International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

Many industries, like the aviation industry and border control, rely on X-ray inspection systems for their security operations. These systems are state of the art complex electromechanical machines that need to be maintained by highly qualified service specialists. The most critical part of each x-ray inspection system is the x-ray generator. In this article, we propose a technique for remote diagnostics based on electrical and thermal telemetry monitoring. We have studied the most important electrical and thermal parameters of various conventional X-ray generators equipped with stationary anode X-ray tubes, up to 300kV acceleration voltage, and their correlation to the operational condition of the generator. The experimental results, obtained in a real operational environment, show that a limited number of monitoring parameters are enough to properly estimate the condition and diagnose some failures in X-ray generators. A simplified physical model, based on electrical and thermal parameters, has been proposed and compared with the results.

The importance of artificial lighting in our daily lives is growing, and street lighting has become a major focus over time. The creation of street lighting was motivated by the need to increase visual and property security and public safety. Current developments in metropolitan environments foreshadow the ‘smart cities’ of the future. The basic concept is that CCTV cameras, traffic lights and street lighting all have ‘smart functions’. Municipalities will be able to adapt to the needs of their inhabitants, thus increasing safety, comfort and energy efficiency. Given the adaptability of smart street lighting to the built environment, artificial intelligence is an essential element of smart cities, even in the systems already in place. Extensive sensor networks will facilitate the collection of environmental data by AI. In addition, unauthorised access to information available through IoT systems poses a serious threat. A critical point is the monitoring and protection of surveillance systems that are vital to the operation of smart systems.

The current work is related to improving security by developing a new type of fog sensors and devices. We investigate fogs and their ability to absorb and clean various pollutants from air, including chemical, biological, radiological and nuclear (CBRN) agents. Fog can be used very effectively for counteraction to terrorist attacks and weapons of mass destruction, as well as for prevention of industrial accidents and disasters. It is crucial to study the specific sizes of fog droplets, which optimally collect dangerous substances. We present a computational fluid dynamic model for estimating droplet number flow rate through a laser beam. It shows, that we can make a quantitative assessment of both the number flow rate and the droplet diameter distribution. After we have confirmed that it is possible to monitor these parameters, we proceed and investigate how they are varied, when the laser beam’s distance from the nozzle is changed. Thus, by selecting the distance between the laser beam and the nozzle, it will be possible to measure the diameters and the number of fog droplets. Different nozzles can be simulated easily by entering their output parameters (mass flow rate, diameter distribution, orifice diameter) in the setup.

This research paper demonstrates the use of experimental problem based learning tasks which students of computer science and information technology study programs realized through a semester in physics study course. In this course students had to master how to use several sensors and how to connect them to Arduino and acquire proper measurements and save them in a memory card. Students admit that in most of the experiments using Arduino as a data logger gives advantages to more easily deal with experimentation. Students appreciate that this kind of mastering physics is more related to their specialty and future work. It becomes more significant to use measuring devices not only in laboratories but also in different environments where specific data acquisition systems are necessary. Therefore with this teaching method students realize the real life needs and conditions.

The current work is related to development of sensors for contamination detection, and systems, which use fog as a cleaning agent, in order to prevent disasters and accidents, and to help acting against terrorist attacks and weapons of mass destruction. Investigations in laboratory conditions of several types of mist generators are presented. For this purpose, various products, which create aerosols, were researched. The diameter distributions of the droplets, produced by them, were experimentally determined. For development purposes, several simple devices for easy fog generation are chosen. This study is related to the development of sensors for fog with different characteristics. The obtained results allow a proper selection of sprayers to be made, so that the necessary conditions for the development of sensors are ensured.

In this paper, a novel patent-pending approach based on optical detection will be described. Various functionalized nanofiber materials have been used to demonstrate feasibility of realization of miniature sensors of biomedical and chemical values (enzymes reactions, metal ions content, etc.). Compactness and sensitivity of the sensors are significantly enhanced through original hybrid fiber-optic/nanofiber design. The potential of the new detection principle for security applications (forensic, seal intrusion, etc.) will be discussed.