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Related papers: Enabling electronic prognostics using thermal data

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It is not surprising that the idea of efficient maintenance algorithms (originally motivated by strict emission regulations, and now driven by safety issues, logistics and customer satisfaction) has culminated in the so-called…

Signal Processing · Electrical Eng. & Systems 2019-12-06 Ehsan Taheri , Ilya Kolmanovsky , Oleg Gusikhin

The predictability of errors in deterministic temperature forecasts is investigated. More precisely, the aim is to issue warnings whenever the differences between forecast and verification exceed a given threshold. The warnings are…

Atmospheric and Oceanic Physics · Physics 2011-12-08 S. Hallerberg , J. Bröcker , H. Kantz , L. A. Smith

Maintenance is an important activity in industry. It is performed either to revive a machine/component or to prevent it from breaking down. Different strategies have evolved through time, bringing maintenance to its current state:…

Software Engineering · Computer Science 2017-06-27 Wiem Elghazel , Jacques M. Bahi , Christophe Guyeux , Mourad Hakem , Kamal Medjaher , Noureddine Zerhouni

Power device reliability is a major concern during operation under extreme environments, as doing so reduces the operational lifetime of any power system or sensing infrastructure. Due to a potential for system failure, devices must be…

Machine Learning · Computer Science 2021-07-23 Carlos Olivares , Raziur Rahman , Christopher Stankus , Jade Hampton , Andrew Zedwick , Moinuddin Ahmed

A system responding to a stochastic driving signal can be interpreted as computing, by means of its dynamics, an implicit model of the environmental variables. The system's state retains information about past environmental fluctuations,…

Statistical Mechanics · Physics 2012-10-09 Susanne Still , David A. Sivak , Anthony J. Bell , Gavin E. Crooks

The great majority of engineered products are subject to thermo-mechanical loads which vary with the product environment during the various phases of its life-cycle (machining, assembly, intended service use...). Those load variations may…

Classical Physics · Physics 2009-05-07 Guillaume Mandil , Alain Desrochers , Alain Rivière

Predictive maintenance is used in industrial applications to increase machine availability and optimize cost related to unplanned maintenance. In most cases, predictive maintenance applications use output from sensors, recording physical…

Machine Learning · Computer Science 2021-11-23 Antoine Guillaume , Christel Vrain , Elloumi Wael

The paper makes a thermal predictive analysis of the electric power system security for a day ahead. This predictive analysis is set as a thermal computation of the expected security. This computation is obtained by cointegrating the daily…

Computational Engineering, Finance, and Science · Computer Science 2011-01-25 Stefan Z. Stefanov

Forecasting thermal load is a key component for the majority of optimization solutions for controlling district heating and cooling systems. Recent studies have analysed the results of a number of data-driven methods applied to thermal load…

Machine Learning · Computer Science 2017-10-18 Davy Geysen , Oscar De Somer , Christian Johansson , Jens Brage , Dirk Vanhoudt

Prognostics and Health Management is crucial for the reliability and lifetime assessment of Polymer Electrolyte Fuel Cells (PEFCs). Here, we review the current advances on this topic, focusing mainly on key degradation mechanisms and…

Systems and Control · Electrical Eng. & Systems 2025-11-17 Farideh Abdollahi , Kourosh Malek , Thomas Kadyk , Nadiia Kulyk , Christophe Gerling , Michael H. Eikerling

Load forecasts have become an integral part of energy security. Due to the various influencing factors that can be considered in such a forecast, there is also a wide range of models that attempt to integrate these parameters into a system…

Machine Learning · Computer Science 2022-10-19 Philipp Giese

Event prediction is the ability of anticipating future events, i.e., future real-world occurrences, and aims to support the user in deciding on actions that change future events towards a desired state. An event prediction method learns the…

Artificial Intelligence · Computer Science 2025-07-10 Janik-Vasily Benzin , Stefanie Rinderle-Ma

The number of electrified powertrains is ever increasing today towards a more sustainable future; thus, it is essential that unwanted failures are prevented, and a reliable operation is secured. Monitoring the internal temperatures of…

Machine Learning · Computer Science 2025-04-28 Dinan Li , Panagiotis Kakosimos

As CMOS technology scales down, thermal fluctuations increasingly impact circuit behavior, posing challenges to conventional circuit design. However, the inherent stochasticity introduced by thermal noise is now being explored as a…

Thermodynamics (in concert with its sister discipline, statistical physics) can be regarded as a data reduction scheme based on partitioning a total system into a subsystem and a bath that weakly interact with each other. The ubiquity and…

Statistical Mechanics · Physics 2009-11-11 David Ford , Steven Huntsman

The impact of machine learning models on healthcare will depend on the degree of trust that healthcare professionals place in the predictions made by these models. In this paper, we present a method to provide people with clinical expertise…

Machine Learning · Computer Science 2021-03-05 Aniruddh Raghu , John Guttag , Katherine Young , Eugene Pomerantsev , Adrian V. Dalca , Collin M. Stultz

The rise of computation-based methods in thermal management has gained immense attention in recent years due to the ability of deep learning to solve complex 'physics' problems, which are otherwise difficult to be approached using…

Machine Learning · Computer Science 2025-09-03 Aviral Chharia , Nishi Mehta , Shivam Gupta , Shivam Prajapati

Central to the efficacy of prognostics and health management methods is the acquisition and analysis of degradation data, which encapsulates the evolving health condition of engineering systems over time. Degradation data serves as a rich…

Databases · Computer Science 2026-02-06 Fabian Mauthe , Christopher Braun , Julian Raible , Peter Zeiler , Marco F. Huber

Decadal temperature prediction provides crucial information for quantifying the expected effects of future climate changes and thus informs strategic planning and decision-making in various domains. However, such long-term predictions are…

Machine Learning · Computer Science 2023-04-20 Jinfu Ren , Yang Liu , Jiming Liu

This paper describes prediction methods for the number of future events from a population of units associated with an on-going time-to-event process. Examples include the prediction of warranty returns and the prediction of the number of…

Methodology · Statistics 2020-08-10 Qinglong Tian , Fanqi Meng , Daniel J. Nordman , William Q. Meeker
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