@inproceedings{3e4c53664d0e465688aae0d8fd3cd5e7,
title = "Diagnostic model for longwall conveyor engines",
abstract = "The paper presents a new approach of wall conveyor engines diagnosis. A wall conveyor is an essential device in coal mines. Its work is usually represented by three time series of current values of three conveyor engines. The startup of the conveyor is the phase with the maximal observed load during its work cycle. In the research, each startup is described with almost twenty variables. On the basis of 1000 real monitored startups, a set of association rules was inducted. On the basis of the further rules analysis and interpretation, a set of almost 50 rules was selected to the diagnosis system. The proposed diagnosis system compares the quality (precision) of each association rule from a selected subset—the precision evaluated on the representative data—with the precision of the same rule, evaluated on newly detected startups.",
keywords = "Association analysis, Association rules, Machine diagnosis",
author = "Marcin Michalak and Beata Sikora and Jurand Sobczyk",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 4th International Conference on Man–Machine Interactions, ICMMI 2015 ; Conference date: 06-10-2015 Through 09-10-2015",
year = "2016",
doi = "10.1007/978-3-319-23437-3\_37",
language = "English",
isbn = "9783319234366",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "437--448",
editor = "Tadeusz Czach{\'o}rski and Aleksandra Gruca and Agnieszka Brachman and Stanis{\l}aw Kozielski and Tadeusz Czach{\'o}rski",
booktitle = "Man–Machine Interactions - 4th International Conference on Man–Machine Interactions, ICMMI 2015",
address = "Germany",
}