Abstract
This paper discusses the problem of diagnosing the condition of bearings in a tension leveler of a sheet mill. Due to aggressive conditions and location features, traditional vibration diagnostic methods are not applicable. The paper proposes an innovative solution based on a multizone temperature sensor. To build a model of the normal behavior of the system, a multivariate state estimation model and a neural network of the autoencoder structure were used. A comparison of the models’ performance is provided.
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