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Data-driven remaining useful life estimation of a fouled plate heat exchanger
ID Berce, Jure (Author), ID Bucci, Mattia (Author), ID Zupančič, Matevž (Author), ID Može, Matic (Author), ID Golobič, Iztok (Author)

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Abstract
Fouling-induced heat exchanger performance degradation brings about the need for timely maintenance to minimize economic and energy losses as well as reduce chances of system failure during long-term operation. An accurate real-time estimation of remaining useful life can drastically shorten downtime and improve process control. In this paper, we propose a novel coupling of machine learning, Kalman filter and Monte Carlo simulations to predict the remaining useful life of a fouled brazed plate heat exchanger without the need for run-to- failure data, with emphasis on practical model deployment. Firstly, an offline-trained Bagged Tree ensemble is employed to predict the reference performance of the heat exchanger in real-time, which is then compared to current sensor-measured performance of the unit. The progressing mismatch between both metrics is exploited for underlying degradation drift identification with the adaptive linear Kalman filter. Finally, the identified degradation model is propagated to the terminal threshold within a Monte Carlo simulation, obtaining a population of predicted remaining useful life values. The framework’s prognostic capability is demonstrated on three distinct experimental case studies of brazed plate heat exchanger fouling. We illustrate an accurate adaptive prediction of remaining useful life, even after dynamic changes of degradation progression in presence of large flow-rate induced disturbances. In addition, we provide a comprehensive outlook for future work together with possible framework extensions.

Language:English
Keywords:remaining useful life, heat exchanger, fouling, prognostics, predictive maintenance, machine learning, kalman filter
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Publication status:In print
Publication version:Version of Record
Year:2025
Number of pages:13 str.
Numbering:Vol. 169, [article no.] 126954
PID:20.500.12556/RUL-169788 This link opens in a new window
UDC:621:551.511.33
ISSN on article:1873-5606
DOI:10.1016/j.applthermaleng.2025.126954 This link opens in a new window
COBISS.SI-ID:238990083 This link opens in a new window
Publication date in RUL:11.06.2025
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Downloads:55
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Record is a part of a journal

Title:Applied thermal engineering
Publisher:Pergamon Press
ISSN:1873-5606
COBISS.SI-ID:23195397 This link opens in a new window

Licences

License:CC BY-NC 4.0, Creative Commons Attribution-NonCommercial 4.0 International
Link:http://creativecommons.org/licenses/by-nc/4.0/
Description:A creative commons license that bans commercial use, but the users don’t have to license their derivative works on the same terms.

Secondary language

Language:Slovenian
Keywords:preostali čas uporabnosti, prenosnik toplote, odlaganje nečistoč, prognostika, prediktivno vzdrževanje, strojno učenje, kalmanov filter

Projects

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0223
Name:Prenos toplote in snovi

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:N2-0251
Name:Izboljšanje procesa vrenja z uporabo teksturiranih površin (BEST)

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J2-50085
Name:Raziskave medfaznih pojavov kapljic in mehurčkov na funkcionaliziranih površinah ob uporabi napredne diagnostike za razvoj okoljskih tehnologij prihodnosti in izboljšanega prenosa toplote (DroBFuSE)

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