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A multi-scale cross-dimension interaction approach with adaptive dilated TCN for RUL prediction. [PDF]
Sci RepLu Z +7 more
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A Survey of AI-Enabled Predictive Maintenance for Railway Infrastructure: Models, Data Sources, and Research Challenges. [PDF]
Sensors (Basel)Bris-Peñalver FJ +2 more
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Stirling cryocooler prognostics and health management (PHM)
2009 IEEE AUTOTESTCON, 2009Tactical Stirling cryocoolers are life-limited components used in many IR sensing systems. Thousands are deployed in commercial and military systems. Using prognostics to predict impending failures will allow cryocooler replacement when it is convenient and cost-effective, rather than during system operation. This both reduces cost and improves mission
Paul H. Barton, Robert Ogden
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Prognostics and Health Management (PHM) System requirements and validation
2010 Prognostics and System Health Management Conference, 2010This paper based on four key abilities of the Prognostics and Health Management (PHM) System including the abilities of fault detection, fault isolation, fault prognosis and prognosis of the remaining life, analyzes and constructs a framework of the PHM quantitative requirements, and defines the quantitative assessment emphasis of the PHM abilities ...
null Ping Xu +2 more
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Improving digital system diagnostics through Prognostic and Health Management (PHM) technology
2007 IEEE Autotestcon, 2007Development of robust prognostic for digital electronic system health management will improve maintainability and operational readiness for many industries with products ranging from enterprise network servers to military aircraft. The emerging digital PHM technology discussed in this paper can be applied in a myriad of applications ranging from on ...
M. Baybutt +4 more
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Case Studies: Prognostics and Health Management (PHM)
2018Prognostics and health management (PHM) technology has been successfully implemented into engineering practice in diverse settings. This chapter presents case studies that explain successful PHM practices in several engineering applications: (1) steam turbine rotors, (2) wind turbine gearboxes, (3) the core and windings in power transformers, (4) power
Chao Hu, Byeng D. Youn, Pingfeng Wang
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Quick positional health assessment for industrial robot prognostics and health management (PHM)
2017 IEEE International Conference on Robotics and Automation (ICRA), 2017Robot calibration and performance will degrade if proper maintenance isn't performed. There have been challenges for manufacturers to optimize the maintenance strategy and minimize unexpected shutdowns. Prognostics and health management (PHM) can be applied to industrial robots through the development of performance metrics, test methods, reference ...
Guixiu Qiao +2 more
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Miniature MEMS-based data recorder for prognostics and health management (PHM)
2010 IEEE AUTOTESTCON, 2010Novel prognostic sensors and reasoner algorithms are the core technology for detecting defects caused by accumulation of fatigue damage in electrical and mechanical systems over time. However, serious technical challenges to implementing a general health management strategy for helicopters and military aircraft still exist. For example, severe heat and
Matt Engelman +3 more
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Miniature MEMS-based data recorder for prognostics and health management (PHM)
IEEE Instrumentation & Measurement Magazine, 2011This paper presents a a prognostic and health management system integrating microelectromechanical systems sensor with a standard microcontroller and measurement electronics for helicopters and military aircraft. In this way, prognostic sensors can be positioned closer to the stressed components and provide higher fidelity data with lower cost.
Sonia Vohnout +2 more
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Survival Analysis Approach to Reliability, Survivability and Prognostics and Health Management (PHM)
2008 IEEE Aerospace Conference, 2008Survival analysis, also known as failure time analysis or time-to-event analysis, is one of the most significant advancements of mathematical statistics in the last quarter of the 20th century. It has become the de facto standard in biomedical data analysis.
Zhanshan Ma, Axel W. Krings
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