Wet foundations and walls of buildings significantly increase the energy consumption of buildings, and the drying of walls is one of the priority activities as part of thermal modernization, along with the insulation of the facades. This article discusses the research findings of detecting moisture decomposition within building walls utilizing electrical impedance tomography (EIT) and deep learning techniques. In particular, the focus was on algorithmic models whose task is transforming voltage measurements into spatial EIT images. Two homogeneous deep learning networks were used: CNN (Convolutional Neural Network) and LSTM (Long-Short Term Memory). In addition, a new heterogeneous (hybrid) network was built with LSTM and CNN layers. Based on the reference reconstructions’ simulation data, three separate neural network algorithmic models: CNN, LSTM, and the hybrid model (CNN+LSTM), were trained. Then, based on popular measures such as mean square error or correlation coefficient, the quality of the models was assessed with the reference images. The obtained research results showed that hybrid deep neural networks have great potential for solving the tomographic inverse problem. Furthermore, it has been proven that the proper joining of CNN and LSTM layers can improve the effect of EIT reconstructions.

Three different methods were used to obtain Bi₅Ti₃FeO₁₅ ceramics, i.e. solid-state sintering, mechanical activation (MA) with subsequent thermal treatment, and electrical discharge assisted mechanical milling (EDAMM). The structure and magnetic properties of produced Bi₅Ti₃FeO₁₅ samples were characterized using X-ray diffraction and Mössbauer spectroscopy. The purest Bi₅Ti₃FeO₁₅ ceramics was obtained by standard solid-state sintering method. Mechanical milling methods are attractive because the Bi₅Ti₃FeO₁₅ compound may be formed at lower temperature or without subsequent thermal treatment. In the case of EDAMM process also the time of processing is significantly shorter in comparison with solid-state sintering method. As revealed by Mössbauer spectroscopy, at room temperature the Bi₅Ti₃FeO₁₅ ceramics produced by various methods is in paramagnetic state.