An attempt has been made to establish a time-discrete neuron model which ir applied to build Radial Basis Function and Multilayer Perceptron networks with distributed dynamics. The well known delta-rule is extended to...
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ISBN:
(纸本)3540594973
An attempt has been made to establish a time-discrete neuron model which ir applied to build Radial Basis Function and Multilayer Perceptron networks with distributed dynamics. The well known delta-rule is extended to the dynamic delta-rule in order to optimize network parameters. Both network types were used to identify empirical parametrical models of a turbocharger of a Diesel engine which comply with the demanded accuracy properties to a high degree. The performance of both network types is compared according to required number of parameter approximation accuracy and computational effort.
Based on the dynamic neuron model-the so called dynamic elementary processor-a dynamic multilayer perceptron neural net (DMLP) is applied to identify black box models of the process. The dynamic adaption algorithm is ...
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Based on the dynamic neuron model-the so called dynamic elementary processor-a dynamic multilayer perceptron neural net (DMLP) is applied to identify black box models of the process. The dynamic adaption algorithm is briefly introduced and compared to other adaption procedures. However, the identified models are used to build the first step of a fault diagnosis scheme (FDS) similar to observer based schemes. The residuals between the measured process output and the outputs estimated by the bank models are used as numerical symptoms for the fault detection and diagnosis. The FDS was successfully applied to monitor the turbine state of a turbosupercharger.< >
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