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The article describes modeling and simulation of the vehicle physical model. The vehicle model is simplified and it is made up of body and 4 tires. The model contains elementary information of the vehicle geometry - dimensions and center of gravity position. These information about the vehicle are sufficient for mathematical description of vehicle. The model is made of basic elements like engine, gearbox, differential and tires, which are represented by blocks. The model includes also other blocks, which are used to show measured outputs and control blocks, that make the vehicle mechatronic systems controllable according the driver model inputs. There are also studied the forces on tires and the engine speed of the vehicle model. [ABSTRACT FROM AUTHOR]

The subject of this article is an introduction of the concept of a device for deep drawing in extreme conditions. In this case, extreme conditions represents drawing process in vacuum by high temperatures required by molybdenum sheets forming. The first part of the paper is about the functional, structural, economical, technological, operational, safety, environmental, legal and design requirements. The second part of the article deals with description of possible variants of the mechanism structure. The paper describes also the results of the research work by evaluating the variants. The variants scores were rated by parameters, which are essential for properly work of the mechatronic system. [ABSTRACT FROM AUTHOR]

• The friction coefficient of molybdenum strip in contact with steel tool was tested. • Molybdenum specimens were tested by various temperatures and drawbead heights. • Higher temperatures reduced measured forces and increased the friction coefficient. • Molybdenum deep drawing is possible by lower temperatures without vacuum. The aim of the presented study was to perform the strip test of 0.5 mm thick molybdenum strip specimens by various simulated drawbead heights from 2 mm up to 6 mm and various temperatures from 20 °C up to 320 °C to obtain friction coefficients between the molybdenum strip and steel cylinders built-in the developed test device simulating the drawbead. The friction coefficients between the dry and lubricated molybdenum strip and the steel cylinders simulating the drawbeads were obtained by changing its value in the bilinear friction model and matching the holder drawing force and the drawbead restraint force curves achieved during the tests and the simulations. The increasing temperature of molybdenum strip led to reduced holder drawing force and drawbead restraint force and increased friction coefficient because of the decrease of molybdenum strip yield strength and the increase of surface contact between molybdenum sheet and the testing tool at elevated temperature. [ABSTRACT FROM AUTHOR]

As a new intelligent optimization algorithm, the African vultures optimization algorithm (AVOA) has been widely used in various fields today. However, when solving complex multimodal problems, the AVOA still has some shortcomings, such as low searching accuracy, deficiency on the search capability and tendency to fall into local optimum. In order to alleviate the main shortcomings of the AVOA, a nonlinear African vulture optimization algorithm combining Henon chaotic mapping theory and reverse learning competition strategy (HWEAVOA) is proposed. Firstly, the Henon chaotic mapping theory and elite population strategy are proposed to improve the randomness and diversity of the vulture's initial population; Furthermore, the nonlinear adaptive incremental inertial weight factor is introduced in the location update phase to rationally balance the exploration and exploitation abilities, and avoid individual falling into a local optimum; The reverse learning competition strategy is designed to expand the discovery fields for the optimal solution and strengthen the ability to jump out of the local optimal solution. HWEAVOA and other advanced comparison algorithms are used to solve classical and CEC2022 test functions. Compared with other algorithms, the convergence curves of the HWEAVOA drop faster and the line bodies are smoother. These experimental results show the proposed HWEAVOA is ranked first in all test functions, which is superior to the comparison algorithms in convergence speed, optimization ability, and solution stability. Meanwhile, HWEAVOA has reached the general level in the algorithm complexity, and its overall performance is competitive in the swarm intelligence algorithms. [ABSTRACT FROM AUTHOR]

• The acoustic based fault diagnosis technique is proposed for detection of bearings and ventilation faults of power tools. • Six acoustic signals of motors were measured and analyzed. • Feature extraction methods SMOFS-NFC is presented. • Results of the analysis were shown. • The acoustic based analysis is useful for analysis of electrical and other mechanical faults of machines. Electric motors use about 68% of total generated electricity. Fault diagnosis of electrical motors is an important task, because it allows saving a large amount of money and time. An analysis of acoustic signals is a promising tool to improve the accuracy of fault diagnosis. It is essential to analyze acoustic signals to assess the state of the motor. In this paper, three electric impact drills (EID) were analyzed using acoustic signals: healthy EID, EID with damaged rear bearing, EID with damaged front bearing. Three angle grinders (AG) were analyzed: healthy AG, AG with 1 blocked air inlet, AG with 2 blocked air inlets. The authors proposed a method for feature extraction: SMOFS-NFC (Shortened Method of Frequencies Selection Nearest Frequency Components). Acoustic features vectors were classified by the nearest neighbor classifier and Naive Bayes classifier. The classification accuracy were in the range of 89.33–97.33% for three electric impact drills. The classification accuracy were in the range of 90.66–100% for three angle grinders. The presented method is very useful for diagnosis of bearings, ventilation faults and other mechanical faults of power tools. It can be also useful for diagnosis of similar power tools. [ABSTRACT FROM AUTHOR]