Browse Topic: Vehicle health management (VHM)
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.
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.
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The complex dynamics of rotorcraft structures under varying operational and environmental conditions demand the development of accurate and robust-to-uncertainties structural health monitoring (SHM) approaches. The inherent uncertainty within monitoring data makes it difficult for conventional methods to accurately and robustly detect and quantify damage without the need for a large number of data sets. In addition, due to the time-varying nature of rotorcraft operations, such conventional metrics might still fail even with abundance of data. In this paper, we propose a unified probabilistic damage detection and quantification framework for active-sensing, guided-wave SHM that focuses on monitoring rotorcraft structural "hotspots". The proposed framework involves three stages: The first stage incorporates statistical damage detection based on stochastic non-parametric time series (NP-TS) models of ultrasonic wave propagation signals within a hotspot sensor network configuration. The second stage involves the statistical path selection, where a NP-TS representation is used for the sole purpose of identifying damage-intersecting signal (wave propagation) paths, that is the paths that are most sensitive to damage, in order to use them in the subsequent damage quantification stage. That last stage achieves probabilistic damage quantification, where the results of the NP-TS models are used to train Bayesian Gaussian Process regression and classification models. This unified framework ensures accurate and robust damage detection and quantification in a data-efficient manner since only damage-intersecting paths are selected and used in the analysis. The performance of the proposed framework is compared to that of conventional state-of-the-art damage indices (DIs) in detecting and quantifying simulated damage in two representative coupons: a Carbon Fiber Reinforced Polymer (CFRP) coupon and a stiffened aluminum (Al) panel. It is shown that the proposed framework outperforms conventional DI-based active-sensing guided-wave SHM methods.
Advancements in Damage Tolerant Airframe Structures in combination with Structural Health Monitoring (SHM) have created an opportunity to exploit the synergies in these technologies to change the paradigm for Airframe Life Management for future Aircraft. In the last decade or more, Sikorsky has validated multiple production helicopter Airframes using Damage and Flaw Tolerant certification requirements. The experience of the authors of this paper contributed to the recent joint services and industry development of the Rotorcraft Structural Integrity Program (RSIP as specified in MIL-STD-3063) for design of future military rotorcraft. In addition, Sikorsky has also developed a range of technologies relevant to SHM to reduce over-inspection and maintenance to drive increased operational availability. Combined, these developments will allow new Airframe designs to meet the US Army's new requirements for Maintenance Free Operational Periods (MFOP), for example 200 flight hours for the Future Vertical Lift (FVL) rotorcraft.
A multidisciplinary team performing under the Aircraft and Aircrew Protection (A&AP) project between Sikorsky and the US Army Combat Capabilities Development Command Aviation & Missile Center (CCDC AvMC) successfully demonstrated the assembly of a full-scale fiber-optic-instrumented composite aircraft structure assembly. Through a building-block progression from test coupons to sub-scale to full-scale assemblies, the team developed practical strategies to maximize fiber optic survival rate and utility. Ultimately, the team defined and implemented five key elements to enable successful fiber optic strain sensor embedment in structural composites: thoughtful arrangement of the fiber optic network, controlled placement of strain sensors and excess fiber in the laminate, accommodation of minimum fiber optic bend radii, encapsulation of the fiber at the egress point from the composite laminate, and protection of the connector termination. These elements allow for a robust strain-sensing network that can be utilized for damage detection and advanced structural health monitoring.
Existing Structural Health Monitoring (SHM) techniques generally depend on deterministic parameters in order to detect, localize, and quantify damage. This limits the applicability of such systems in real-life situations, where stochastic, time-varying structural response, as well as complex damage types immersed in operational/environmental uncertainties are almost always encountered. Thus, there lies a need for the proposal of statistical quantities and methods for assessing structural health. That is, a holistic probabilistic SHM framework involving damage detection, localization, and quantification, is due if such systems are to become standard on VTOL platforms. In this work, a novel probabilistic approach for active-sensing acousto-ultrasound SHM targeting damage detection and quantification is proposed based on stochastic non-parametric time series representations. Statistical signal processing techniques are used to formulate statistical hypothesis tests, based on which a decision can be made to whether a component is healthy or damaged within pre-defined confidence bounds. The methods presented herein can also be used for damage quantification. The proposed framework is first applied to a notched Aluminum coupon with different damage sizes within an active-sensing, local "hot-spot" monitoring framework. After that, experimental data collected over a stiffened Aluminum panel, representing a sub-scale fuselage component, is analyzed using the probabilistic framework for validation of the proposed methods on more real-life structures. Results show the advantage of the proposed techniques in citing confidence to the decision-making process when compared with state-of-the-art damage indicators. In addition, insights into damage localization within a probabilistic framework are also presented, which may be used as a preliminary step to damage localization
Guided-wave-based acousto-ultrasound structural health monitoring (SHM) methods have attracted the interest of the SHM community as guided waves can travel long distances without significant dissipation and are capable of detecting small damage sizes of several types. However, when subject to changing environmental and operational conditions (EOC), guided-wave-based methods may give false indications of damage as they exhibit increased sensitivity to varying EOC. In order to improve the reliability and enable the large-scale applicability of these methods, and to build a robust SHM system, it is necessary to quantify the uncertainty in guided wave propagation due to changing EOC. In this paper, a rigorous investigation on the uncertainty involved in the propagation of Lamb waves due to the variation in temperature and material properties of nominally-identical structures has been performed both numerically and experimentally. A high fidelity finite element model is established to study the effect of small temperature perturbation on the S0 and A0 modes of Lamb waves and the associated uncertainty is quantified. Then experiments are performed under ambient laboratory temperature variations during an eleven day period. The experimental results have indicated that temperature variations as small as 0.5°C may result variations in the amplitude of Lamb waves and affect the damage index. Then uncertainty due to the variation in material properties has been considered by taking into account the statistical Gamma distributed dependency between Young's modulus and Poisson ratio jointly and the associated variation in the damage index is also investigated.
ABSTRACT Structural usage and loads monitoring can enhance safety, by identifying unusual usage patterns by individual aircraft or sub-fleets (e.g. operators, missions, or locations), and provide benefit to operators by enabling extended retirement times of life-limited components. While flight regime recognition (RR) algorithms have been demonstrated and partially validated, the use of existing onboard generic RR software provided in legacy Health and Usage Monitoring Systems (HUMS) remains a challenge for achieving airworthiness approval of retirement time extensions using archived fleet data in compliance with existing guidance, such as the U.S. Army ADS-79E Handbook for Condition-Based Maintenance. The U.S. Army and Sikorsky Aircraft, a Lockheed Martin Company, conducted a joint Fatigue Life Management (FLM) project to configure, validate, and apply processes and methods for extending the retirement times of six high-value components for the Army's Black Hawk helicopter fleet, which is equipped with a state-of-the-art HUMS, known as the Integrated Vehicle Health Management System (IVHMS). A RR post-processing process for addressing key technical challenges associated with the use of legacy onboard RR software was configured and verified against existing UH-60 flight test data. These post-processing methods were then applied to a two year population of UH-60 fleet data to calculate usage statistics for individual aircraft within several sub-fleet populations associated with either different global deployment locations and/or missions. The fleet statistics were then used by the Army Aviation Engineering Directorate (AED) to establish a conservative update to the existing usage spectrum, which was applied by Sikorsky to calculate updated retirement times. The focus of this paper is on the successful configuration and verification of RR software used in compliance with ADS-79E to establish UH-60 A/L/M IVHMS fleet usage statistics. A companion paper, also published within proceedings of the AHS 74th Annual Forum, provides details on using the fleet statistics to define an updated UH-60 usage spectrum.
ABSTRACT A combination of nondestructive evaluation (NDE) and structural health monitoring technique has been used to detect and localize in situ damage in X-COR sandwich composites. The NDE techniques, flash thermography and ultrasonic C-Scan, were used, and the inspection results showed promising capabilities as well as their inherent limitations. Subsequently, a guided wave based active interrogation technique was used to enable real-time damage detection and localization capabilities. Macro fiber composite and piezoelectric wafers were used for actuation and sensing, and the interaction of guided waves with the primary damage modes, delaminations and foam core separations, were studied. The results showed that delaminations lead to the guided wave mode conversion phenomenon within the material discontinuity area. A multidimensional signal processing technique, which was developed with a real-time and reference-free perspective, was used to analyze the converted wave modes in the time-space domain for damage localization. The results indicate that the converted wave mode is an effective indicator of in situ damage, especially when the received signal contains wave modes transmitted from multiple source locations.
ABSTRACT We present a model-based structural health monitoring approach to mitigate fatigue damage of critical rotorcraft components in real time. The overall concept is demonstrated with aerodynamic loads for a utility helicopter similar to the UH-60 Black Hawk and a structural model of the main rotor's pitch link. The potential of reducing computational costs associated with modeling by utilizing a quasi-static analysis was considered in this study, however, it was concluded that a dynamic analysis was indeed necessary to accurately capture the inertial effects of the vehicle. Maximum stress results extracted from the model can be sent to a controller to apply a load alleviation control scheme to appropriately modify the input to the rotorcraft controls and reduce air loads to the vehicle. The modeling, analysis, and load alleviation process were also automated. We also completed an investigation into the impact of vehicle control input parameters on stress experienced by the component.
ABSTRACT Lives of fatigue critical components for Army aircraft are typically established based on component strength from ground test, loads for each regime from flight test, and aircraft usage in each regime from engineering and aircrew judgement. This paper documents the updates to the spectrum for the large Army UH-60 fleet based on usage monitored by the Integrated Vehicle Health Management System (IVHMS). IVHMS and subsequent post processing uses aircraft parameters to identify the regime at any given time. The recognized regimes are summed to generate a spectrum of time or occurrences in each regime. The Partial Regime Recognition Spectrum used here identified specific regimes that had a significant effect on part life and concentrated on identifying only those regimes. Time in other ‘unrecognized’ regimes was prorated based on the legacy spectrum. The SUMS system is validated using scripted flights, as well as by cross checking against a spectrum generated via pilot interviews. Six components were addressed with life changes ranging from 80% to 600% of the legacy life.
ABSTRACT This paper presents an original combined approach to shape-sensing and structural health monitoring of helicopter rotors. It is based on the measurement of strain in a limited number of points over the blade surface. The Shape-Sensing algorithm is modal-based and capable of reconstructing nonlinear, moderate lag, flap and torsion deflections. Two Structural Health Monitoring algorithms are presented, one in the time domain and the other in the frequency domain. Both are based on the analysis of the discrepancies between the strains arising in the damaged and the undamaged blades. Two damage types have been considered: a mass unbalance and a localized stiffness reduction. Both Shape Sensing and Structural Health Monitoring capabilities have been tested by numerical simulation using a multibody dynamic solver for general nonlinear comprehensive aeroelastic analysis.
ABSTRACT The U.S. Army traditionally has used a time-based, on-condition maintenance paradigm that relies on at-aircraft inspections and periodic in-depth phased inspections to determine condition and ensure airworthiness. The result is a significant maintenance burden, both scheduled and unscheduled, and excessive aircraft downtime. The objective of the Aviation Development Directorate (ADD) and Sikorsky Aircraft Corporation (SAC) Capability-Based Operations and Sustainment Technology-Aviation (COST-A) program was to develop and demonstrate an integrated set of high value diagnostics, prognostics, and system health management technologies that reduce scheduled inspections and preventive maintenance while enhancing safety. More than two dozen Prognostics and Health Management (PHM) technologies across six primary rotorcraft systems (propulsion, drive train, airframe/structural, rotor, electrical, and vehicle management) were matured to technology readiness level (TRL) 6. These technologies were integrated into a prototype laboratory on-board system built around the Integrated Vehicle Health Management Unit (IVHMU) currently installed in all UH-60 Black Hawk aircraft and successfully demonstrated to perform concurrently in representative simulated flight scenarios, using playback data from healthy and faulty components. A subset of these technologies, jointly selected by ADD and SAC, was flight tested on an HH-60M aircraft to further reduce the risk of transitioning these technologies. This paper summarizes the flight-test efforts, with a focus on results obtained for the technologies under test. Upon deployment to the UH-60 aircraft fleet, these PHM technologies can enable the Army to transition to a more effective automated condition-based maintenance (CBM) paradigm.
The U.S. Army traditionally has used a time-based, on-condition maintenance paradigm that relies on at-aircraft inspections and periodic in-depth phase inspections to determine condition and ensure airworthiness. The result is a significant maintenance burden, both scheduled and unscheduled, and excessive aircraft downtime. The objective of the Aviation Development Directorate (ADD) and Sikorsky Aircraft Corporation (SAC) Capability-Based Operations and Sustainment Technology-Aviation (COST-A) program was to develop and demonstrate an integrated set of high value diagnostics, prognostics, and system health management technologies that reduce scheduled inspections and preventive maintenance while enhancing safety. More than two dozen Prognostics and Health Management (PHM) technologies across six primary rotorcraft systems (propulsion, drive train, airframe/structural, rotor, electrical, and vehicle management) were matured to technology readiness level (TRL) 6. These technologies were integrated into a prototype laboratory on-board system built around the Integrated Vehicle Health Management Unit (IVHMU) currently installed in all UH-60 Black Hawk aircraft and successfully demonstrated to perform concurrently in representative simulated flight scenarios, using playback data from healthy and faulty components. A subset of these technologies, jointly selected by ADD and SAC, has been prepared for an upcoming flight test on a UH-60M aircraft to further reduce the risk of transitioning these technologies. This paper summarizes the flight-test preparation efforts, including the implementation of associated algorithms within a representative integrated on-aircraft and ground-based system software environment. Upon deployment to the UH-60 aircraft fleet, these PHM technologies can enable the Army to transition to a condition-based maintenance (CBM) paradigm.
The US Navy has long relied on time-based maintenance to sustain the airworthiness of military aircraft. Historically, these practices have contributed to significant maintenance burden. The Integrated Hybrid Structural Management System (IHSMS) program is developing structural health management (SHM) capabilities for the CH-53K rotorcraft to move beyond conventional flight-hour based maintenance towards a reliability-based maintenance framework. IHSMS incorporates a number of wired and wireless sensor technologies and analytical methods into a modular SHM system that integrates directly with the aircraft's existing Integrated Vehicle Health Management System (IVHMS). IHSMS is being developed for transition to the CH-53K heavy lift helicopter while being designed for adaptability to other Navy and Marine Corps applications. This paper provides an overview of the IHSMS program, the design development approach, and execution strategy adopted by Sikorsky and US Navy to develop and mature an integrated rotor and airframe SHM system to a Technology Readiness Level (TRL) 6.
Outlier or anomaly detection refers to the task of identifying abnormal or inconsistent patterns from a dataset. While they may seem to be undesirable entities, identifying them has many potential applications in fraud and intrusion detection, medical research, and safety-critical vehicle health management. Outliers can be detected using supervised, semi-supervised, or unsupervised techniques. Unsupervised techniques do not require labeled instances for detecting outliers. Supervised techniques require labeled instances of both normal and abnormal operation data for first building a model (e.g., a classifier), and then testing if an unknown data point is a normal one or an outlier. The model can be probabilistic such as Bayesian inference or deterministic such as decision trees, Support Vector Machines (SVMs), and neural networks. Semi-supervised techniques only require labeled instances of normal data. Hence, they are more widely applicable than the fully supervised ones. These techniques build models of normal data and then flag outliers that do not fit the model.
ABSTRACT Very little success has been reported in the literature in developing diagnostic systems trained on simulated data that can accurately describe the real situation. Furthermore, no studies attempting automated structural health monitoring (SHM) system performance qualification are available. A diagnostic algorithm based on an artificial neural network and trained with finite element simulated strains has been verified during repeated fatigue crack growth tests on metallic helicopter fuselage panels. Strain measures from a network of fiber Bragg gratings are provided as input to the diagnostic system, allowing fatigue crack damage identification. Anomaly detection performances have been evaluated with reference to the recent Aerospace Recommended Practice (ARP-6461) and the Recommended Practice for a Demonstration of Nondestructive Evaluation Reliability on Aircraft Production Parts, providing a SHM system qualification in terms of minimum detectable crack length, based on reliability-confidence curves. In particular, repeated fatigue crack growth tests on metallic aerospace panels allowed the estimation of the probability of detection as a function of crack length. Furthermore, a numerical model of the monitored structure has been used for the generation of virtual specimens, thus enabling the model-assisted probability of detection assessment.
ABSTRACT A novel, robust, directional transducer design to be used in guided-wave (GW) structural health monitoring (SHM) applications is presented. The paper describes the design and preliminary fabrication of a novel piezoelectric-fiber-based transducer to be used in structural integrity monitoring schemes. The work proposed here aims to extend frequency steered acoustic transducers (FSATs) concept so to develop a new, robust piezocomposite actuator. This new transducer aims to leverage the advanced design of the FSAT concept, and the durability and robustness associated with piezoelectric fibers–based constructions. This new actuator performs even in harsh environments, can conform to curved surfaces and is suitable to application to metal and composite components of the kind typically found in rotorcraft structures.
ABSTRACT The U.S. Army traditionally has used a time-based, on-condition maintenance paradigm that relies on at-aircraft inspections and periodic in-depth phase inspections to determine condition and ensure airworthiness. The result is a significant maintenance burden, both scheduled and unscheduled, and excessive aircraft downtime. The objective of the Aviation Development Directorate-Aviation Applied Technology Directorate (ADD-AATD) and Sikorsky Aircraft Corporation (SAC) Capability-Based Operations and Sustainment Technology-Aviation (COST-A) project was to develop and demonstrate an integrated set of high value diagnostics, prognostics, and system health management technologies that reduce scheduled inspections and preventive maintenance while enhancing safety. More than two dozen Prognostics and Health Management (PHM) technologies across six primary rotorcraft systems (propulsion, drive train, airframe/structural, rotor, electrical, and vehicle management) were matured to TRL-6. These technologies were integrated into a prototype laboratory on-board system built around the Integrated Vehicle Health Management Unit (IVHMU) currently installed in all UH-60 Black Hawk aircraft and successfully demonstrated to perform concurrently in representative simulated flight scenarios, using playback data from healthy and faulty components. These PHM technologies can enable the Army to transition to a condition-based maintenance (CBM) paradigm. This paper summarizes the overall Validation and Verification (V&V) approach, demonstration results, and additional details of technologies that demonstrated the most promise for near-term transition. COST-A work is on-going to further mature a subset of these technologies through flight testing.
Sustainment Operations rely on reliability centered maintenance approaches to determine component retirement regardless of actual remaining useful life. With maintenance actions accounting for a significant portion of overall operating costs, operators seek approaches that maximize service intervals. Integrated Vehicle Health Management concepts afford an adaptive approach that can reduce the frequency of required maintenance actions based on proactively managing the damage incurred during flight operations. Tactics to gain airworthiness approval for extending remaining useful life and instructions for maintaining continued airworthiness are proposed. Techniques to identify, quantify, substantiate, and validate component failure rates for basic flight maneuvers are discussed. Finally, a pilot cueing system and the procedures for recommending pilot actions to manage health during flight operations are presented.
Airworthiness Approval of a Health and Usage Monitoring System as described in Miscellaneous Guidance 15 of the FAA's Advisory Circular 27-1B requires emphasis be placed on the certification requirements and their relationship to the design solution as it matures during the systems development process. A candidate Integrated Vehicle Health Management (IVHM) System-of-Systems (SoS) architecture is proposed in which the vertical lift segment and automated information systems are integrated with the sustainment processes. Next generation ground and support processes are introduced and methods used to substantiate reliability, availability, maintainability, and cost (RAM-C) using discrete event simulations based on market specific design reference missions are examined. A step-by-step system design process, including techniques to allocate data manipulation, condition monitoring, health assessments, and prognostics functionality to on-board and off-board system segments from concept design through sustainment with emphasis on certification is presented.
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