167,233 research outputs found
Methods of Technical Prognostics Applicable to Embedded Systems
HlavnĂ cĂlem dizertace je poskytnutĂ ucelenĂŠho pohledu na problematiku technickĂŠ prognostiky, kterĂĄ nachĂĄzĂ uplatnÄnĂ v tzv. prediktivnĂ ĂşdrĹžbÄ zaloĹženĂŠ na trvalĂŠm monitorovĂĄnĂ zaĹĂzenĂ a odhadu ĂşrovnÄ degradace systĂŠmu Äi jeho zbĂ˝vajĂcĂ Ĺživotnosti a to zejmĂŠna v oblasti komplexnĂch zaĹĂzenĂ a strojĹŻ. V souÄasnosti je technickĂĄ diagnostika pomÄrnÄ dobĹe zmapovanĂĄ a reĂĄlnÄ nasazenĂĄ na rozdĂl od technickĂŠ prognostiky, kterĂĄ je stĂĄle rozvĂjejĂcĂm se oborem, kterĂ˝ ovĹĄem postrĂĄdĂĄ vÄtĹĄĂ mnoĹžstvĂ reĂĄlnĂ˝ch aplikaci a navĂc ne vĹĄechny metody jsou dostateÄnÄ pĹesnĂŠ a aplikovatelnĂŠ pro embedded systĂŠmy. DizertaÄnĂ prĂĄce pĹinĂĄĹĄĂ pĹehled zĂĄkladnĂch metod pouĹžitelnĂ˝ch pro ĂşÄely predikce zbĂ˝vajĂcĂ uĹžitnĂŠ Ĺživotnosti, jsou zde popsĂĄny metriky pomocĂ, kterĂ˝ch je moĹžnĂŠ jednotlivĂŠ pĹĂstupy porovnĂĄvat aĹĽ uĹž z pohledu pĹesnosti, ale takĂŠ i z pohledu vĂ˝poÄetnĂ nĂĄroÄnosti. Jedno z dizertaÄnĂch jader tvoĹĂ doporuÄenĂ a postup pro vĂ˝bÄr vhodnĂŠ prognostickĂŠ metody s ohledem na prognostickĂĄ kritĂŠria. DalĹĄĂm dizertaÄnĂm jĂĄdrem je pĹedstavenĂ tzv. ÄĂĄsticovĂŠho filtrovanĂ (particle filtering) vhodnĂŠ pro model-based prognostiku s ovÄĹenĂm jejich implementace a porovnĂĄnĂm. HlavnĂ dizertaÄnĂ jĂĄdro reprezentuje pĹĂpadovou studii pro velmi aktuĂĄlnĂ tĂŠma prognostiky Li-Ion baterii s ohledem na trvalĂŠ monitorovĂĄnĂ. PĹĂpadovĂĄ studie demonstruje proces prognostiky zaloĹženĂŠ na modelu a srovnĂĄvĂĄ moĹžnĂŠ pĹĂstupy jednak pro odhad doby pĹed vybitĂm baterie, ale takĂŠ sleduje moĹžnĂŠ vlivy na degradaci baterie. SouÄĂĄstĂ prĂĄce je zĂĄkladnĂ ovÄĹenĂ modelu Li-Ion baterie a nĂĄvrh prognostickĂŠho procesu.The main aim of the thesis is to provide a comprehensive overview of technical prognosis, which is applied in the condition based maintenance, based on continuous device monitoring and remaining useful life estimation, especially in the field of complex equipment and machinery. Nowadays technical prognosis is still evolving discipline with limited number of real applications and is not so well developed as technical diagnostics, which is fairly well mapped and deployed in real systems. Thesis provides an overview of basic methods applicable for prediction of remaining useful life, metrics, which can help to compare the different approaches both in terms of accuracy and in terms of computational/deployment cost. One of the research cores consists of recommendations and guide for selecting the appropriate forecasting method with regard to the prognostic criteria. Second thesis research core provides description and applicability of particle filtering framework suitable for model-based forecasting. Verification of their implementation and comparison is provided. The main research topic of the thesis provides a case study for a very actual Li-Ion battery health monitoring and prognostics with respect to continuous monitoring. The case study demonstrates the prognostic process based on the model and compares the possible approaches for estimating both the runtime and capacity fade. Proposed methodology is verified on real measured data.
A novel mechanical analogy based battery model for SoC estimation using a multi-cell EKF
The future evolution of technological systems dedicated to improve energy
efficiency will strongly depend on effective and reliable Energy Storage
Systems, as key components for Smart Grids, microgrids and electric mobility.
Besides possible improvements in chemical materials and cells design, the
Battery Management System is the most important electronic device that improves
the reliability of a battery pack. In fact, a precise State of Charge (SoC)
estimation allows the energy flows controller to exploit better the full
capacity of each cell. In this paper, we propose an alternative definition for
the SoC, explaining the rationales by a mechanical analogy. We introduce a
novel cell model, conceived as a series of three electric dipoles, together
with a procedure for parameters estimation relying only on voltage measures and
a given current profile. The three dipoles represent the quasi-stationary, the
dynamics and the istantaneous components of voltage measures. An Extended
Kalman Filer (EKF) is adopted as a nonlinear state estimator. Moreover, we
propose a multi-cell EKF system based on a round-robin approach to allow the
same processing block to keep track of many cells at the same time. Performance
tests with a prototype battery pack composed by 18 A123 cells connected in
series show encouraging results.Comment: 8 page, 12 figures, 1 tabl
Screening of energy efficient technologies for industrial buildings' retrofit
This chapter discusses screening of energy efficient technologies for industrial buildings' retrofit
Task-Driven Estimation and Control via Information Bottlenecks
Our goal is to develop a principled and general algorithmic framework for
task-driven estimation and control for robotic systems. State-of-the-art
approaches for controlling robotic systems typically rely heavily on accurately
estimating the full state of the robot (e.g., a running robot might estimate
joint angles and velocities, torso state, and position relative to a goal).
However, full state representations are often excessively rich for the specific
task at hand and can lead to significant computational inefficiency and
brittleness to errors in state estimation. In contrast, we present an approach
that eschews such rich representations and seeks to create task-driven
representations. The key technical insight is to leverage the theory of
information bottlenecks}to formalize the notion of a "task-driven
representation" in terms of information theoretic quantities that measure the
minimality of a representation. We propose novel iterative algorithms for
automatically synthesizing (offline) a task-driven representation (given in
terms of a set of task-relevant variables (TRVs)) and a performant control
policy that is a function of the TRVs. We present online algorithms for
estimating the TRVs in order to apply the control policy. We demonstrate that
our approach results in significant robustness to unmodeled measurement
uncertainty both theoretically and via thorough simulation experiments
including a spring-loaded inverted pendulum running to a goal location.Comment: 9 pages, 4 figures, abridged version accepted to ICRA2019;
Incorporates changes in final conference submissio
Information and communication technology solutions for outdoor navigation in dementia
INTRODUCTION:
Information and communication technology (ICT) is potentially mature enough to empower outdoor and social activities in dementia. However, actual ICT-based devices have limited functionality and impact, mainly limited to safety. What is an ideal operational framework to enhance this field to support outdoor and social activities?
METHODS:
Review of literature and cross-disciplinary expert discussion.
RESULTS:
A situation-aware ICT requires a flexible fine-tuning by stakeholders of system usability and complexity of function, and of user safety and autonomy. It should operate by artificial intelligence/machine learning and should reflect harmonized stakeholder values, social context, and user residual cognitive functions. ICT services should be proposed at the prodromal stage of dementia and should be carefully validated within the life space of users in terms of quality of life, social activities, and costs.
DISCUSSION:
The operational framework has the potential to produce ICT and services with high clinical impact but requires substantial investment
Optimal treatment allocations in space and time for on-line control of an emerging infectious disease
A key component in controlling the spread of an epidemic is deciding where, whenand to whom to apply an intervention.We develop a framework for using data to informthese decisionsin realtime.We formalize a treatment allocation strategy as a sequence of functions, oneper treatment period, that map up-to-date information on the spread of an infectious diseaseto a subset of locations where treatment should be allocated. An optimal allocation strategyoptimizes some cumulative outcome, e.g. the number of uninfected locations, the geographicfootprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategyfor an emerging infectious disease is challenging because spatial proximity induces interferencebetween locations, the number of possible allocations is exponential in the number oflocations, and because disease dynamics and intervention effectiveness are unknown at outbreak.We derive a Bayesian on-line estimator of the optimal allocation strategy that combinessimulationâoptimization with Thompson sampling.The estimator proposed performs favourablyin simulation experiments. This work is motivated by and illustrated using data on the spread ofwhite nose syndrome, which is a highly fatal infectious disease devastating bat populations inNorth America
CURRENT ISSUES AFFECTING TRADE AND TRADE POLICY: AN ANNOTATED LITERATURE REVIEW
This review provides a base of literature describing current issues and research on the impacts of lobalization and the industrialization of agriculture and recent approaches to analyze and model agricultural trade and trade policies. Three key factors of the survey are differentiated goods, global economic integration and international supply chain linkages. The review covers 182 publications, which are presented alphabetically by author with a brief annotation describing how it relates to the above criteria. The articles are also indexed by keyword. A brief summary highlights the documented literature and includes a series of issues for future discussion and research.International Relations/Trade,
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