Prognostics.umd.edu

Prognostics and Health Management Group

WEBThe PHM Group conducts research and development of prognostics and health management applications for electronic products and systems, as well as systems-of-systems. The research focuses on computational algorithms, advanced sensors and data collection techniques, condition-based maintenance, PHM for the application of in-situ …

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URL: https://www.prognostics.umd.edu/

APPLICATIONS OF IN -SITU HEALTH -MONITORING AND …

WEBThis paper reviews the applications of in-situ health monitoring and prognostic sensors with the focus on those in electronic systems. It provides an insight into the issues of utilizing in-situ sensors in electronic systems for health monitoring and prognostics. Those issues are discussed in comparison to those for mechanical systems and

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Prognostics for state of health estimation of lithium-ion …

WEBPrognostics for state of health estimation of lithium-ion batteries based on combination Gaussian process functional regression Datong Liua,⇑, Jingyue Panga, Jianbao Zhoua, Yu Penga, Michael Pechtb a Department of Automatic Test and Control, Harbin Institute of Technology, Harbin 150080, China bCALCE, University of Maryland, College Park, MD …

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Sensor System Selection for Prognostics and Health …

WEBPrognostics and Health Management Lab Center for Advanced Life Cycle Engineering (CALCE) University of Maryland, College Park, MD, 20742. ∗Author of correspondence, Phone: (301) 405-5278, Email:[email protected].

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Modeling Approaches for Prognostics and Health …

WEBAbstract: Prognostics and Health Management is an enabling technology with the potential to solve complex reliability problems that are due to complexity in design, manufacturing, and maintenance. There are several different mathematical techniques that can assist in performing prognostics and health management of electronic systems.

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A REVIEW OF PHM SYSTEM’S ARCHITECTURAL FRAMEWORKS

WEBIt provides a holistic view of the system for system developers and thereby forms the basis for building a system or serves as a guide for system modeling, integration and testing. This paper reviews the architectures proposed in literature for a PHM system. The architectural frameworks proposed for various PHM applications are also discussed

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Use of Temperature as a Health Monitoring Tool for Solder

WEBIn this paper, the efficacy of the use of temperature rise as a health assessment tool for solder interconnects degradation under thermal fatigue is demonstrated. The test specimens were insertion-mount varistors soldered with Sn99.3Cu+Ni (Ge) (SN100C) and conventional Sn37Pb solder.

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Prognostics and Health Monitoring for Lithium-ion Battery

WEBTable I shows relevant monitored parameters to battery health in the current battery industry. The objectives of health monitoring are to detect and predict the remaining charge and

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Prognostics of Lithium-Ion Batteries Using Model- Based and …

WEBCenter for Advanced Life Cycle Engineering (CALCE) University of Maryland, College Park College Park, USA [email protected]. Abstract—This paper presents an integrated approach to predict remaining useful life (RUL) of lithium-ion batteries using model-based and data-driven methods. An empirical model is adopted to emulate the battery

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Prognostics and Health Management (ePHM) for Improved

WEBPROGNOSTICS AND HEALTH MANAGEMENT FOR IMPROVED DISPATCHABILITY OF INTEGRATED MODULAR AVIONICS EQUIPPED AIRCRAFT Chris Wilkinson, CALCE Electronic Products and Systems Center, Department of Mechanical

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Physics-of-failure-basedprognostics forelectronicproducts

WEBMD 20742, USA 2Center for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD 20742, USA. This paper presents a physics-of-failure (PoF)-based prognostics and health management approach for effective reliability prediction. PoF is an approach that utilizes knowledge of a product’s life cycle loading and failure

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Comparative Analysis of Features for Determining State of …

WEBInternational Journal of Prognostics and Health Management, ISSN 2153-2648, 2013 004 Comparative Analysis of Features for Determining State of Health in

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Data Analysis Approach for System Reliability, Diagnostics and …

WEBThis approach is a black box approach where failure specific knowledge and systems operational conditions are not required. This approach assumes that electronics are non-susceptible to environmental conditions. In this approach, the prognostic algorithms are of low complexity and require input of product’s.

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Failure Prognostics of Multilayer Ceramic Capacitors in

WEBAbstract—This paper presents a prognostics approach which detects the performance degradation of multilayer ceramic capacitors under temperature-humidity-bias conditions, and then predicts remaining useful life. In the tests, three performance parameters (capacitance, dissipation factor and insulation resistance) were monitored in-situ.

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Precursor Parameter Identification for Power Supply …

WEBHuiguo Zhang, Rui Kang , Mingzhu Luo. Abstract—Prognostics and health management (PHM) seeks to identify and isolate reliability problems in products (diagnostics) and predict a product’s remaining useful life (prognostics). In this paper, a four-step PHM approach for power supplies is presented: 1) precursor parameter identification based

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Author's personal copy

WEBAuthor's personal copy A health indicator method for degradation detection of electronic products Sachin Kumar, Nikhil M. Vichare, Eli Dolev, Michael Pecht

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Prognostics implementation of electronics under vibration …

WEBCenter for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD 20742, USA. Received 17 January 2007 Available online 6 April 2007. Abstract. In this paper, a methodology is developed for monitoring, recording, and analyzing the life-cycle vibration loads for remaining-life prognostics of electronics.

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Health Assessment of Electronic Products using Mahalanobis …

WEBTwo approaches for detection and fault isolation based on classification theory are presented in this paper. Both are capable of system level anomaly detection in multivariate, data-rich environments. One methodology uses the Mahalanobis Distance (MD) and the other uses a projection pursuit analysis (PPA) to analyze on-line system data.

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