The main goal of this paper is to research and analyze the problem of image reconstruction performance using machine learning methods in 3D electrical capacitance tomography (ECT) and electrical impedance tomography (EIT) by comparing the areas inside the tank to determine the finite elements for which one of the method reconstructions is more effective. The research was conducted on 5000 simulated cases, which ranged from one to five inclusions generated for a cylindrical tank. The authors first used the elastic net learning method to perform the reconstruction and then proposed a method for testing the effectiveness of reconstruction. Based on this approach, the reconstructions obtained by each method were compared, and the areas within the object were identified. Finally, the results obtained from the simulation tests were verified on real measurements made with two types of tomographs. It was found that areas closer to the edge of the tank were more effectively reconstructed by EIT, while ECT reconstructed areas closer to the center of the tank. Extensive analysis of the inclusions makes it possible to use this measurement for energy optimization of industrial processes and biogas plant operation.

The research presented here concerns the analysis and selection of logistic regression with wave preprocessing to solve the inverse problem in industrial tomography. The presented application includes a specialized device for tomographic measurements and dedicated algorithms for image reconstruction. The subject of the research was a model of a tank filled with tap water and specific inclusions. The research mainly targeted the study of developing and comparing models and methods for data reconstruction and analysis. The application allows choosing the appropriate method of image reconstruction, knowing the specifics of the solution. The novelty of the presented solution is the use of original machine learning algorithms to implement electrical impedance tomography. One of the features of the presented solution was the use of many individually trained subsystems, each of which produces a unique pixel of the final image. The methods were trained on data sets generated by computer simulation and based on actual laboratory measurements. Conductivity values for individual pixels are the result of the reconstruction of vector images within the tested object. By comparing the results of image reconstruction, the most efficient methods were identified.

An uninterrupted chain of energy supplies is the core of every activity, without exception for the operations of the North Atlantic Treaty Organization. A robust and efficient energy supply is fundamental for the success of missions and a guarantee of soldier safety. However, organizing a battlefield energy supply chain is particularly challenging because the risks and threats are particularly high. Moreover, the energy supply chain is expected to be flexible according to mission needs and able to be moved quickly if necessary. In line with ongoing technological changes, the growing popularity of hydrogen is undeniable and has been noticed by NATO as well. Hydrogen is characterised by a much higher energy density per unit mass than other fuels, which means that hydrogen fuel can increase the range of military vehicles. Consequently, hydrogen could eliminate the need for risky refuelling stops during missions as well as the number of fatalities associated with fuel delivery in combat areas. Our research shows that a promising prospect lies in the mobile technologies based on hydrogen in combination with use of the nuclear microreactors. Nuclear microreactors are small enough to be easily transported to their destinations on heavy trucks. Depending on the design, nuclear microreactors can produce 1–20 MW of thermal energy that could be used directly as heat or converted to electric power or for non-electric applications such as hydrogen fuel production. The aim of the article is to identify a model of nuclear-hydrogen synergy for use in NATO operations. We identify opportunities and threats related to mobile energy generation with nuclear-hydrogen synergy in NATO operations. The research presented in this paper identifies the best method of producing hydrogen using a nuclear microreactor. A popular and environmentally “clean” solution is electrolysis due to the simplicity of the process. However, this is less efficient than chemical processes based on, for example, the sulphur-iodine cycle. The results of the research presented in this paper show which of the methods and which cycle is the most attractive for the production of hydrogen with the use of mini-reactors. The verification criteria include: the efficiency of the process, its complexity and the residues generated as a result of the process (waste)—all taking into account usage for military purposes.

The work covers the development of intelligent sensors, as well as intelligent mechanisms for the assembly and control of industrial processes using modern measurement techniques, process tomography, vision systems, motion and temperature sensors. Design/Methodology/Approach: Tomographic techniques and new analytical algorithms were used. Special algorithms have been developed to combine data from different types of measurements in real time to identify potential hazards or undesirable effects. Findings: The use of various types of data in a single decision-making process, starting with the availability of resources, availability of staff and ending with the maintenance schedules of machines, will allow for the analysis and optimisation of the process. The use of the socalled uncertain data and data that do not have an unambiguous impact on the production process requires the use of solutions based on artificial intelligence algorithms in the decision-making process, which are able to draw conclusions relatively quickly based on such data, and then quickly affect the optimisation of the production process. The results of the conducted research indicate that a platform with an open architecture can be a useful tool in the control and steering of industrial processes. Practical Implications: A measurement module that allows to unify the signal coming out of particular measurement sub-assemblies to a coherent form, thanks to which the acquisition, storage and processing of any quantity can be carried out in a similar way for each case. Originality/Value: The novelty and innovation of the system is a unique technological solution (types of measurements and data processing), new algorithms for optimisation, reconstruction and data analysis, a unique multi-module device based on tomographic technologies. The project as a whole as well as each of its components is innovative on a global scale. The use of tomography for analysis, control and monitoring of technological processes is an innovative solution.

Purpose:The aim of the article is an industrial system platform for diagnostics and control of the crystallization process with the use of tomographic technologies. Design/Methodology/Approach: Various methods are used to study crystallization processes. Here, the tomographic method has been applied. Findings: Tomography of industrial processes is a harmless, non-invasive imaging technique used in various industrial in-process technologies. It plays an important role in continuous data measurement for better understanding and monitoring of industrial processes, providing a fast and dynamic response that facilitates real-time process control, fault detection and system malfunctions. Practical Implications: Sensor networks with their feedback loops are fundamental elements of production control. A critical difference in the mass production of chemicals, metals, building materials, food and other commodities is that common process sensors provide only local measurements, e.g. temperature, pressure, fill level, flow rate or species concentration. However, in most production systems such local measurements are not representative of the entire process, so spatial solutions are required. Here the future belongs to distributed and image sensors. Originality/Value: The concept of a system based on industrial tomography represents a solution currently unavailable on the world market, in its assumptions and effects it has a legitimate character of innovation on a global scale. At the same time, it means the creation of a new, fundamentally different from those available on the market, universal product in the technological sphere. It is an innovative, efficient tool for diagnostics and process control.