Artificial intelligence in technical diagnostics

• Autorzy: Korbicz J.

Warianty tytułu

PL

Sztuczna inteligencja w diagnostyce technicznej

• Języki publikacji: EN

Abstrakty

EN

The paper deals with the problems of robust fault detection using soft computing techniques, particularly neural networks (Group Method of Data Handling, GMDH), neuro-fuzzy networks (Takagi-Sugeno (T-S) model) and genetic programming. The model-based approach to Fault Detection and Isolation (FDI) is considered. The main objective is to show how to employ the bounded-error approach to determine the uncertainty defined as a confidence range for the model output, the adaptive thresholds can be defined. Finally, the presented approaches are tested on a servoactuator being an FDI benchmark in the DAMADICS project.

PL

W artykule rozpatruje się problemy odpornej detekcji uszkodzeń z wykorzystaniem technik obliczeń inteligentnych, a w szczególności sieci neuronowych (Group Method of Data Handling, GMDH), sieci neuronowo-rozmytych (model Takagi-Sugeno) oraz programowania genetycznego. Rozpatruje się układ detekcji i lokalizacji uszkodzeń z modelem. Głównym celem jest pokazanie jak zastosować metodę ograniczonego błędu do wyznaczenia niepewności modeli neuronowych i rozmytych. Pokazano, że korzystając z wyznaczonych niepewnych modeli obliczeń inteligentnych zdefiniowanych w postaci przedziałów ufności dla wyjścia modelu można zdefiniować adaptacyjny próg decyzyjny. W ostatniej części efektywność rozpatrywanych podejść ilustrowana jest na przykładzie układu diagnostyki inteligentnego urządzenia siłownik-ustawnik-zawór z projektu DAMADICS.

Słowa kluczowe

EN

fault detection; robustness; adaptive threshold; neural networks; neuro-fuzzy network; genetic programming; technical diagnostics

PL

detekcja uszkodzeń; odporność; próg adaptacyjny; sieć neuronowa; sieć neuronowo-rozmyta; programowanie genetyczne; diagnostyka techniczna

• Wydawca: Polskie Towarzystwo Diagnostyki Technicznej
• Czasopismo: Diagnostyka
• Rocznik: 2008
• Tom: nr 2(46)
• Strony: 7--16
• Opis fizyczny: Bibliogr. 51 poz., rys., tab.

Twórcy

autor

Korbicz J.

• Instytut Sterowania i Systemów Informatycznych, Uniwersytet Zielonogórski, ul. Podgórna 50, 65-246 Zielona Góra,

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