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- W4313362014 abstract "An online evolving clustering (OEC) method equivalent to ensemble modeling is proposed to tackle prognostics problems of learning and the prediction of remaining useful life (RUL). During the learning phase, OEC extracts predominant operating modes as multiple evolving clusters (EC). Each EC is associated with its own Weibull distribution-inspired degradation (survivability) model that will receive incremental online modifications as degradation signals become available. Example case studies from machining (drilling) and automotive brake-pad wear prognostics are used to validate the effectiveness of the proposed method." @default.
- W4313362014 created "2023-01-06" @default.
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- W4313362014 date "2022-12-29" @default.
- W4313362014 modified "2023-10-14" @default.
- W4313362014 title "Online System Prognostics with Ensemble Models and Evolving Clustering" @default.
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- W4313362014 doi "https://doi.org/10.3390/machines11010040" @default.
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