Developing automatic recognition system of drill wear in standard laminated chipboard drilling process

• Autorzy: Kurek J. , Kruk M. , Osowski S. , Hoser P. , Wieczorek G. , Jegorowa A. , Górski J. , Wilkowski J. , Śmietańska K. , Kossakowska J.

Identyfikatory

DOI

10.1515/bpasts-2016-0071

• Języki publikacji: EN

Abstrakty

EN

The paper presents an automatic approach to recognition of the drill condition in a standard laminated chipboard drilling process. The state of the drill is classified into two classes: “useful” (sharp enough) and “useless” (worn out). The case “useless” indicates symptoms of excessive drill wear, unsatisfactory from the point of view of furniture processing quality. On the other hand the “useful” state identifies tools which are still able to drill holes acceptable due to the required processing quality. The main problem in this task is to choose an appropriate set of diagnostic features (variables), based on which the recognition of drill state (“useful” versus “useless”) can be made. The features have been generated based on 5 registered signals: feed force, cutting torque, noise, vibration and acoustic emission. Different statistical parameters describing these signals and also their Fourier and wavelet representations have been used for defining the features. Sequential feature selection is applied to detect the most class discriminative set of features. The final step of recognition is done by using three types of classifiers, including support vector machine, ensemble of decision trees and random forest. Six standard drills of 12 mm diameter with tungsten carbide tips were used in experiments. The results have confirmed good quality of the proposed diagnostic system.

Słowa kluczowe

EN

diagnostic expert systems; neural networks; wavelet packets; wear monitoring

PL

diagnostyczny system ekspercki; sieci neuronowe; pakiety falkowe; monitorowanie zużycia

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2016
• Tom: Vol. 64, nr 3
• Strony: 633--640
• Opis fizyczny: Bibliogr. 24 poz., rys., wykr., fot., tab.

Twórcy

autor

Kurek J.

• Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences,166 Nowoursynowska St., 02-787 Warsaw, Poland

autor

Kruk M.

• Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences,166 Nowoursynowska St., 02-787 Warsaw, Poland

autor

Osowski S.

• Faculty of Electrical Engineering, Warsaw University of Technology and Faculty of Electronic Engineering, Military University of Technology, Warsaw, 75 Koszykowa St., 00-662 Warsaw, Poland

autor

Hoser P.

• Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences,166 Nowoursynowska St., 02-787 Warsaw, Poland

autor

Wieczorek G.

• Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences,166 Nowoursynowska St., 02-787 Warsaw, Poland

autor

Jegorowa A.

• Faculty of Wood Technology, Warsaw University of Life Sciences, 166 Nowoursynowska St., 02-787 Warsaw, Poland

autor

Górski J.

• Faculty of Wood Technology, Warsaw University of Life Sciences, 166 Nowoursynowska St., 02-787 Warsaw, Poland

autor

Wilkowski J.

• Faculty of Wood Technology, Warsaw University of Life Sciences, 166 Nowoursynowska St., 02-787 Warsaw, Poland

autor

Śmietańska K.

• Faculty of Wood Technology, Warsaw University of Life Sciences, 166 Nowoursynowska St., 02-787 Warsaw, Poland

autor

Kossakowska J.

• Institute of Manufacturing Technologies, Warsaw University of Technology, 85 Narbutta St., 02-524 Warsaw, Poland

Bibliografia

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