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Application of selected Levy processes for degradation modelling of long range mine belt using real-time data

100%

Vališ D. , Mazurkiewicz D.

2018

tom Vol. 18, no. 4

1430--1440

When analysing big data generated by a typical diagnostic system, the maintenance operator has to deal with several problems, including a substantial number of data appearing every second. Maintenance systems, especially those in mining industry additionally require the operator to make reliable predictions and decisions under uncertainty. All this create so called information overload problem, which can be solved in data mining with the use of existing data reduction techniques. Unfortunately, with complex mining machinery operating under diverse conditions more advanced approaches are needed. Effective solutions can be found among non-trivial degradation assessment techniques provided which shall be properly applied. This work proposes new methods to modelling specific system degradation and prognosis for system failure occurrence. The approach presented here does not rely on typical statistical assumptions. This paper relates to mathematical modelling of real diagnostic data with the use of selected stochastic processes – types of Wiener process and Ornstein–Uhlenbeck process. The main novelty and contribution is in the specific forms of above mentioned processes, in the ways how the process parameters were estimated and also in realistic correlation of proposed models to the studied system. Simulated and real case results show that the proposed robust functional analysis reduces bias and provides more accurate false fault detection rates, as compared to the previous method. We hope the outcomes provide applicable inputs for more effective principles of system operation, predictive maintenance policy and risk assessment.

Metody pośredniego badania starzenia się systemu

80%

Vališ D. , Koucky M. , Zak L.

tom Vol. 14, No. 1

33-41

Nowadays the system requirements are set up and evaluated in various manners. We have plenty of excellent options available taking about an item technical state. We can also consider other states by many diagnostic options. The paper deals with the mathematical processing, monitoring and analysis of the oil field data got as a result from the laser spectrography in frame of the tribodiagnostic oil tests. The mathematical methods based on time series and their analysis and calculation processed by suitable method are used in the paper for oil data analysis. Due to the fact that the data sample is classified as fuzzy and uncertain from many reasons the FIS (Fuzzy Inference System) is used.

Obecnie wymagania systemu mogą być ustalane i oceniane w różny sposób. Mamy do dyspozycji wiele doskonałych opcji oceny stanu technicznego obiektów. Istnieje również wiele możliwości diagnozowania innych stanów. W artykule przedstawiono proces matematycznego przetwarzania, monitorowania i analizy danych eksploatacyjnych dotyczących oleju uzyskanych na podstawie spektrografii laserowej przeprowadzonej w ramach diagnostyki tribologicznej. Do analizy danych wykorzystano metody matematyczne oparte na szeregach czasowych oraz odpowiednie metody analizy i obliczania szeregów czasowych. Ponieważ dostępne dane sklasyfikowano jako rozmyte i niepewne, zastosowano System Wnioskowania Rozmytego FIS.