An architecture to implement Integrated Vehicle Health Management systems

Keller, K.; Wiegand, Dietmar; Swearingen, K.; Reisig, C.; Black, S.; Gillis, Allan; Vandernoot, M.

doi:10.1109/autest.2001.948902

Cited by 31 publications

(19 citation statements)

References 1 publication

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“…These criticisms were supported by reported cases of inadequate or faulty sensors which caused premature termination of components or failure to detect faults in critical structures [12]. The costs and benefits of IVHM are directly related to how early in the design it is considered [5], [11], [27] and this requires a significant change in the way vehicle systems are designed [36].…”

Section: Finding 5: Ivhm Technology Has Many Potential Drivers To MImentioning

confidence: 95%

“…The usual approach taken is to give a short discussion of the concept and then to describe specific IVHM solutions [9], [14], [27]. Despite their brevity, these introductory discussions typically contain a description of the benefits of IVHM, although a more detailed treatment of the potential drivers is given by authors who substantially focus on cost-benefit analysis [3], [26], [33].…”

Section: Drivers For Ivhmmentioning

confidence: 99%

“…Almost no papers have been published in academic journals but some articles have appeared as special reports, typically from government agencies and military organisations. These articles cover a range of aspects of IVHM, with approximately 35% describing potential impacts or costbenefit analyses [11], [24], [25], [26]; 15% discussing design approaches [15], [27], [28]; and about 25% focusing on examples of IVHM systems in use or under development [8], [29], [30]. …”

Section: Evolution Of the Ivhm Conceptmentioning

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:

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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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Section: Finding 5: Ivhm Technology Has Many Potential Drivers To MImentioning

confidence: 95%

Section: Drivers For Ivhmmentioning

confidence: 99%

Section: Evolution Of the Ivhm Conceptmentioning

confidence: 99%

See 1 more Smart Citation

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

Benedettini

Baines

Lightfoot

et al. 2008

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…5,6) With the rapid development of the PHM concept and fault prognostics technology, PHM has become an important part in complex aerospace systems such as helicopters, aircraft engines, missiles and so on. 7) At present, more and more attention is being focused on PHM architecture, 8,9) PHM-related models and algorithms. Few studies focus on information sensing and Ó 2013 The Japan Society for Aeronautical and Space Sciences testing of PHM.…”

Section: Introductionmentioning

confidence: 99%

Sensor Selection and Optimization for Aerospace System Health Management under Uncertainty Testing

Yang

Qiu

Liu

et al. 2013

Trans. Japan Soc. Aero. S Sci.

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Prognostics and health management (PHM) has an important part in aerospace systems. Information sensing and testing are the bases of PHM, and design for testability (DFT) developed concurrently with system design is considered a fundamental way to improve PHM performance. The traditional DFT, which is only based on the requirements of fault detection and isolation, is not suitable for sensor design and optimization for PHM. Aiming to solve this problem, the intrinsic requirements of PHM for testability are firstly analyzed qualitatively and the corresponding testability indexes are defined quantitatively. Then, a sensor selection/optimization process for PHM is presented. Fault detection uncertainty is also analyzed systematically from the view of fault attributes, sensor attributes and fault-sensor matching attributes, respectively. Based on the requirements and process, the object and constraint models of sensor optimization selection problem are studied in great detail. For aerospace system health management, a sensor optimization selection model is constructed that treats sensor total cost as the objective function and the proposed testability indexes under uncertainty test as constraint conditions. Due to the NP-hard property of the model, a generic algorithm (GA) is introduced to obtain the optimal solution. The application examples show that the proposed model and algorithm are effective and feasible.

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“…A vehicle health management system based on the OSA-CBM was developed by Boeing [2,3]. Another OSA-CBM system was used in the diagnostic and prognostics for avionics health management [4].…”

Section: Budsmentioning

confidence: 99%