A Review of System Health State Determination Methods

Aaseng, Gordon; Garcia-Galan, Carlos

doi:10.2514/6.2005-2528

Cited by 15 publications

(2 citation statements)

References 5 publications

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“…Finally the verification phase ensures that repairs have been performed correctly and that the system has been returned to full operational status. Of the four phases, accurate health state determination is essential for effective health management [2].…”

Section: B Health Manage~ent Is a Processmentioning

confidence: 99%

Enterprise health management framework - A holistic approach for technology planning, R&D collaboration and transition

Dabney¹,

Hernández

Scandura

et al. 2008

2008 International Conference on Prognostics and Health Management

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Health management technologies are critical for detecting and predicting impending system faults before actual failures occur, initiating fault mitigation, and producing data to enable proactive logistics planning and fleet operations decision processes. While early indications in certain initiatives within the government and commercial sectors are beginning to show promising results, the authors observe that there is a need to develop a holistic, systems engineering approach to facilitate program needs assessment, health management technology planning, coordinated research and development, and effective transition of emerging health management capabilities to both new and legacy platforms. Health management, unlike other platform capabilities, is not a self-contained, stand-alone "system", but is rather an integral part of every subsystem, system, the entire platform, and ultimately affects the entire logistics support enterprise. This holistic view requires a new mindset within our industry.The authors propose that what is needed is a systems engineering approach that would be used throughout an enterprise for technology planning, research and development collaboration and effective transition to operational programs. The proposed systems engineering approach provides an Enterprise Health Management (EHM) Framework for assessing operational needs and business case, identifying technology gaps, roadmaps and collaboration opportunities, assessing enterprise integration constraints and transition planning. This paper discusses the conceptual EHM Framework, some examples of the potential benefits, and the critical implementation issues.

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Section: B Health Manage~ent Is a Processmentioning

confidence: 99%

Enterprise health management framework - A holistic approach for technology planning, R&D collaboration and transition

Dabney¹,

Hernández

Scandura

et al. 2008

2008 International Conference on Prognostics and Health Management

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show abstract

“…System health monitoring (SHM) has been highly concerned in the system engineering field, where information extracted from SHM can be used to understand the system behavior and improve the system utilization based on optimal component replacement and maintenance strategies [1]. In the field of SHM, the system degradation is identified by comparing the system's real-time performance with its normal operational performance [2], and system degradation or fault occurrence will lead to a decrease of the system reliability.…”

Section: Introductionmentioning

confidence: 99%

A modified profust-performance-reliability algorithm and its application to dynamic systems

Zhao

Quan

Cai

2017

IFS

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In the field of system health monitoring, system performance degradation or fault occurrence will decrease the system reliability to some degree. However, traditional reliability analysis is of limited usefulness in evaluating the reliability of an individual product under dynamic operating and environmental conditions. In this case, research on performance reliability as well as real-time reliability has attracted extensive attentions. Considering the characteristics of fuzzy reliability theory, a performance reliability based on profust reliability theory has its advantage on tracking system's continuous degradation. On the basis of our previous work, this paper proposes a modified profust-performance-reliability (PPR) algorithm as a supplement to the profust reliability based approach to prognostics and health management. In the modified PPR algorithm, the item of transition probability among system's multi-states is replaced with the real-time distribution of system's health status, which achieves an easier implementation of PPR's calculation in practice with higher real-time capability and accuracy. Then, its application in the performance evaluation and prediction of dynamic systems are comprehensively proposed. Finally, a simulation of a quadrotor with partial loss of actuator effectiveness is presented to validate the availability and effectiveness of the proposed method.

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Launch Vehicle Health Management

Brown¹,

Kelley²,

Gormley³

2011

System Health Management

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A Review of System Health State Determination Methods

Cited by 15 publications

References 5 publications

Enterprise health management framework - A holistic approach for technology planning, R&D collaboration and transition

Enterprise health management framework - A holistic approach for technology planning, R&D collaboration and transition

A modified profust-performance-reliability algorithm and its application to dynamic systems

Launch Vehicle Health Management

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A Review of System Health State Determination Methods

Cited by 15 publications

References 5 publications

Enterprise health management framework - A holistic approach for technology planning, R&#x00026;D collaboration and transition

Enterprise health management framework - A holistic approach for technology planning, R&#x00026;D collaboration and transition

A modified profust-performance-reliability algorithm and its application to dynamic systems

Launch Vehicle Health Management

Contact Info

Product

Resources

About

Enterprise health management framework - A holistic approach for technology planning, R&D collaboration and transition

Enterprise health management framework - A holistic approach for technology planning, R&D collaboration and transition