A Hybrid Expert Systems Architecture for Yarn Fault Diagnosis

Dlodlo, N.; Hunter, L.; Cele, C.; Metelerkamp, R.; Botha, A. F.

Artykuł - szczegóły

Tytuł artykułu

A Hybrid Expert Systems Architecture for Yarn Fault Diagnosis

Autorzy

Dlodlo N. , Hunter L. , Cele C. , Metelerkamp R. , Botha A. F.

Wybrane pełne teksty z tego czasopisma

Identyfikatory

Warianty tytułu

Hybrydowe systemy eksperckie do rozpoznawania uszkodzeń przędzy

Języki publikacji

Abstrakty

This article describes a hybrid expert system architecture to support yarn fault diagnosis. The system uses a combination of rule-based and case-based techniques to achieve the diagnosis. Rule-based systems handle problems with well-defined knowledge bases, which limits the flexibility of such systems. To overcome this inherent weakness of rule-based systems (RBS), case-based reasoning (CBR) has been adopted to improve the performance of the expert system by incorporating previous cases in the generation of new cases. The idea of this research is to use rules to generate a diagnosis on a fault and to use cases to handle exceptions to the rules. The cases are represented using an object-oriented approach to support abstraction, re-use and inheritance features.

Artykuł ten opisuje architekturę hybrydowego systemu eksperckiego, stosowanego jako pomoc w rozpoznawaniu błędów przędzy. W celu dokonania rozpoznania uszkodzeń, system hybrydowy oparty jest na kombinacji technik, których podstawami są „reguły” i „przypadki”. Systemy oparte na „regułach” (SOR) rozwiązują problemy o dobrze znanych i określonych zasadach, co ogranicza elastyczność takich systemów. Aby pokonać tą ich nieodłączną niesprawność i polepszyć działanie systemu, zastosowano podsystemy rozpoznające przypadki (SRP), dla generacji nowych przypadków na podstawie analizy dotychczasowych. Myślą przewodnią przedstawionego opracowania jest stosowanie reguł dla generowania diagnozy, dotyczącej danego błędu i wykorzystania przypadków dla rozpatrywania odstępstw od reguł. Przypadki są reprezentowane poprzez dochodzenie do celu zorientowanie na obiekt dla wsparcia abstrakcji reguły i powtórnej realizacji zadania.

Słowa kluczowe

expert systems knowledge-based systems yarn faults case-based reasoning rule-based reasoning textiles artificial intelligence object-oriented

systemy eksperckie systemy baz wiedzy błędy przędzy systemy oparte na przypadkach systemy oparte na regułach tkaniny sztuczna inteligencja programowanie zorientowane obiektowo

Wydawca

Sieć Badawcza Łukasiewicz - Łódzki Instytut Technologiczny

Czasopismo

Fibres & Textiles in Eastern Europe

Rocznik

2007

Tom

Vol. 15, no. 2 (61)

Strony

43--49

Opis fizyczny

Bibliogr. 50 poz., rys.

Twórcy

autor

Dlodlo N.

ndlodlo@nust.ac.zw, ndlodlo@csir.co.za

National University of Science and Technology, Box AC 939, Ascot, Bulawayo, Zimbabwe
Council for Scientific and Industrial Research, National Fibre, Textile and Clothing Centre, Box 1124, Gomery Avenue, Summerstrand, Port Elizabeth, South Africa 6000

autor

Hunter L.

lawrance.hunter@nmmu.ac.za, lhunter@csir.co.za

Nelson Mandela Metropolitan University P.O. Box 7700 Port Elizabeth, South Africa 6003
Council for Scientific and Industrial Research, National Fibre, Textile and Clothing Centre, Box 1124, Gomery Avenue, Summerstrand, Port Elizabeth, South Africa 6000

autor

Cele C.

ccele@csir.co.za

Council for Scientific and Industrial Research, National Fibre, Textile and Clothing Centre, Box 1124, Gomery Avenue, Summerstrand, Port Elizabeth, South Africa 6000

autor

Metelerkamp R.

rmetler@csir.co.za

Council for Scientific and Industrial Research, National Fibre, Textile and Clothing Centre, Box 1124, Gomery Avenue, Summerstrand, Port Elizabeth, South Africa 6000

autor

Botha A. F.

afbotha@csir.co.za

Council for Scientific and Industrial Research, National Fibre, Textile and Clothing Centre, Box 1124, Gomery Avenue, Summerstrand, Port Elizabeth, South Africa 6000

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Typ dokumentu

Bibliografia

Identyfikator YADDA

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