Implications of an open system approach to vehicle health management

Followell, D.; Gilbertson, D. D.; Keller, K.

doi:10.1109/aero.2004.1368189

Cited by 14 publications

(8 citation statements)

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“…A key element of the Ops Lab is the open software reference architecture based on the Open System Architecture for Condition Based Maintenance (OSACBM) Machinery Information Open System Alliance (MIMOSA) standard [6], [7]. Boeing has been an active participant in the OSACBM development and is continuing to support its maturation along with other industry participants.…”

Section: Open Reference S/w Reference Architecture and Component Librmentioning

confidence: 99%

Health Management Engineering Environment and Open Integration Platform

Keller

Baldwin

Ofsthun

et al. 2007

2007 IEEE Aerospace Conference

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The Phantom Works' role at The Boeing Company is to facilitate the development and transition of emerging technologies into Boeing products to provide a competitive advantage. 12 Phantom Works is developing a Health Management Engineering Environment (HMEE) to foster and transition health management technology from industry, academia and government technology base to Boeing Products. The HMEE consists of a:• Program Analysis and Modeling Environment, • Development Environment and an • Operations Environment.The Program Analysis and Modeling Environment provides the processes and tools to do performance/cost driver analysis, root cause analysis, solution formulation, and cost/benefit trade studies including fleet simulation modeling. The Development Environment provides the design processes and synthesis tools required to develop solutions.The Operations Environment provides the processes and tools to integrate, test and mature the hardware and software elements of the health management solution. Major elements of the HMEE are an open software reference architecture, access to hardware laboratories to characterize degraded components/ subsystems, a data repository to store and access laboratory and field data, and hardware and software to support end to end technology demonstrations. It will support progressive levels of integration and demonstration from a single technology on a PC to the integration of this technology into a complete IVHM system with hardware in the loop as needed to provide vehicle data and address integration into vehicle avionics or a ground support system. Significant elements of the HMEE are in place with additional expansion and integration ongoing. The Boeing Phantom Works IVHM team is acquiring hardware, tools and algorithms from a number of suppliers to create a pool of resources for system level, end to end demonstrations of IVHM applications and development tools.

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Section: Open Reference S/w Reference Architecture and Component Librmentioning

confidence: 99%

Health Management Engineering Environment and Open Integration Platform

Keller

Baldwin

Ofsthun

et al. 2007

2007 IEEE Aerospace Conference

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“…Nearly all systems, especially more complex aerospace systems, fall short of the ideal system that could accurately and unambiguously drive replacement or repair actions with no additional testing required. Inherent diagnostic ambiguity and conditions that lead to false alarms results in extensive troubleshooting, parts swapping and shotgun maintenance which increases in turnaround time and maintenance costs [11]. This of course has an impact on further development for the diagnostic reasoners, initiating several different techniques such as Model Based Reasoning (MBR) or data driven methods [12].…”

Section: A Detection and Diagnostic Systemmentioning

confidence: 99%

Multi-Domain Modeling and Simulation of an Aircraft System for Advanced Vehicle-Level Reasoning Research and Development

Khan¹,

Eker²,

Sreenuch³

et al. 2014

IJACSA

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Abstract-In this paper, we describe a simulation based health monitoring system test-bed for aircraft systems. The purpose of the test-bed is to provide a technology neutral basis for implementing and evaluation of reasoning systems on vehicle level and software architecture in support of the safety and maintenance process. This simulation test-bed will provide the sub-system level results and data which can be fed to the VLRS to generate vehicle level reasoning to achieve broader level diagnoses. This paper describes real-time system architecture and concept of operations for the aircraft major sub-systems. The four main components in the real-time test-bed are the aircraft sub-systems (e.g. battery, fuel, engine, generator, heating and lighting system) simulation model, fault insertion unit, health monitoring data processing and user interface. In this paper, we adopted a component based modelling paradigm for the implementation of the virtual aircraft systems. All of the fault injections are currently implemented via software. The fault insertion unit allows for the repeatable injection of faults into the system. The simulation test-bed has been tested with many different faults which were undetected on system level to process and detect on the vehicle level reasoning. This article also shows how one system fault can affect the overall health of the vehicle.

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“…This type of information fusion can serve as the basis for developing advanced diagnostic and prognostic algorithms for legacy, current, and nextgeneration commercial and military aircraft.1 23 1 1 1-4244-1488-1/08/$25.00 ©2008 IEEE. 2 IEEEAC paper # 1081, Version3.1, Updated November 14, 2007 3Disclaimer Notice: This material is based upon work supported by the Naval Air Warfare Center under Contract No. N00421-05-C-0140.…”

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confidence: 99%

Multi Source Data Integration for Aircraft Health Management

Ortiz

Clark

Babbar

et al. 2008

2008 IEEE Aerospace Conference

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Modem aircraft are capable of generating and collecting massive quantities of data from flight recorders, maintenance reports, logistics, and mission-readiness reporting systems. Current aircraft system health management schemes are developed based on data sources consisting of the aircraft's system operational conditions or maintenance and repair actions; however, crucial information regarding flight condition and situational parameters are often disregarded or used in a limited sense for diagnostics due to data accessibility issues or what can be an overwhelming volume of time-series data that is collected from modem onboard aircraft data recorders. With improved access to multiple sources of aircraft data, diagnostics and prognostics capabilities may be improved allowing flight crews, engineering, maintenance, and logistics users of an interoperable data system to make more informed decisions. Improved knowledge of the actual aircraft condition, usage and component life monitoring can significantly reduce aircraft Operations and Support (O&S) costs. In addition, integrating multiple sources of aircraft data can reduce Total Ownership Cost (TOC), enhance mission safety and improve aircraft performance. There is a need to develop a multi-source data integration architecture for analyzing vast quantities of disparate data obtained from both onboard and off-board data sources. The multi-source data integration will be able to accurately combine disparate data and establish interconnectivity between distinct data sources to significantly improve data interoperability across multiple data sources. This type of information fusion can serve as the basis for developing advanced diagnostic and prognostic algorithms for legacy, current, and nextgeneration commercial and military aircraft.1 23 1 1 1-4244-1488-

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Implications of an open system approach to vehicle health management

Cited by 14 publications

References 0 publications

Health Management Engineering Environment and Open Integration Platform

Health Management Engineering Environment and Open Integration Platform

Multi-Domain Modeling and Simulation of an Aircraft System for Advanced Vehicle-Level Reasoning Research and Development

Multi Source Data Integration for Aircraft Health Management

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