Integrated Management of System Health in Space Applications

Reichard, Karl; Crow, Eddie C.; Bair, Tami L

doi:10.1109/rams.2007.328098

Cited by 15 publications

(16 citation statements)

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“…The algorithms used in eCM are based on the MSET model developed at Argonne National Laboratory for monitoring NPPs. Researchers at NASA are particularly interested in PHM and automatic reconfiguration for space vehicles, from launch site ground equipment (Ren et al 2011) to reconfigurable control and mission planning (Liang et al 2010b) to unmanned missions (Reichard et al 2007). …”

Section: Avionics and Aerospace Systemsmentioning

confidence: 99%

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

Coble¹,

Ramuhalli²,

Bond³

et al. 2012

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Recent years have seen a resurgence of nuclear power worldwide, with interest in extending the operating life of the approximately 436 reactors currently in service (as of March, 2012), 61 new reactors being constructed, and as many as 162 under consideration. Renewed worldwide interest in nuclear power has been somewhat tempered by the March 2011 incident at Fukushima Dai-ichi in Japan. However, nuclear power is still considered a key element in meeting future worldwide sustainable energy, energy security, and emissions goals. Currently, three separate thrusts to safe and economical nuclear power development for energy security are being pursued in the United States: (i) longer term operation for the legacy fleet, from 40-60 and possibly 60-80 years; (ii) near-term new nuclear plants with a 60-year design life; and (iii) small modular reactors, which are expected to employ light water reactor technology at least in the medium term. Within these activities, attention is turning to enhanced methods for plant component and structural health management.The operating U.S. fleet includes 104 light water reactors. In addition, there are now (as of May 2012) four new nuclear power plants (AP-1000 plants) under construction in the United States, and two delayed plants are being completed by the Tennessee Valley Authority. There is also interest in the United States in small modular reactors (SMRs), which could be easier to match to existing grid infrastructure and which could replace aging coal fired plants. The current low price for natural gas presents a challenge to the economics of nuclear power, at least in the short term; however, some recent studies have demonstrated that nuclear generation will be competitive in the longer term (at least in some markets) when anticipated escalation in gas prices and the cost of building, operating, and maintaining gas-fired plants are considered over those same time periods.This report reviews the current state of the art of prognostics and health management (PHM) for nuclear power systems and related technology currently applied in field or under development in other technological application areas, as well as key research needs and technical gaps for increased use of PHM in nuclear power systems. The historical approach to monitoring and maintenance in nuclear power plants (NPPs), including the Maintenance Rule for active components and Aging Management Plans for passive components, are reviewed. An outline is given for the technical and economic challenges that make PHM attractive for both legacy plants through Light Water Reactor Sustainability (LWRS) and new plant designs. There is a general introduction to PHM systems for monitoring, fault detection and diagnostics, and prognostics in other, non-nuclear fields. The state of the art for health monitoring in nuclear power systems is reviewed. A discussion of related technologies that support the application of PHM systems in NPPs, including digital instrumentation and control systems, wired and wireless sensor techno...

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Section: Avionics and Aerospace Systemsmentioning

confidence: 99%

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

Coble¹,

Ramuhalli²,

Bond³

et al. 2012

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“…As an integrated approach, the IVHM system will improve the isolation of the root causes of failures as well as facilitating improved decision making throughout the lifecycle. Although most authors see IVHM as a reliability and maintainability concept, and some link IVHM applications with automated logistics coordination [7], [16], [17] there are those who see the ultimate instantiation of IVHM as a competitive proposition for aftercare service providers [1], [10]. Such authors refer to the increased viability of performance-based arrangements through IVHM however this concept does not appear in any of the definitions.…”

Section: Definition Of Ivhmmentioning

confidence: 99%

“…Baroth et al [12] give an overview of the leading applications across the automotive, space, military and commercial aviation sectors while Janasak and Behshears [2] discuss health management systems available for consumer products, including both vehicle and non-vehicle systems. Similarly, Reichard et al [7] provide a list of military projects in which the vehicle health information is incorporated within automated logistics systems. More specific examples of IVHM-like applications are provided by Fox and Glass [11], Hess and Fila [29], Bird et al [8] and You et al [30].…”

Section: Examples Of Ivhm Applicationsmentioning

confidence: 99%

“…Maintenance operations benefit from reduced occurrences of unexpected faults as the health management system will provide early identification of failure precursors, while condition-based maintenance (CBM) is enabled which can enhance availability, mission reliability, system life and affordability [1], [3], [4], [5]. Similarly, command and control functions can be enhanced by an improved awareness of vehicle condition and vehicle situational capabilities, so that safety, utilisation, vehicle turnaround time, and the chance of mission success can improve [2], [6], [7]. Some IVHM systems include logistics management where the availability of current vehicle health information can be used to automatically trigger logistics actions.…”

Section: Introductionmentioning

confidence: 99%

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State-of-the-art in integrated vehicle health management

Benedettini

Baines

Lightfoot

et al. 2008

Proceedings of the Institution of Mechanical Engineers, Part G:

101

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Integrated Vehicle Health Management (IVHM) is the collection of data relevant to the present and future performance of a vehicle system and its transformation into information that can be used to support operational decisions. This design and operation concept embraces an integration of sensors, communication technologies and artificial intelligence in order to provide vehicle-wide abilities to diagnose problems and recommend solutions. This paper aims to report the state-of-the-art of IVHM research by presenting a systematic review of the literature. Literature from different sources is collated and analysed, and the major emerging themes are presented. On this basis, the paper describes the IVHM concept and its evolution, discusses configurations and existing applications along with potential benefits and barriers to adoption, summarises design guidelines and available methods, and identifies future research challenges.

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“…Under this framework, the system's current on‐board condition is evaluated, and the MSA malfunctions are identified. Then, the prognostics estimate the advent of failure by providing a distribution of the remaining useful life and the level of deviation or degradation . The main purpose of the on‐board condition prediction is to elucidate the changing trends in the on‐board conditions through an effective predictive approach and give early warning of potential areas of concern, which can assist decision makers in deciding on the ISHM preventive measures required for the MSA.…”

Section: Introductionmentioning

confidence: 99%

Integrated System Health Management-based Fuzzy On-board Condition Prediction for Manned Spacecraft Avionics

Meng

2014

Qual. Reliab. Engng. Int.

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The purpose of this study is to develop a prediction methodology for a condition assessment of on-board integrated health management systems in manned spacecraft avionics. The framework of this study is based on two main premises. The first is the need to examine the problems in the on-board prediction tools in space avionics integrated system health management, an area that has been rarely focused on. The second is the need to consider the failure correlation coefficients to enable accurate health predictions. To deal with the uncertainty in the prediction process, a fuzzy theory-gray model-support vector machine approach, which uses fuzzy theory combined with a gray model and a support vector machine, is used to make the prediction. An example is given to demonstrate the accuracy and reliability of the model.

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Integrated Management of System Health in Space Applications

Cited by 15 publications

References 1 publication

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

State-of-the-art in integrated vehicle health management

Integrated System Health Management-based Fuzzy On-board Condition Prediction for Manned Spacecraft Avionics

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