5,550 research outputs found

    The challenge of advanced model-based fdir techniques for aerospace systems: the 2011 situation

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    For aerospace systems, advanced model-based Fault Detection, Identification, and Recovery (FDIR) challenges range from predesign and design stages for upcoming and new programs up to the improvement of the performance of in-service flying systems. However, today, their application to real aerospace world has remained extremely limited. The paper underlines the reasons for a widening gap between the advanced scientific FDIR methods being developed by the academic community and technological solutions demanded by the aerospace industry

    No Fault Found events in maintenance engineering Part 2: Root causes, technical developments and future research

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    This is the second half of a two paper series covering aspects of the no fault found (NFF) phenomenon, which is highly challenging and is becoming even more important due to increasing complexity and criticality of technical systems. Part 1 introduced the fundamental concept of unknown failures from an organizational, behavioral and cultural stand point. It also reported an industrial outlook to the problem, recent procedural standards, whilst discussing the financial implications and safety concerns. In this issue, the authors examine the technical aspects, reviewing the common causes of NFF failures in electronic, software and mechanical systems. This is followed by a survey on technological techniques actively being used to reduce the consequence of such instances. After discussing improvements in testability, the article identifies gaps in literature and points out the core areas that should be focused in the future. Special attention is paid to the recent trends on knowledge sharing and troubleshooting tools; with potential research on technical diagnosis being enumerated

    No Fault Found events in maintenance engineering Part 1: Current trends, implications and organizational practices

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    This paper presents the first part of a state of the art review on the No Fault Found (NFF) phenomenon. The aim has been to compile a systematic reference point for burgeoning NFF literature, and to provide a comprehensive overview for gaining an understanding of NFF knowledge and concepts. Increasing systems complexities have seen a rise in the number of unknown failures that are being reported during operational service. Units tagged as ‘NFF’ are evidence that a serviceable component was removed, and attempts to troubleshoot the root cause have been unsuccessful. There are many reasons on how these failures manifest themselves and these papers describe the prominent issues that have persisted across a variety of industrial applications and processes for decades. This article, in particular, deals with the impact of NFF from an organizational culture and human factors point of view. It also highlights recent developments in NFF standards, its financial implications and safety concerns

    Research on computer aided testing of pilot response to critical in-flight events

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    Experiments on pilot decision making are described. The development of models of pilot decision making in critical in flight events (CIFE) are emphasized. The following tests are reported on the development of: (1) a frame system representation describing how pilots use their knowledge in a fault diagnosis task; (2) assessment of script norms, distance measures, and Markov models developed from computer aided testing (CAT) data; and (3) performance ranking of subject data. It is demonstrated that interactive computer aided testing either by touch CRT's or personal computers is a useful research and training device for measuring pilot information management in diagnosing system failures in simulated flight situations. Performance is dictated by knowledge of aircraft sybsystems, initial pilot structuring of the failure symptoms and efficient testing of plausible causal hypotheses

    Assessment team report on flight-critical systems research at NASA Langley Research Center

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    The quality, coverage, and distribution of effort of the flight-critical systems research program at NASA Langley Research Center was assessed. Within the scope of the Assessment Team's review, the research program was found to be very sound. All tasks under the current research program were at least partially addressing the industry needs. General recommendations made were to expand the program resources to provide additional coverage of high priority industry needs, including operations and maintenance, and to focus the program on an actual hardware and software system that is under development

    A review of model based and data driven methods targeting hardware systems diagnostics

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    System health diagnosis serves as an underpinning enabler for enhanced safety and optimized maintenance tasks in complex assets. In the past four decades, a wide-range of diagnostic methods have been proposed, focusing either on system or component level. Currently, one of the most quickly emerging concepts within the diagnostic community is system level diagnostics. This approach targets in accurately detecting faults and suggesting to the maintainers a component to be replaced in order to restore the system to a healthy state. System level diagnostics is of great value to complex systems whose downtime due to faults is expensive. This paper aims to provide a comprehensive review of the most recent diagnostics approaches applied to hardware systems. The main objective of this paper is to introduce the concept of system level diagnostics and review and evaluate the collated approaches. In order to achieve this, a comprehensive review of the most recent diagnostic methods implemented for hardware systems or components is conducted, highlighting merits and shortfalls

    Health monitoring of Gas turbine engines: Framework design and strategies

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    An analysis of the application of AI to the development of intelligent aids for flight crew tasks

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    This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research

    System level airborne avionics prognostics for maintenance, repair and overhaul

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    The aim of this study is to propose an alternative approach in prognostics for airborne avionics system in order to enhance maintenance process and aircraft availability. The objectives are to analyse the dependency of avionic systems for fault propagation behaviour degradation, research and develop methods to predict the remaining useful life of avionics Line Replaceable Units (LRU), research and develop methods to evaluate and predict the degradation performances of avionic systems, and lastly to develop software simulation systems to evaluate methods developed. One of the many stakeholders in the aircraft lifecycle includes the Maintenance, Repair and Overhaul (MRO) industry. The predictable logistics process to some degree as an outcome of IVHM gives benefit to the MRO industry. In this thesis, a new integrated numerical methodology called ‘System Level Airborne Avionic Prognostics’ or SLAAP is developed; looking at a top level solution in prognostics. Overall, this research consists of two main elements. One is to thoroughly understand and analyse data that could be utilised. Secondly, is to apply the developed methodology using the enhanced prognostic methodology. Readily available fault tree data is used to analyse the dependencies of each component within the LRUs, and performance were simulated using the linear Markov Model to estimate the time to failure. A hybrid approach prognostics model is then integrated with the prognostics measures that include environmental factors that contribute to the failure of a system, such as temperature. This research attempts to use data that is closest to the data available in the maintenance repair and overhaul industry. Based on a case study on Enhanced Ground Proximity Warning System (EGPWS), the prognostics methodology developed showed a sufficiently close approximation to the Mean Time Before Failure (MTBF) data supplied by the Original Equipment Manufacturer (OEM). This validation gives confidence that the proposed methodology will achieve its objectives and it should be further developed for use in the systems design process
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