Abstract
The operating time of a diesel locomotive indicates its mechanical states to a certain scale. Though, even the same variant of diesel locomotive with the same types of operating hours shows different technical states in different types of operative environments. Therefore, it is quite intricate to obtain the data for entire life or general life prediction methods are required to study the physical failure mechanism. In pursuant of the discussed cases, mathematical model of diesel locomotive’s life estimation with respect to downward trend and neural networks is evolved in the study. Primarily, the parameters corresponds to downward trends are selected and the sample data is to be standardized & then the principal component analysis method is being used to simplify different parameters to a pervasive parameter. Method of interpolation is being used for the parameter’s time series data as the train data of neural network. Finally, the life span estimation model of the locomotive engine based on neural network is evolved.
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