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- W1570695536 abstract "A neural network (NN) based fault detection and isolation (FDI) approach for unknown non-linear system is proposed to detect both actuator and sensor faults. An enhanced parallel (independent) NN model is trained to represent the process and used to generate residual. A mean-weight strategy is developed to overcome the un-modelled noise and disturbance problem. A signal pre-processor is also developed to convert the quantitative residual to qualitative form and applied to a NN fault classifier to isolate different faults. The developed techniques are demonstrated with a multi-variable non-linear tank process." @default.
- W1570695536 created "2016-06-24" @default.
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- W1570695536 date "2006-01-01" @default.
- W1570695536 modified "2023-09-26" @default.
- W1570695536 title "Fault Diagnosis with Enhanced Neural Network Modelling" @default.
- W1570695536 cites W1482540049 @default.
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- W1570695536 doi "https://doi.org/10.1007/11760191_53" @default.
- W1570695536 hasPublicationYear "2006" @default.
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