Search

Nowadays detection of deterioration of electrical motors is an important topic of research. Vibration signals often carry diagnostic information of a motor. The authors proposed a setup for the analysis of vibration signals of three-phase induction motors. In this paper rotor fault diagnostic techniques of a three-phase induction motor (TPIM) were presented. The presented techniques used vibration signals and signal processing methods. The authors analyzed the recognition rate of vibration signal readings for 3 states of the TPIM: healthy TPIM, TPIM with 1 broken bar, and TPIM with 2 broken bars. In this paper the authors described a method of the feature extraction of vibration signals Method of Selection of Amplitudes of Frequencies – MSAF-12. Feature vectors were obtained using FFT, MSAF-12, and mean of vector sum. Three methods of classification were used: Nearest Neighbor (NN), Linear Discriminant Analysis (LDA), and Linear Support Vector Machine (LSVM). The obtained results of analyzed classifiers were in the range of 97.61 % – 100 %.

Fault diagnosis techniques of electrical motors can prevent unplanned downtime and loss of money, production, and health. Various parts of the induction motor can be diagnosed: rotor, stator, rolling bearings, fan, insulation damage, and shaft. Acoustic analysis is non-invasive. Acoustic sensors are low-cost. Changes in the acoustic signal are often observed for faults in induction motors. In this paper, the authors present a fault diagnosis technique for three-phase induction motors (TPIM) using acoustic analysis. The authors analyzed acoustic signals for three conditions of the TPIM: healthy TPIM, TPIM with two broken bars, and TPIM with a faulty ring of the squirrel cage. Acoustic analysis was performed using fast Fourier transform (FFT), a new feature extraction method called MoD-7 (maxima of differences between the conditions), and deep neural networks: GoogLeNet, and ResNet-50. The results of the analysis of acoustic signals were equal to 100% for the three analyzed conditions. The proposed technique is excellent for acoustic signals. The described technique can be used for electric motor fault diagnosis applications. [ABSTRACT FROM AUTHOR]

In this article results of diagnostic investigations of separately excited DC motor were presented. In diagnostics were applied a Fourier analysis method based on the fast Fourier transform (FFT) and a recognition method using Bayes classifier. In training process a set of the most important frequencies has been determined for which differences of corresponding signals in two states are the largest. Three categories of signals have been recognized in identification process: faultless state, state of the rotor broken one coil and state of the rotor shorted three coils.

This study aims to invent a new, low-cost, and faster method of prosthetic socket fabrication, especially in Indonesia. In this paper, the photogrammetry with the 3D printing method is introduced as the new applicative way for transradial prosthetic making. Photogrammetry is used to retrieve a 3D model of the amputated hand stump using a digital camera. A digital camera is used for photogrammetry technique and the resulting 3D model is printed using a circular 3D printer with Polylactic acid (PLA) material. The conventional casting socket fabrication method was also conducted in this study as a comparison. Both prosthetic sockets were analyzed for usability, and sectional area conformities to determine the size deviation using the image processing method. This study concludes that the manufacturing of transradial prosthetic sockets incorporating the photogrammetry technique reduces the total man-hour production. Based on the results, it can be implied that the photogrammetry technique is a more efficient and economical method compared to the conventional casting method. The 3D printed socket resulting from the photogrammetry method has a 5–19% area deviation to the casting socket but it is still preferable and adjustable for the transradial amputee when applied to the stump of the remaining hand. [ABSTRACT FROM AUTHOR]

An organic Rankine cycle (ORC) system with R123 working fluid has been utilised for generating electricity from low-temperature geothermal resources. The degree of superheated vapour warrants attention to be studied further. This is because the degree of superheated vapour is the last point to absorb heat energy from geothermal heat sources and influence the amount of expansion power produced by the expander. Therefore, achieving high ORC system efficiency requires a parameter of superheated vapour degree. This paper presents an experimental study on a binary cycle, applying R123 as the working fluid, to investigate the effect of variation in superheated vapour degree on the ORC efficiency. Geothermal heat sources were simulated with conduction oil as an external heat source to provide input heat to the ORC system. The temperature high inlet (TH in) evaporator was designed to remain at 120 °C during the experiment, while mass flow rate was adjusted to make superheated vapour variations, namely set at 278, 280, 282, 284, and 286 K. Furthermore, the effect was observed on heat transfer inlet, pinch, heat transfer coefficient, expander work output, isentropic efficiency, expander shaft power, power generation, thermal efficiency, and ORC efficiency. The experimental results showed that the mass flow rate nearly remained unchanged at different degrees of superheated vapour. The ranges of heat transfer inlet, pinch temperature, and heat transfer coefficient were 25.34–27.89 kJ/kg, 9.35–4.08 °C, 200.62–232.54 W/m2·K, respectively. In conclusion, ORC system efficiency can be triggered by various parameters, including the temperature on the exit side of the evaporator. The superheated vapour of R123 working fluid to higher temperatures has caused a decrease in ORC system efficiency due to the decrease in heat transfer inlets, although theoretically, the work total increased. Further investigation has found that the magnitude of the mass flow rate affects the behaviour of the components of the ORC system. [ABSTRACT FROM AUTHOR]