Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: wear monitoring

Sortuj według:

Ogranicz wyniki do:

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

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

Bulletin of the Polish Academy of Sciences. Technical Sciences

2016

Vol. 64, nr 3

633--640

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.

Condition monitoring of tribosystems by wear debris analysis

Myshkin N. K., Grigoriev A. Ya., Markova L. V.

International Journal of Applied Mechanics and Engineering

2002

Vol. 7, no 3

923--947

Wear as a surface loss of material resulting from friction is considered in connection with various factors affecting a tribosystem. It is shown that debris formed at friction can be a source of valuable information on the wear mechanism and mode. The shape, texture and color of particles can be used for wear analysis. Methods of image recognition are used in order to solve the problem of debris analysis and classification for further use as a database being a part of integrated monitoring service. The concept of wear monitoring and its main purposes are considered in the context of providing non-failure, long-term operation at optimum friction performance of a tribosystem. Wear monitoring tools based on the analysis of debris accumulation in lubricated machinery are reviewed.