This paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...

The paper presents an atomic force microscopy (AFM)-based approach to evaluation of local protective properties of organic coatings. Apart from topography, it provides local ac and dc characteristics of examined coating. The method consists in application of ac voltage perturbation signal between conductive AFM tip and coated metal substrate. The resulting current is used to determine local impedance characteristics. Both impedance...