The identification method of the coal mill motor power model with the use of machine learning techniques

• Autorzy: Łabęda-Grudziak Zofia Magdalena , Lipiński Mariusz

Identyfikatory

DOI

10.24425/bpasts.2021.135842

• Języki publikacji: EN

Abstrakty

EN

The article presents an identification method of the model of the ball-and-race coal mill motor power signal with the use of machine learning techniques. The stages of preparing training data for model parameters identification purposes are described, as well as these aimed at verifying the quality of the evaluated model. In order to meet the tasks of machine learning, additive regression model was applied. Identification of the additive model parameters was performed on the basis of iterative backfitting algorithm combined with nonparametric estimation techniques. The proposed models have predictive nature and are aimed at simulation of the motor power signal of a coal mill during its regular operation, startup and shutdown. A comparative analysis has been performed of the models structured differently in terms of identification quality and sensitivity to the existence of an exemplary disturbance in the form of overhangs in the coal bunker. Tests carried out on the basis of real measuring data registered in the Polish power unit with a capacity of 200 MW confirm the effectiveness of the method.

Słowa kluczowe

EN

coal mill motor power; nonlinear model identification; machine learning; additive regression models; process monitoring

PL

moc silnika młyna węglowego; nieliniowa identyfikacja modelu; nauczanie maszynowe; model regresji addytywny; monitorowanie procesu

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2021
• Tom: Vol. 69, nr 1
• Strony: art. no. e135842
• Opis fizyczny: Bibliogr. 24 poz., rys., tab.

Twórcy

autor

Łabęda-Grudziak Zofia Magdalena

• Warsaw University of Technology, Institute of Automatic Control and Robotics, ul. św. Andrzeja Boboli 8, 02-525 Warsaw, Poland

• https://orcid.org/0000-0003-3195-0650

autor

Lipiński Mariusz

• Institute of Power Systems Automation, u. Wystawowa 113, 51-618 Wrocław, Poland

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).