A. James Clark School of Engineering

Permanent URI for this communityhttp://hdl.handle.net/1903/1654

The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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    Conference Proceedings Report: ASME-SERAD and UMD-CRR Interactive seminar & pre-workshop on the intersection of PRA and PHM
    (2020-10) Groth, Katrina; Pourgol-Mohammad, Mohammad; Modarres, Mohammad
    This event is the first in a two-part series exploring the intersection of PRA and PHM in the context of complex engineering systems. Initially the workshop was planned as a fully in-person workshop to be held in April, 2020, but as with many events in 2020, it was postponed due to the travel restrictions resulting from COVID-19 pandemic. The organizers recognized that the online format isn't amenable to the deep discussions which were intended to be at the heart of the in person workshop, but we decided to try an experiment: to see if we could make a “pre-workshop” as interactive possible in an era of webinar fatigue. Thus the workshop was reimagined as an online, interactive pre-workshop in 2020, to be followed with the in person, discussion-heavy workshop to be held when we are able to travel again in 2021.
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    FAULT DETECTION AND PROGNOSTICS OF INSULATED GATE BIPOLAR TRANSISTOR (IGBT) USING A K-NEAREST NEIGHBOR CLASSIFICATION ALGORITHM
    (2013) Sutrisno, Edwin; Pecht, Michael; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Insulated Gate Bipolar Transistor (IGBT) is a power semiconductor device commonly used in medium to high power applications from household appliances, automotive, and renewable energy. Health assessment of IGBT under field use is of interest due to costly system downtime that may be associated with IGBT failures. Conventional reliability approaches were shown by experimental data to suffer from large uncertainties when predicting IGBT lifetimes, partly due to their inability to adapt to varying loading conditions and part-to-part differences. This study developed a data-driven prognostic method to individually assess IGBT health based on operating data obtained from run-to-failure experiments. IGBT health was classified into healthy and faulty using a K-Nearest Neighbor Centroid Distance classification algorithm. A feature weight optimization method was developed to determine the influence of each feature toward classifying IGBT's health states.
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    PROGNOSTICS DEMONSTRATION OF ELECTRONIC COMPONENTS SUBJECTED TO VIBRATION ENVIRONMENT OF A LIGHT MILITARY TACTICAL VEHICLE
    (2007-11-05) Yu, Alan; Barker, Donald B; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    A demonstration of the Prognostics and Health Management (PHM) method in a military vehicle environment was performed. The purpose of the demonstration is to show rapid and cost effective means to increase reliability and effectiveness of in-cabin equipment through PHM implementation. The PHM method allows for prediction of damage accumulation in a system while in its operating environment. Prediction is achieved by monitoring and assessing appropriate product parameters. An experimental setup to perform in-cabin accelerated testing on printed circuit boards (PCB) was developed. Strain, acceleration, continuity, and GPS data were recorded during testing. Using recorded data, life prediction with cycle counting and PSD load blocking techniques was demonstrated for BGA components. A limited set of terrain and loading conditions was characterized using Root Mean Square (RMS) and Power Spectral Density (PSD).