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In this article, indentation process of thin-walled metal sections with quadrangular cross-section was studied under the applied lateral compressive loading by a rigid cylindrical punch through numerical simulations by the ABAQUS. Based on numerical simulations and by changing one of the parameters and fixing the other parameters, effects of that parameter was investigated on total and specific absorbed energy by the structure. In other words, influences of various geometrical dimensions such as height, width and wall thickness of cross-section, punch diameter, loading rate and also, effects of material were investigated. In each part, physical justifications of the obtained results were presented, based on theoretical and engineering concepts. Comparison of the results showed that in the specimens with the same cross-sectional perimeter, but, with different aspect ratios, the highest ratio of height/width of the cross-section, results in the best energy absorber, in the studied domain. Furthermore, by changing the height and fixing the width of cross-section and the other parameters, when height of the cross-section was selected equal to punch diameter, the maximum value of total and specific absorbed energy was achieved. But, when cross-section width changed and height and the other characteristics remained constant, by reducing the width, energy absorption performance of the structure improved. In addition, numerical simulations showed that total and specific absorbed energy of quadrangular sections are dependent on the second and first power of wall thickness of the cross-section, respectively. Also, in same specimens, by increasing punch diameter, both TAE and SAE increased.

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Gears are a very important part of mechanical equipment in industry. Due to the fact that in mechanical processes, the teeth are subjected to long-term load, the surface of their teeth is usually rusty, worn out and even broken. Timely fault detection cannot only increase the life cycle of the gears, however it can even prevent property losses and losses due to breakdowns. Therefore, it is necessary to monitor and diagnose the health of the gears to ensure the normal operation of the invaluable machines in industry. In this research, fault detection in polymer gears using audio signal is considered as a non-contact inspection method. Sound signals were recorded from 50 pairs of gears in normal condition, worn teeth and broken teeth at two speeds of 66 and 99 rpm. In the following, using wavelet packet transformation (WPT), the sound signal is analyzed in the time-frequency domain and 12 statistical features are extracted from the 16 coefficients of the fourth level of WPT. In order to study the performance of the fault detection algorithm, four classifications of linear discriminant analysis, K-nearest neighbor, decision tree and support vector machine have been used. The values of accuracy, true positive rate, true negative rate, positive predictive value, negative predictive value, geometric-mean, F1 score, and Matthews correlation coefficient have shown that by using WPT, a significant distinction can be found between normal and faulty gears. Therefore, the proposed method is a suitable approach for timely error detection of polymer gears used in mechanical equipment.