Qualitative evaluation of the regeneration process of a technical object in a maintenance system with an artificial neural network

被引:5
|
作者
Duer, Stanislaw [1 ]
机构
[1] Tech Univ Koszalin, Dept Mech, PL-75620 Koszalin, Poland
来源
NEURAL COMPUTING & APPLICATIONS | 2011年 / 20卷 / 05期
关键词
Servicing process; System modelling; Expert system; Artificial neural networks; Knowledge base; Diagnostics information;
D O I
10.1007/s00521-010-0418-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The present article includes a description of a qualitative evaluation of the regeneration process of a reparable technical object in a maintenance system with an artificial neural network. The delineated spaces of the operational features of a new technical object and of a technical object after regeneration in a maintenance system constitute the basis of the evaluation proposed of a maintenance system. The proposed evaluation of the maintenance system is realized in a graphical and analytical method. The graphical evaluation makes the use of the spaces of maintenance information: the operation features of a new technical object (as a model) and the spaces of maintenance information after a regeneration of an object was performed in a maintenance system. For this purpose, a nominal (model) space was described and defined of maintenance information: the operational properties of a technical object and the space of theoretical maintenance information: the current operational properties of a technical object after maintenance. In the proposed qualitative analysis of regeneration, examinations covered the level of the features of the object's operation after regeneration was performed in relation to the level of the operational properties of a new object (which was only put to operation) as a model. The resulting differences in the metrics of the distances between these spaces of the object's operational properties indicate directly the errors (the qualitative evaluation level) in the organization process of the maintenance system.
引用
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页码:741 / 752
页数:12
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