears relatively minor. These insights offer valuable perspectives into the vibrational characteristics of cracked FGM beams, which can contribute to structural health monitoring and allow optimizing their design. In automotive applications, these insights aid in the development of more resilient vehicle components and improving the overall durability and reliability of automotive structures.
D, Manish, C V, Prasshanth, N, Suhas, Bhaskara Rao, Lokavarapu
Guidance for Assessing the Damage Detection Capability of Structural Health Monitoring SystemsARP6821 (Current)2/7/2025
This document contains information and guidance necessary for the development of a representative, repeatable validation program that may be utilized to assess the capability of SHM systems. The nature of SHM data differs from that seen in traditional nondestructive evaluation (NDE) applications in that the position of SHM sensors is fixed and SHM data can be available much more frequently (if not continuously) over time. This document presents methodologies that can be used to arrive at SHM capability while considering the unique nature of SHM deployment. Each SHM system must be considered independently to determine the applicability and limitations of the guidance contained here for each SHM system being assessed.
Aerospace Industry Steering Committee on Structural Health
Construction of Multi-Scale Aging Indicators Based on the Aging Mechanism of Fuel Cells2025-01-70891/31/2025
State of health (SOH) estimation is essential to ensure safety and reliability in the operation of Proton Exchange Membrane Fuel Cells (PEMFCs). The aging of fuel cells results from the deterioration of multiple internal components, and the aging degree of some key components even directly determines the end of cell life. Due to the complexity of the internal reactions in fuel cell, many internal parameters cannot be measured or recorded during aging tests. In addition, external characteristics do not reflect the internal changes in the cell. Therefore, establishing a multi-scale metric based on fuel cell components is very important for fuel cell life research. During the aging process of a fuel cell, the contributions of different components to the overall aging vary significantly. Additionally, the allocation of indicator parameters presents a challenge in multi-scale modeling. To address these issues, this paper proposes a method to construct multi-scale indicators for fuel cells. Firstly, based on the operational mechanisms of fuel cells, a 3-D Computational Fluid Dynamics (CFD) model of the fuel cell is developed using COMSOL Multiphysics 6.2 to simulate the working environment of the fuel cell. In addition, based on existing research, the aging mechanisms of various fuel cell components are analyzed, and aging models are established. The aging of selected components is then simulated in MATLAB R2023a based on the component aging mechanism model. Moreover, a co-simulation platform based on COMSOL and MATLAB is established to facilitate parameter interaction and iteration between the two models, thereby obtaining the aging data of the cell. Finally, the data is analyzed to select parameters and allocate coefficients for the multi-scale aging indicators. The multi-scale aging indicator can provide an effective approach to characterizing the aging state of fuel cells.
Lin, Yipeng, Min, Haitao, Sheng, Xia, Zhang, Zhaopu, Sun, Weiyi
Spacecraft System Health Management: Current Practices and Emerging TechnologiesR-56612/12/2024
Ensuring the safe and reliable operation of spacecraft is a complex task that requires advanced technologies and innovative approaches. This comprehensive guide provides a deep dive into the world of spacecraft system health management. From understanding the intricacies of spacecraft systems to exploring cutting-edge technologies like AI and digital twins, this book offers a valuable resource for anyone interested in the field. Key Features: - Clear and accessible language: The book is written for both technical experts and general readers, making it easy to understand complex concepts. - Real-world examples: Case studies and examples from actual missions bring the theoretical concepts to life. - Future-focused: The book explores emerging technologies that are shaping the future of spacecraft health management, giving readers a glimpse into the future of space exploration. Whether you're a seasoned space engineer or simply curious about the wonders of space exploration, this book offers valuable insights into the critical role of system health management in ensuring mission success. In addition to its technical depth, the book also explores the broader implications of spacecraft health management. It discusses the ethical and societal considerations involved in space exploration and the importance of responsible innovation. By understanding these factors, readers can gain a well-rounded perspective on the field. Spacecraft System Health Management is an essential resource for anyone interested in the future of space exploration. It provides a comprehensive overview of the key concepts and technologies, making it a valuable tool for students, researchers, and professionals alike.
Khan, Samir
Guide to Temperature Monitoring in Aircraft Gas Turbine EnginesAIR1900C (Current)12/3/2024
This SAE Aerospace Information Report (AIR) provides an overview of temperature measurement techniques for various locations of aircraft gas turbine engines while focusing on current usage and methods, systems, selection criteria, and types of hardware.
E-32 Aerospace Propulsion Systems Health Management
Detection of Cut-Out in Aluminum Plate Using Ultrasonic Guided Waves: A Finite Element Analysis01-17-03-001911/9/2024
Aluminum alloys serve a critical role in the aerospace industry, accounting for a significant amount of commercial aircraft weight. Despite the growing use of composite materials, aluminum remains important in airframe construction due to its lightweight, cost-effectiveness, and high strength potential. Structural integrity is critical in modern engineering, necessitating early diagnosis and localization of damage. To detect the flaws, cracks, and cut-out in the structures, structural health monitoring (SHM) systems are essential, with non-destructive testing (NDT) methodologies playing critical roles. Among these technologies, ultrasonic guided wave testing (UGWT) has gained popularity because of its capacity to propagate over long distances and detect subsurface faults. This article investigates the use of UGWs to identify cut-outs in aluminum plates. The numerical investigation has been carried out using commercially available finite element software Abaqus. The ultrasonic lamb waves are generated through the load. The results obtained in pristine and defected 2D aluminum plate has been compared with proper selection of actuation and sensing points. Further by changing the location of actuation and sensing points the shift of damage scattering components has been observed. After identification of reflected wave mode, the location of the cut-out can be predicted accurately.
Rajput, Arun, Patil, Vaibhav Kailas, Bhosale, Aniket, Yadav, Ritesh, Ghatge, Adityaraj, Pandey, Anand Ji
Validation and Verification of Integrated Vehicle Health Management SystemsARP6887 (Current)9/18/2024
This SAE Aerospace Recommended Practice (ARP) provides guidance to plan and perform validation and verification of IVHM systems. The intent of this ARP is to help the reader appreciate and understand additional objectives and activities of validation and verification processes, beyond validation and verification of the vehicle, that arise due to the nature of an IVHM System. This includes an end-to-end evaluation of the entire IVHM system, noting that IVHM is a “system of systems.” In order to perform validation and verification, the user must determine what they are using IVHM for, including the criticality of the application. The process should then determine appropriateness of the data corresponding to the application criticality. This document provides validation and verification guidance for IVHM as: (1) a system of systems, (2) a system, and (3) elements within a system. While this document is not intended to be prescriptive, it is a reference guide that highlights and discusses some attributes of IVHM and its uses that typically necessitate special handling during validation and verification. For more information about validation and verification processes required for onboard aerospace applications, please refer to ARP4754 (for development process), ARP4761 (for safety assessment process), RTCA DO-178 (for software), RTCA DO-254 (for hardware), and FAA guidance provided by AC 25.1309-1A. The validation and verification processes identified in the standards cited above must be considered where IVHM elements are part of an airborne system. See 1.3 for a more detailed overview.
HM-1 Integrated Vehicle Health Management Committee
Environment Spectra and Corrosivity Monitoring Using Electrochemical and Electrical Resistance SensorsAIR6970 (Current)7/23/2024
This SAE Aerospace Information Report (AIR) provides guidance on using environmental, electrochemical, and electrical resistance measurements to monitor environment spectra and corrosivity of service environments, focusing on parameters of interest, existing measurement platforms, deployment requirements, and data processing techniques. The sensors and monitoring systems provide discrete time-based records of (1) environmental parameters such as temperature, humidity, and contaminants; (2) measures of alloy corrosion of the sensor; and (3) protective coating performance of the sensor. These systems provide measurements of environmental parameters, sensor material corrosion rate, and sensor coating condition for use in assessing the risk of atmospheric corrosion of a structure. Time-based records of environment spectra and corrosivity can help determine the likelihood of corrosion to assess the risk of corrosion damage of the host structure for managed assets and aid in establishing maintenance intervals and processes. Diagnostics for determining damage to a structure and prognostics for predicting the remaining useful life before reaching a critical corrosion damage threshold are not within the scope of this document. Also not within the scope of this document are other nondestructive evaluation tools or structural health monitoring (SHM) technologies that can directly assess corrosion-based damage. While this document is focused on air-vehicle environments, many of these topics would translate to other industries and systems without much modification.
HM-1 Integrated Vehicle Health Management Committee
A Guide to Aircraft Turbine Engine Vibration Monitoring SystemsARP1839 (Current)6/12/2024
This Aerospace Recommended Practice (ARP) is a general overview of typical airborne engine vibration monitoring (EVM) systems applicable to fixed or rotary wing aircraft applications, with an emphasis on system design considerations. It describes EVM systems currently in use and future trends in EVM development. The broader scope of Health and Usage Monitoring Systems, (HUMS) is covered in SAE documents AS5391, AS5392, AS5393, AS5394, AS5395, AIR4174. This ARP also contains the essential elements of AS8054 which remain relevant and which have not been incorporated into Original Equipment Manufacturers (OEM) specifications.
E-32 Aerospace Propulsion Systems Health Management
Flange - ThermocoupleARP465C (Current)6/12/2024
This SAE Aerospace Recommended Practice (ARP) provides guidance for the design of flanges on temperature sensors intended for use in gas turbine engines. Three figures detail the configuration of standard size flange mounts with bolt holes, slotted flanges, and miniaturized flanges for small probes.
E-32 Aerospace Propulsion Systems Health Management
Temperature Measuring Devices NomenclatureARP485B (Current)6/12/2024
This SAE Aerospace Recommended Practice (ARP) defines the nomenclature of temperature measuring devices. General temperature measurement related terms are defined first, followed by nomenclature specifice to temperature measuring devices, particularly thermocouples.
E-32 Aerospace Propulsion Systems Health Management
Generating Reduced-Order Image Data and Detecting Defect Map on Structural Components Using Ultrasonic Guided Wave Scan2024-26-04166/1/2024
The paper presents a theoretical framework for the detection and first-level preliminary identification of potential defects on aero-structure components by employing ultrasonic-guided wave-based structural health monitoring strategies, systems and tools. In particular, we focus our study on ground inspection using a laser-Doppler scan of the surface velocity field, which can also be partly reconstructed or monitored using point sensors and actuators structurally integrated. Using direct wavefield data, we first question the detectability of potential defects of unknown location, size, and detailed features. Defects could be manufacturing defects or variations, which may be acceptable from a design and qualification standpoint; however, those may cause significant background signal artefacts in differentiating structure progressive damage or sudden failure like impact-induced damage and fracture. We consider the surface velocity field over continuous time stamps obtained from laser-doppler scan experiments using surface-integrated piezoelectric transducers on a composite panel. We consider such likely uncertainty in material properties and measurement noise issues while studying specific defects such as delamination. We use the physics of wave interaction with these different defects to show the detectability of hotspots and their preliminary identification ability, whether they could be material manufacturing uncertainty or structure damage such as delamination. We then discuss advanced algorithms based on reduced-order imaging techniques with certain invariance properties, such as signal phase change associated with stationary features compared to moving features or noise. A novel first-order cross-correlation using surface velocity similarity is developed and applied to study the stationary and non-stationary features in the image. The defect map is then generated from the high-dimensional temporal field data, where a detection threshold is used to define the defect hot spot. To this end, the nature of wave mode conversion and attenuation across these defects are discussed, which are important precursors for full-fledge SHM system-based automated detection.
Kolappan Geetha, Ganesh, Ravi, Nitin. B, Roy Mahapatra, Debiprosad
A CDMA Based Approach for QoS Improvement in Intra-Aircraft Wireless Sensor Networks (IAWSN)2024-26-04356/1/2024
Aviation industry is striving to leverage the technological advancements in connectivity, computation and data analytics. Scalable and robust connectivity enables futuristic applications like smart cabins, prognostic health management (PHM) and AI/ML based analytics for effective decision making leading to flight operational efficiency, optimized maintenance planning and aircraft downtime reduction. Wireless Sensor Networks (WSN) are gaining prominence on the aircraft for providing large scale connectivity solution that are essential for implementing various health monitoring applications like Structural Health Monitoring (SHM), Prognostic Health Management (PHM), etc. and control applications like smart lighting, smart seats, smart lavatory, etc. These applications help in improving passenger experience, flight operational efficiency, optimized maintenance planning and aircraft downtime reduction. Intra Aircraft WSNs (IAWSN) used for such applications are expected to provide robust and reliable communication performance. However, IAWSNs, when deployed, must co-exist with other wireless devices and networks based on Wi-Fi and Bluetooth technologies. Sharing of the ISM frequency band (2.4 GHz) among these networks makes the co-existence problem more challenging and has a significant impact on the Quality of Service (QoS) in terms of throughput, latency and Packet Error Rate (PER) of IAWSN. In addition, they are subjected to additional electromagnetic interference from other electronic and avionic systems onboard aircraft. There are various channel management, priority-based scheduling and time-sharing techniques that are deployed currently to address the co-existence problem. However, these methods perform a trade-off among one or more operational parameters like channel bandwidth, number of nodes per channel, throughput, latency, PER, etc. of IAWSN. Code Division Multiple Access (CDMA) technique is a proven one in cellular networks for providing reliable interference free communication performance especially in large scale networks. This paper evaluates the feasibility of deploying CDMA for IEEE 802.15.4 based IAWSN onboard aircraft. A CDMA based communication schema is proposed and simulated for IAWSN operating as per IEEE 802.15.4 protocol. The communication performance of the CDMA based IAWSN is evaluated in comparison with the performance of a standard IEEE 802.15.4 protocol implementation in the presence of interference from the co-nodes of the IAWSN and Wi-Fi devices by analyzing the QoS parameters like signal to noise ratio (SNR), operational bandwidth, Bit-Error Rate (BER) and Process Gain through simulation. Simulations results are evaluated against the desired performance level for a reference use case application. Improvement opportunities are identified and areas for future research are proposed.
C S, Adishesha, Ramamurthy, Prasanna, Banerjee, Kumardeb, Barik, Mridul Sankar
Management, Repair, and Overhaul: Vol. 1EPRCOMPV2820235/10/2024
Maintenance, repair, and overhaul (MRO) facilities are a major contributor to the safe, reliable, and efficient service of an aircraft. Practices have continually evolved to support complex operations and enhance performance and availability while decreasing operating costs. With technological breakthroughs in electric land vehicles revolutionizing their respective industry, MRO facilities in aviation are also adopting digital technologies in their practices. Despite this drive towards digitalization, the industry is still dominated by manual labor and subjective assessments. Operations may or may not follow the exact expected profile, and that is when sensors integrated into a maintenance system can indicate that the aircraft may or may not fly another flight. Today, several technologies, processes, and practices are being championed to resolve some of these outstanding challenges. Considering this, it is important to present current perspectives regarding where the technology stands and how we can evaluate capabilities for autonomous decision support systems that prescribe maintenance activities. It is a complex issue because it is a transversal phenomenon involving many stakeholders cooperating to achieve their logistical and strategic interests. Overarching challenges—from data management, robotics, optimization, artificial intelligence, and systems engineering—must be appreciated. Overlooking some of these unsettled domain issues can potentially undermine any benefits in speed, process, and resilience promised by such systems. This chapter provides some understanding of specific motivating factors by focusing on the digitalization challenges for MRO 4.0 (i.e., the digital transformation of MRO) and the role of building “trust” in technology by reimagining stakeholder experiences. As a result, this chapter discusses emerging technologies that continue to evolve with changes to the products and services they maintain and the socioeconomic environment they function within. Prioritizing programs can add value as MRO 4.0 is slated to significantly affect the industry in the near future.
Khan, Samir, Walthall, Rhonda, Rajamani, Ravi, Holland, Steve
Evaluation of Local and Global Diagnostics for the Integration of Stochastic Time Series Models and Variational Autoencoders: Experimental Assessment on a Full Scale Helicopter BladeF-0080-2024-13715/7/2024
In this work, a unified framework integrating global and local SHM methods for structural health monitoring (SHM) of rotorcraft structures is proposed. This framework integrates both "local" ultrasonic-guided wave-based and "global" vibration-based SHM schemes for tackling damage detection, identification, and quantification under uncertainty. The local SHM is completed by training a variation of variational auto-encoder (MMD-VAE) along with feed-forward neural networks (FFNN). The compressed latent space vector obtained during the training process is applied to achieve both signal reconstruction and state prediction. In terms of the global model, functionally pooled auto-regressive models with exogenous excitation (VFP-ARX) models are applied including to capture low-frequency vibrations. The complete experimental evaluation and assessment of the proposed framework are presented for an Airbus H125 helicopter blade under both low-frequency vibrations and ultrasonic guided waves for SHM.
Fan, Yiming, Kopsaftopoulos, Fotis, Forrester, David, Zhou, Peiyuan
Development of a Common, Open Data Exchange (CODEX) for Rotorcraft HUMS DataF-0080-2024-11965/7/2024
A Common Open Data Exchange format for rotorcraft Health and Usage Monitoring Systems (CODEX-HUMS) would offer a more affordable, capable and effective Integrated Vehicle Health Management System. The Society of Automotive Engineers (SAE) HM-1R committee is developing a standard definition for the CODEX-HUMS open data format produced or used by an on-board or off-board system, SAE Aerospace Standard AS7140. The standard format benefits end users (e.g., operators, developers, suppliers, integrators, and maintainers) with the capability to more rapidly operationalize HUMS data. This HUMS open data format meets the intent of a Modular Open System Approach (MOSA) and provides a foundation for rapid realization of operational benefits from the point of maintenance and from the exchange of HUMS data with external enterprise systems.
Tucker, Brian, Carney, Eric, Fok, Derek, Royar, Kenneth T., Cheung, Catherine
A Study on a Prognostics and Health Management (PHM) Based on Fracture Mechanics Using Deep Learning2024-01-22484/9/2024
This paper presents deep learning-based prognostics and health management (PHM) for predicting fractures of an electric propulsion (eP) drivetrain system using real-time CAN signals. The deep learning algorithm, based on autoencoders, resamples time-series signals and converts them into 2D images using recurrence plots (RP). Subsequently, through unsupervised learning of DeepSVDD, it detects anomalies in the converted 2D images and predicts the failure of the system in real-time. Also, reliability analysis based on fracture mechanics was performed using the detected signals and big data. In particular, the severity of the eP drivetrain system is proportional to the maximum shear stress (τmax) in terms of linear elastic fracture mechanics (LEFM) and can be calculated by summarizing the relationship between cracks (a) and the stress intensity factor (KIII). During this process, the system status can be checked by comparing the stress intensity factor and fracture toughness (KIIIc), and the time from the detection of an abnormal signal in the system to complete failure can be quantitatively determined. Therefore, it is possible to continuously maintain the status of the system by detecting failure signals using deep learning before vehicle parts fail, and with the detected failure prediction signals, a process can be established to enable users to repair defects in the vehicle system before breakdown occurs. By predicting the remaining life of the system and calculating field reliability through these procedures, we introduce innovative technologies aimed at preventing safety accidents, reducing economic costs, and addressing quality issues. In the future, we expect to achieve high business performance by extending and applying this deep learning-based PHM approach to all vehicle components.
Moon, Byungwoo, Lee, SangWon, Nam, DongJin, Kim, Jeonghwan, Bae, JaeWoong, Shin, JeongMin
A Process for Utilizing Aerospace Propulsion Health Management Systems for Airworthiness CreditARP5987A (Historical)4/1/2024
The process detailed within this document is generic and applies to the entire end-to-end health management capability, covering both on-board and on-ground elements, in both commercial and military applications throughout their lifecycle. This ARP addresses a gap in guidance related to usage of ground-based health management equipment for airworthiness credit, ensuring a level of integrity commensurate with the potential aircraft-level consequences of the relevant failure conditions. The practical application of this standardized process is detailed in the form of a checklist. The on-board elements described here are typically the source of the data acquisition used for off-board analysis. The on-board aspects relating to airworthiness and/or safety of flight, e.g., pilot notification, are addressed by existing guidance and policy documents. If a proposed health management capability for airworthiness credit involves modification of the on-board systems, the substantiation of those changes should be based on the applicable type certification guidance. This document does not prescribe hardware or software assurance levels, nor does it answer the question “how much mitigation and evidence are enough?” The criticality level and mitigation methods will be determined between the applicant and the regulator. There are cases where this process is applicable but may not be appropriate due to historical precedents. For example, there is a historical precedent for using an off-board health management solution to achieve compliance with Extended-Range Twin-Engine Operations Performance Standards (ETOPS) (refer to FAA AC 120-42A). In order to provide some detailed guidance utilizing the process and checklist, some high-level examples of previous successful cases of maintenance credit applications for airworthiness credit are included. Refer to ARP5120 for additional examples of practical mitigating measures applicable to health management systems. At this point, it is incumbent on the applicant to explain any differences in terminology between the health management system they are seeking credit for and the appropriate regulatory references. For example, the system name often uses interchangeable terms such as “Engine Health Monitoring,” “Equipment Health Management,” “Prognostic Health Management,” “Powerplant Health Management,” etc.
E-32 Aerospace Propulsion Systems Health Management
Enhancing In-Flight Structural Health Monitoring of Vertical Lift Vehicles Operating in an Urban EnvironmentSM-2024-TVF-50872/6/2024
In-situ airframe sensors have long been considered a potential solution for structural health monitoring that could change the design, certification, operation and maintenance paradigms of flight vehicles. In this approach, large networks of sensors covering the entire, or most of, an airframe throughout its operational lifetime would support real-time decisions on airworthiness and obviate the need to overbuild components or perform multiple cycles of structural qualification testing and inspections. This concept would go beyond the current practice of placing select sensors in strategic locations or relying on such sensors only during airframe qualification flights and inspections. For vehicles in the emerging urban air mobility space, reducing weight associated with overbuilds and shortening downtime associated with inspections are critical for improving safety and affordability. In practice, the wide-scale use of in-situ sensors as primary assurance for structural health has not been demonstrated to be feasible or the best solution. A sensor integration testbed was developed as a platform to evaluate the potential of multiple sensor types to enable decision making on airworthiness. We report on the initial runs of this testbed with multiple sensors attached to a common test article. Metal foil strain gauges, eddy current, fiber optic, guided wave (acoustic emission and ultrasonic) and carbon nanotube roving sensors were affixed to the test article. Baseline as well as post damage initiation and fatiguing data are presented and discussed. Despite the relative simplicity of the test article, the interpretation of the as-captured test data was generally not conclusive or did not have wide enough coverage. This result emphasizes the challenges and current limitations both in testing and the practical broad application of embedded sensors as the determinative elements in critical decision making on wide-scale structural health.
Sauti, Godfrey, Wicheski, Russell, Steller, Christopher, Moore, Jason, Siochi, Emilie, Horne, Michael
The Adoption of Digital Twins in Integrated Vehicle Health ManagementEPR202302410/26/2023
To many, a digital twin offers “functionality,” or the ability to virtually rerun events that have happened on the real system and the ability to simulate future performance. However, this requires models based on the physics of the system to be built into the digital twin, links to data from sensors on the real live system, and sophisticated algorithms incorporating artificial intelligence (AI) and machine learning (ML). All of this can be used for integrated vehicle health management (IVHM) decisions, such as determining future failure, root cause analysis, and optimized energy performance. All of these can be used to make decisions to optimize the operation of an aircraft—these may even extend into safety-based decisions. The Adoption of Digital Twins in Integrated Vehicle Health Management, however, still has a range of unsettled topics that cover technological reliability, data security and ownership, user presentation and interfaces, as well as certification of the digital twin’s system mechanics (i.e., AI, ML) for use in safety-critical applications. Click here to access the full SAE EDGETM Research Report portfolio.
Phillips, Paul
A Guide to APU Health ManagementAIR5317A (Current)9/15/2023
AIR5317 establishes the foundation for developing a successful APU health management capability for any commercial or military operator, flying fixed wing aircraft or rotorcraft. This AIR provides guidance for demonstrating business value through improved dispatch reliability, fewer service interruptions, and lower maintenance costs and for satisfying Extended Operations (ETOPS) availability and compliance requirements.
E-32 Aerospace Propulsion Systems Health Management
Guide to Temperature Monitoring in Aircraft Gas Turbine EnginesAIR1900B (Historical)9/7/2023
This SAE Aerospace Information Report (AIR) provides an overview of temperature measurement techniques for various locations of aircraft gas turbine engines while focusing on current usage and methods, systems, selection criteria, and types of hardware.
E-32 Aerospace Propulsion Systems Health Management
Nondestructive Inspection Program Requirements for Aerospace SystemsAS6870A (Current)6/2/2023
This SAE Aerospace Standard defines the requirements for establishing a nondestructive inspection (NDI) program for aerospace systems to include but not limited to aircraft structure, aircraft stores (external structures such as antennas, pods, fuel tanks, weapons, radomes, etc.) and missile/rocket structural components when an NDI Program Plan is required by contract. NDI Programs are essential to ensuring NDI processes are implemented to support the lifecycle design requirements of the system and its components. NDI Programs are applicable to all phases of the system life cycle, including acquisition, modification, and sustainment. This standard may also be applicable to mechanical equipment, subsystems, and propulsion systems, but the requirements defined by the NDI Program Plan should be tailored by the contracting agency for such use. An NDI Program Plan shall be developed at the beginning of the technology development phase and shall define all NDI requirements to be adhered to throughout the system life cycle.
AMS K Non Destructive Methods and Processes Committee
A Digital Twin Framework for Structural Health Monitoring Enhanced by Physics-Based Reduced Order Modeling and Stochastic Time Series ModelsF-0079-2023-180995/16/2023
Zhou, Peiyuan, Fan, Yiming, Ju, Brian, Kopsaftopoulos, Fotis
Guidelines for the Development of Architectures for Integrated Vehicle Health Management SystemsARP6290 (Current)5/10/2023
This SAE Aerospace Recommended Practice (ARP) provides guidance when creating integrated vehicle health management (IVHM) system architecture. IVHM covers a vehicle’s monitoring and data processing functions inherent within its sub-systems, and the tools and processes used to manage and restore the vehicle health. These guidelines are drawn from experience within both defense and commercial IVHM initiatives and implementations. The document identifies a step-by-step methodology to expose functional and non-functional requirements, mature the architecture and support organizational business goals and objectives.
HM-1 Integrated Vehicle Health Management Committee
Challenges and Opportunities of Future Vehicle Diagnostics in Software-Defined Vehicles2023-01-08474/11/2023
The automotive industry changes rapidly. New players, concepts, and technologies from the Information Technology (IT) domain enter the market and software receives a high priority. Inside the vehicle, the number of components, which consist mostly of software, are increasing and more and more software-based functions are offered. In addition, High Performance Computers (HPCs) are continuing to be integrated into vehicles. These aspects lead to several challenges with current vehicle diagnostics, but also enable new opportunities in that field. However, in the specific area of vehicle diagnostics, there exists only very limited literature that considers current challenges and new possibilities for future vehicle diagnostics. Some literature deals with the general automotive system design or shows results from about five years ago. The viewpoints of an Original Equipment Manufacturer (OEM) are not included there. This paper presents results from an expert survey in order to identify what challenges and new opportunities are currently affecting vehicle diagnostics in the year 2022. The survey was conducted within the publicly-funded project Software-Defined Car (SofDCar), which is funded by the German Federal Ministry for Economic Affairs and Climate Action. The survey shows the ongoing state of the vehicle diagnostics in the industry as well as needs and ideas from the perspective of diagnostics experts. In addition, the survey results are compared with respective statements from the academic, scientific area to decrease the gap between the industry and research communities. Therefore, aspects for possible future work in the field of vehicle diagnostics can be identified. Based on that, goals beyond the survey are to think about how a concept for HPC diagnostics could look like and how it might influences an approach for future vehicle diagnostics.
Bickelhaupt, Sandra, Hahn, Michael, Nuding, Nikolai, Morozov, Andrey, Weyrich, Michael
Real Time Bearing Defect Classification Using Time Domain Analysis and Deep Learning Algorithms2023-01-00964/11/2023
Structural Health Monitoring (SHM), especially in the field of rotary machinery diagnosis, plays a crucial role in determining the defect category as well as its intensity in a machine element. This paper proposes a new framework for real-time classification of structural defects in a roller bearing test rig using time domain-based classification algorithms. Along with the bearing defects, the effect of eccentric shaft loading has also been analyzed. The entire system comprises of three modules: sensor module – using accelerometers for data collection, data processing module – using time-domain based signal processing algorithms for feature extraction, and classification module – comprising of deep learning algorithms for classifying between different structural defects occurring within the inner and outer race of the bearing. Statistical feature vectors comprising of Kurtosis, Skewness, RMS, Crest Factor, Mean, Peak-peak factor etc. have been extracted from the 1-D time series data for different defect cases. These features are then fed as input vectors to algorithms comprising of Support Vector Machines (SVM’s) and Multi-layered Perceptron (MLP) for defect classification. A dedicated hardware setup has been built to test the efficiency of the developed algorithms in real-time. These algorithms have been evaluated based on two criteria – examining the simultaneous defect classification accuracy for two sets of bearings and individually monitoring the class labels for a particular defect. It was observed that the developed framework was able to classify between different bearing defects with a classification accuracy of 97.8%.
Gorantiwar, Anish, Taheri, Saied, Zahiri, Feraidoon, Moslehi, Bijan
Aerospace & Defense Technology: April 202323AERP044/6/2023
Breathing Life into Artificial Intelligence and Next Generation Autonomous Aerospace Systems Robotic Rotational Molding Creates New Opportunities for Military and Aerospace Applications Rim-Driven Electric Aircraft Propulsion High-Speed Midwave Infrared Cameras Enable Military Test Range Tracking System What Today's Advances in Radar Technology Mean for Testing and Training Tackling Ruggedization Challenges for RF Communications in Software Defined Radios AUVSI XPONENTIAL 2023 The Blueprint for Autonomy Multi-Scale Structuring of the Polar Ionosphere Understanding a radically new sensing capability for polar ionospheric science introduced by observational evidence recently provided by the electronically steerable Resolute Bay Incoherent Scatter Radar (RISR). Stepped-Frequency Distributed Radar for Through-the-Wall Sensing A technical analysis of the effectiveness of distributed radar for through-the-wall sensing applications. Drift Improvement with Reinforcement Training of Inertial Sensors Analyzing the use of Reinforcement Learning (RL) to extend the holdover time of inertial sensors in the absence of a Global Navigation Satellite System (GNSS). Overcoming Performance Limitations of Distributed Brillouin Fiber Laser Sensors A technical analysis of the effectiveness of dis-tributed Brillouin fiber laser sensing (DBFLS) in overcoming performance limitations of existing Brillouin sensors in structural health monitoring and environmental sensing applications. Electro-Optic Materials Research Developing single photon UV detection for compact chemical and biological sensors.
Overcoming Performance Limitations of Distributed Brillouin Fiber Laser SensorsTBMG-478994/1/2023
Distributed fiber sensors are a powerful tool for structural health monitoring and environmental sensing due to their ability to remotely monitor the strain at 1,000s of locations using low-cost optical fiber. Sensors based on Brillouin scattering are uniquely suited to these tasks since they can make completely distributed, absolute measurements of strain, with a long range (>100 km), small sensing size (<1 cm), and a huge absolute dynamic range, all in standard off-the-shelf telecom fiber. These sensors function by measuring the resonance frequency of the non-linear Brillouin interaction in fiber which shifts linearly with strain and temperature.
Inflatable Space Habitats Use Sensors Embedded in Webbing for Structural Health MonitoringTBMG-473801/10/2023
Bally Ribbon Mills Bally, PA
The Preparation and Use of Thermocouples for Aircraft Gas Turbine EnginesAIR46C (Current)9/14/2022
This SAE Aerospace Information Report (AIR) reviews the precautions that must be taken and the corrections which must be evaluated and applied if the experimental error in measuring the temperature of a hot gas stream with a thermocouple is to be kept to a practicable minimum. Discussions will focus on Type K thermocouples, as defined in National Institute of Standards and Technology (NIST) Monograph 175 as Type K, nickel-chromium (Kp) alloy versus nickel-aluminium (Kn) alloy (or nickel-silicon alloy) thermocouples. However, the majority of the content is relevant to any thermocouple type used in gas turbine applications.
E-32 Aerospace Propulsion Systems Health Management
Right to RepairHRCS-N0000028/9/2022
The Health-Ready Components and Systems (HRCS) Consortium developed this policy statement to provide guidance regarding the Right to Repair. These principles apply across all mobility sectors, irrespective of the underlying asset type. Modern vehicles produce large amounts of data and are becoming increasingly complicated to repair. Right to Repair refers to the ability of private repair shops and owners to access vehicle data and service information required to effectively repair and maintain these vehicles. This statement is intended to clarify the rights of independent repair shops and owners and to review key issues relevant to this question.
Health Ready Components and Systems
Data OwnershipHRCS-N0000018/9/2022
The Health-Ready Components and Systems (HRCS) Consortium developed this policy statement to provide guidance regarding the ownership and use of operating data. These principles apply across all mobility sectors, irrespective of the underlying asset type. Sophisticated components installed in modern vehicles can store and transmit large volumes of data regarding the operating condition of individual components, systems, or the entire vehicle. This data is valuable for predictive and comparative purposes in a variety of contexts. This statement is intended to clarify the rightful owner of that operating data, as well as elucidate some of the key issues relevant to this question.
Health Ready Components and Systems
Hierarchical Bayesian Networks for Predicting the Structural Behavior of Coupled Systems2022-01-09426/15/2022
Simulations play an important role in the continuing effort to reduce development time and risks. However, large and complex models are necessary to accurately simulate the dynamic behavior of complex engineering systems. In recent years, the use of data-driven models based on machine learning (ML) algorithms has become popular for predicting the structural dynamic behavior of mechanical systems. Due to their advantages in capturing non-linear behavior and efficient calculation, data-driven models are used in a variety of fields like uncertainty quantification, optimization problems, and structural health monitoring. However, the black box structure of ML models reduces the interpretability of the results and complicates the decision-making process. Hierarchical Bayesian Networks (HBNs) offer a framework to combine expert knowledge with the advantages of ML algorithms. In general, Bayesian Networks (BNs) allow connecting inputs, parameters, outputs, and experimental data of various models to predict the overall system-level dynamic behavior. This characteristic of BNs enables a divide and conquer approach. Hence, complex engineering systems can be split into more easily describable subsystems. HBNs are an extension of BNs that can use knowledge about the structure of the data to introduce a bias that can contribute to improving the modelling result. In this work, an approach to design a HBN is presented where each model in the network can be a parametric reduced finite-element models. The influence of the hierarchical approach is evaluated by comparing a HBN and a BN of the model from the Sandia structural dynamics challenge.
Hülsebrock, Moritz, Schmidt, Hendrik, Stoll, Georg, Atzrodt, Heiko
Active-Sensing Acousto-Ultrasound-based Rotorcraft Structural Health Monitoring via Adaptive Functional Series ModelsF-0078-2022-12865/10/2022
In this work, the experimental assessment of the damage diagnosis performance of a full-scale rotorcraft blade is performed via stochastic time-varying time series models in the context of active sensing acousto-ultrasound guided wave-based damage detection and identification scheme. Ultrasonic guided waves, that are dispersive in nature, are represented via functional series time-varying autoregressive (FS-TAR) models. Next, the estimated time-varying model parameters are employed within a statistical decision making framework to tackle damage detection and identification under predetermined type I error probability levels. Damage detection and identification based on coefficients of projection (COP) as well as time-varying model parameters are shown. Both damage intersecting and non-intersecting paths are considered in a full-scale rotorcraft blade as well as in an aluminum plate in pitch-catch configuration for the complete experimental assessment. The detailed damage diagnosis results are presented and the method's robustness, effectiveness, and limitations are discussed.
Kopsaftopoulos, Fotis, Ahmed, Shabbir, Zhou, Peiyuan
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