Baza Publikacji Pracowników Politechniki Lubelskiej

Status:
Autorzy:	Jonak Józef, Kuric Ivan, Droździel Paweł, Gajewski Jakub, Sága Milan
Dyscypliny:
	Aby zobaczyć szczegóły należy się zalogować.
Rok wydania:	2020
Wersja dokumentu:	Drukowana \| Elektroniczna
Język:	angielski
Numer czasopisma:	4
Wolumen/Tom:	25
Strony:	444 - 452
Impact Factor:	1,413
Web of Science® Times Cited:	1
Scopus® Cytowania:	2
Bazy:	Web of Science \| Scopus
Efekt badań statutowych	NIE
Materiał konferencyjny:	NIE
Publikacja OA:	TAK
Licencja:
Sposób udostępnienia:	Otwarte czasopismo
Wersja tekstu:	Ostateczna wersja opublikowana
Czas opublikowania:	W momencie opublikowania
Data opublikowania w OA:	5 kwietnia 2021
Abstrakty:	angielski
	A tunnel boring machine (TBM) is a machine that is used to excavate tunnels with a circular cross-section. TBMs can bore through a variety of ground conditions. Tunnel boring machines are used as an alternative to drilling methods. TBMs have the advantages of limiting the disturbance to the surrounding ground. Predicting the load on cutting tools in tunnel boring machines is important for the mining process. The article presents a proposal for a method of forecasting the load on mining machinery tools. This paper presents current trends in hard rock tunnelling, including the directions of research on automated excavation processes. Particular emphasis is put on the aspects of predicting load variations in the cutterhead tools, which is of vital importance for machine power selection and mining process control, among others. The problem of predicting the load and wear of excavation tools plays an important role in designing and maintaining cutterheads. The effective monitoring of the operation of multi-tool cutterhead knives and their replacement time depend on correct identification of the type and condition of the excavating tool cutting insert.A neural network with a multilayer perceptron structure was used as a prediction tool. The concept of this network type is based on the arrangement of neurons in successive layers. This neural network type is treated as an input-output model. Its parameters include weights and threshold values.

Informacja o cookies

Prediction of load on the cutting tools in tunnel boring machines

Artykuł w czasopiśmie