Inteligent performance analysis with a natural language interface

• Autorzy: Juuso E. K.

Identyfikatory

DOI

10.1515/mspe-2017-0025

Warianty tytułu

PL

Inteligentna analiza wydajności z interfejsem naturalnego języka

• Języki publikacji: EN

Abstrakty

EN

Performance improvement is taken as the primary goal in the asset management. Advanced data analysis is needed to efficiently integrate condition monitoring data into the operation and maintenance. Intelligent stress and condition indices have been developed for control and condition monitoring by combining generalized norms with efficient nonlinear scaling. These nonlinear scaling methodologies can also be used to handle performance measures used for management since management oriented indicators can be presented in the same scale as intelligent condition and stress indices. Performance indicators are responses of the process, machine or system to the stress contributions analyzed from process and condition monitoring data. Scaled values are directly used in intelligent temporal analysis to calculate fluctuations and trends. All these methodologies can be used in prognostics and fatigue prediction. The meanings of the variables are beneficial in extracting expert knowledge and representing information in natural language. The idea of dividing the problems into the variable specific meanings and the directions of interactions provides various improvements for performance monitoring and decision making. The integrated temporal analysis and uncertainty processing facilitates the efficient use of domain expertise. Measurements can be monitored with generalized statistical process control (GSPC) based on the same scaling functions.

PL

Najważniejszym celem zarządzania aktywami jest poprawa wydajności. Zaawansowana analiza danych jest potrzebna, aby efektywnie integrować dane monitorowania stanu maszyn podczas działania i konserwacji. Inteligentne wskaźniki obciążeń i stanu zostały opracowane w celu kontroli i monitorowania stanu poprzez połączenie uogólnionych norm z efektywnym skalowaniem nieliniowym. Nieliniowe metody skalowania mogą być również wykorzystane do pomiarów wydajności używanych do zarządzania, ponieważ wskaźniki zarządzania mogą być prezentowane w tej samej skali co inteligentne wskaźniki stanu i obciążeń. Wskaźniki efektywności to odpowiedzi procesu, maszyny lub systemu, na obciążenia analizowane z danych pochodzących z monitorowania procesu i stanu. Skalowane wartości są bezpośrednio stosowane w inteligentnej analizie czasowej do obliczania fluktuacji i trendów. Wszystkie te metody mogą być stosowane w prognostyce i przewidywaniu obciążenia. Znaczenie zmiennych jest korzystne w zdobywaniu wiedzy eksperckiej i prezentowaniu informacji w języku naturalnym. Idea dzielenia problemów na znaczenie w zmienności specyficznych i kierunków interakcji, zapewnia wiele ulepszeń w monitorowaniu wydajności i podejmowaniu decyzji. Zintegrowana analiza czasowa i przetwarzanie niepewności ułatwiają efektywne wykorzystanie wiedzy specjalistycznej. Pomiary mogą być monitorowane za pomocą uogólnionej statystycznej kontroli procesu (GSPC) opartej o te same funkcje skalowania.

Słowa kluczowe

EN

data analysis; nonlinear scaling; trend analysis; fuzzy systems; natural language

PL

analiza danych; skalowanie nieliniowe; analiza trendu; systemy rozmyte; język naturalny

• Wydawca: STE GROUP
• Czasopismo: Management Systems in Production Engineering
• Rocznik: 2017
• Tom: nr 3 (25)
• Strony: 168--175
• Opis fizyczny: Bibliogr. 52 poz., rys., tab.

Twórcy

autor

Juuso E. K.

• Control Engineering, Faculty of Technology Pentti Kaiteran katu 1, 90014 Oulu, FINLAND

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)