V. Horák, V. Hrubý and T. Mrázková
The plasma nitriding process produces a hard near-surface thin layer of the nitrided material. The thickness of the diffused layer, produced in the course of this process, is between 0.001 and 0.6 mm. The paper presents a study of influence of the nitriding temperature, pressure, and time on the steel microhardness profiles. The one- dimensional transient diffusion model is applied to a thin nitrided layer. That allows one to predict the material hardness distribution within the near-surface layer as a function of time for a modified nitrogen diffusion coefficient. The temperature and pressure dependence of the diffusion coefficient is considered. Hence, the model involves the reaction rates of nitrides formation. The solution obtained in this way is compared with experimental data for a decrease of hardness as a function of depth and time, until the core hardness is reached.
Keywords: Diffusion, nitriding, surface hardness, logistic function
Y. Zhang, C. M. Bingham and M. Gallimore
Sensor fault detection and identification (SFD/I) has attracted considerable attention in military applications, especially when safety- or mission-critical issues are of paramount importance. Here, two readily implementable approaches for SFD/I are proposed through hierarchical clustering and self-organizing map neural networks. The proposed methodologies are capable of detecting sensor faults from a large group of sensors measuring different physical quantities and achieve SFD/I in a single stage. Furthermore, it is possible to reconstruct the measurements expected from the faulted sensor and thereby facilitate improved unit availability. The efficacy of the proposed approaches is demonstrated through the use of measurements from experimental trials on a gas turbine. Ultimately, the underlying principles are readily transferable to other complex industrial and military systems.
Keywords: Sensor fault detection and identification, hierarchical clustering, self-organizing map neural network, data reconstruction
Y. Zhang, C. M. Bingham and M. Gallimore
The paper presents two approaches for fault detection and discrimination based on principal component analysis (PCA). The first approach proposes the concept of y-indices through a transposed formulation of the data matrices utilized in traditional PCA. Residual errors (REs) and faulty sensor identification indices (FSIIs) are introduced in the second approach, where REs are generated from the residual sub- space of PCA, and FSIIs are introduced to classify sensor- or component-faults. Through field data from gas turbines during commissioning, it is shown that in- operation sensor faults can be detected, and sensor- and component-faults can be discriminated through the proposed methods. The techniques are generic, and will find use in many military systems with complex, safety critical control and sensor arrangements.
Keywords: Fault detection, principal component analysis, y-index, residual error, faulty sensor identification index
K. Zaplatílek and J. Leuchter
The essence of this article is finding the optimal degree of the p = f (v) real photovoltaic panel characteristics approximation polynomial. The characteristics are considered as one realization of a stochastic system and it is the result of long-term measuring. The outputs are the coefficients of an approximation polynomial of an optimal degree. For its calculation, we use the well-known Euclidean norm of residues. The advantage of this approach is that it takes all the influences on the panel’s attributes into consideration (solar irradiation, temperature, aging, random effects). It is necessary for the approximation to carry out a rotation of the measured characteristics and a backwards rotation of the approximation polynomial course. This method enables us to create a mathematical or numerical model of a real photovoltaic panel of any type. All the algorithms and experiments were done using MATLAB® system.
Keywords: Photovoltaic panel, modelling, stochastic approach, MATLAB
V. Horák, J. Komenda and L. Do Duc
The article is focussed on the quasi-dynamic analysis of the released plug assembly motion due to the acting fluid force. The request for this analysis is connected with the pressure testing of high-pressure valves. There exists a real danger of the failure of the plug clamping system causing the plug assembly to fly off. The hydrodynamic model of the problem describes the plug motion in three phases of fluid flow and was solved using the MATLAB code. Presented analysis enables us to understand how the plug assembly mass and dimensions influence the plug assembly fly off motion. Further, we can understand the effect of the test pressure and the system inner volume. This analysis provides the input data applicable for the design of a restraint system, which is part of the testing box for high-pressure valves.
Keywords: Fluid dynamics, high-pressure equipment, fluid discharge, fly off
J. Hub and J. Komenda
The article presents the simulation analysis of the main elements of the restraint system. Such system provides a protection in case of accidental ejection of plug assembly during pressure testing of high-pressure valves. The aim of the analysis is to increase safety in the operating pressure tests at the manufacturer of valves facilities for given velocity and character of plug assembly. This article presents the estimation of the limit thickness of three possible barrier materials which can be used in the construction of the restraint system elements. The analysis was performed using 2D Ansys Autodyn simulation model. Results of the analysis can be used as a basis for the design of the restraint system capable to safely absorb the shock of flying body with the energy of tens to thousands of joules.
Keywords: Pressure valve, pressure test, restraint system, limit thickness of barrier, ballistic protection, FEM simulation
Author presents a design of the artificial neural network for routing in the sensor network. The routing table is replaced by artificial neural network. The main aim is to realize this operation as fast as possible. In this paper author presents offline learning method and also real-time learning of the Artificial Neural Network (ANN). Offline learning regards to learning procedure on a general-purpose computing platform before the learned system is implemented in hardware. Real-time learning is done during the using of the system in the sensor network. Optimized neural network is implemented in the reconfigurable hardware. The paper concludes with possible future research areas.
Keywords: Artificial neural network, FPGA, network routing
M. Petrasek, S. Ignatovich, M. Karuskevich and T. Maslak
The possibility of fatigue damage analysis by the extrusion/intrusion structures on the surface of aluminium alloy is shown. Quantitative characteristics of the extrusion/intrusion structures and the methods for their monitoring are substantiated. Two approaches for fatigue analysis are presented: a) direct inspection of the aircraft components, b) application of fatigue sensors.
Keywords: Aircraft, fatigue, alclad alloy, deformation relief, fatigue sensor, structural health monitoring
Relationship between Writing Skills of Native and Foreign Languages in Military Students
N. Mocková and M. Šikolová
The article deals with research conducted on the students of Military Technology at the University of Defence and it highlights some aspects of their writing skills both in their native language (Czech) and English. English language skills are considered to be an integrated part of the profile of the graduates of Military Technology. The authors believe that writing skills in both languages are indispensable for a good scientist in all branches, including military technology. Thus the article presents one of the ways how to identify some pitfalls in learning English in students of Military Technology, and how to address them.
Keywords: Error analysis, language learning, language skills, grammar, vocabulary, military university, military students
Soldiers’ fungal and bacterial infections, especially in their feet, cause significant reduction in their performance. Copper has potent antifungal and antibacterial properties. Copper is also an essential trace element vital for the normal function of skin and wound healing. Socks containing copper oxide particles, such as socks designed to protect the feet of diabetic individuals, are commercially available in many countries. This article describes the results of a trial conducted with 53 soldiers undergoing intensive basic training. The soldiers used the socks with copper oxide daily for a period of three weeks. At the end of the trial the vast majority of soldiers reported a notorious reduction in their feet skin irritation, itching, and dryness and reduction in foot and sock odour. Reduced foot infection and discomfort improves the soldiers’ physical and mental health, increases productiveness and decreases medical treatment costs and days lost for treatment. For these reasons, and in view of the results of this trial, socks containing copper oxide particles may be an important part of every soldier’s arsenal of personal equipment.
Keywords: Athlete’s foot, biocide, copper, skin infections, socks