Fault diagnosis is part of the maintenance system, which can reduce maintenance costs, increase productivity, and ensure the reliability of the machine system. In the fault diagnosis system, the analysis and extraction of fault signal characteristics are very important, which directly affects the accuracy of fault diagnosis. In the paper, a fast bearing fault diagnosis method based on the ensemble empirical mode decomposition (EEMD), the moth-flame optimization algorithm based on Lévy flight (LMFO) and the naive Bayes (NB) is proposed, which combines traditional pattern recognition methods meta-heuristic search can overcome the difficulty of selecting classifier parameters while solving small sample classification under reasonable time cost. The article uses a typical rolling bearing system to test the actual performance of the method. Meanwhile, in comparison with the known algorithms and methods was also displayed in detail. The results manifest the efficiency and accuracy of signal sparse representation and fault type classification has been enhanced.

In this paper, to solve the problem of detecting network anomalies, a method of forming a set of informative features formalizing the normal and anomalous behavior of the system on the basis of evaluating the Hurst (H) parameter of the network traffic has been proposed. Criteria to detect and prevent various types of network anomalies using the Three Sigma Rule and Hurst parameter have been defined. A rescaled range (RS) method to evaluate the Hurst parameter has been chosen. The practical value of the proposed method is conditioned by a set of the following factors: low time spent on calculations, short time required for monitoring, the possibility of self-training, as well as the possibility of observing a wide range of traffic types. For new DPI (Deep Packet Inspection) system implementation, algorithms for analyzing and captured traffic with protocol detection and determining statistical load parameters have been developed. In addition, algorithms that are responsible for flow regulation to ensure the QoS (Quality of Services) based on the conducted static analysis of flows and the proposed method of detection of anomalies using the parameter Hurst have been developed. We compared the proposed software DPI system with the existing SolarWinds Deep Packet Inspection for the possibility of network traffic anomaly detection and prevention. The created software components of the proposed DPI system increase the efficiency of using standard intrusion detection and prevention systems by identifying and taking into account new non-standard factors and dependencies. The use of the developed system in the IoT communication infrastructure will increase the level of information security and significantly reduce the risks of its loss.

The article examines: (i) the reasons of error due to thermoelectric inhomogeneity of electrodes of thermocouples acquired during prolonged use; (ii) the neural network method of error correction based on a generalization of verification results in several temperature fields; (iii) the method of investigating the impact of changing the speed of the conversion characteristic drift of thermocouple on error correction; (iv) results of this investigation. It is shown that residual error for type K thermocouples at the 5 % level of significance does not exceed µ±0.46 ºС and one at the 10 % level of significance does not exceed ±0.25 °С.

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The development was carried out using the Qt5.2 integrated development environment, which uses the programming language C++. The main advantage of this environment is that the code written in it can be compiled to different platforms (for example, Windows, Linux, Mac OS). A software router based on a modular architecture has been developed. It uses the socket technology, which allows forming a program-oriented packet network with any topology, including full-coupled topology. A network traffic generator to test the developed software router has been designed. We proposed a scheme to measure the packet processing time of a router using a specialized packet-capture network interface cards (NIC 1 and NIC 2) and a novel traffic generator installed on PC. Based on an experimental test bed we confirmed that our software router provides a cost-efficient alternative to the expensive, special hardware router CISCO 2801.

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Error due to inhomogeneity is the main problem of thermocouples (TCs), e.g., during the operation of a type K TC, this error can reach 11-30 °C. Thus, metrological reliability of TCs is threatened by this error because there is a high risk of exceeding the permissible error when the temperature distribution along the TC legs changes. Such a large error, in turn, can threaten a proper operation or even safety of a measured object. A TC with controlled temperature field was proposed to cope with this error. An information-measuring system to perform proper measurements, measurement data acquisition and collection to construct mathematical models is proposed. Its property is high diurnal stability of ±(0.0025+0,002(X/XMAX–1) %. The requirements for the information-measuring system and its structure are considered in this paper. In particular, one of the key problems of such a sensor is how stable is its own temperature field under the influence of the temperature field of a measured object. The experimental studies were carried out using the developed system. They showed that the coefficient of penetration of the temperature field of the measured object is about 0.04. This allows decreasing error due to inhomogeneity by about 10-20 times.

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