Turbomachinery Degradation Monitoring Using Adaptive Trend Analysis
| Autor: | Charlotte Skourup, Arne-Marius Ditlefsen, Nina F. Thornhill, Marta Zagorowska |
|---|---|
| Přispěvatelé: | Commission of the European Communities, ABB Switzerland Ltd. |
| Jazyk: | angličtina |
| Předmět: |
Function approximation
0209 industrial biotechnology Work (thermodynamics) Computer science 020208 electrical & electronic engineering Process (computing) 02 engineering and technology Prediction methods Fault detection and isolation Convexity Exponential function 020901 industrial engineering & automation Device degradation Control and Systems Engineering Control theory Turbomachinery 0202 electrical engineering electronic engineering information engineering Trends Fault detection Compressors Degradation (telecommunications) |
| Zdroj: | IFAC-Papers 12th International-Federation-of-Automatic-Control (IFAC) Symposium on Dynamics and Control of Process Systems including Biosystems (DYCOPS) |
| ISSN: | 2405-8963 |
| DOI: | 10.1016/j.ifacol.2019.06.141 |
| Popis: | Performance deterioration in turbomachinery is an unwanted phenomenon that changes the behaviour of the system. It can be described by a degradation indicator based on deviations from expected values of process variables. Existing models assume that the degradation is strictly increasing with fixed convexity and that there are no additional changes during the considered operating period. This work proposes the use of an exponential trend approximation with shape adaptation and apply it in a moving window framework. The suggested method of adjustment makes it possible for the model to follow the evolution of the indicator over time. The approximation method is then applied for monitoring purposes, to predict future degradation. The influence of the tuning parameters on the accuracy of the algorithm is investigated and recommendations for the values are derived. Finally directions for further work are proposed. |
| Databáze: | OpenAIRE |
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