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.
The aim of this publication is to design a procedure for the synthesis of an IDT (interdigital transducer) with diluted electrodes. The paper deals with the surface acoustic waves (SAW) and the theory of synthesis of the asymmetrical delay line with the interdigital transducer with diluted electrodes. The authors developed a theory, design, and implementation of the proposed design. They also measured signals. The authors analysed acoustoelectronic components with SAW: PLF 13, PLR 40, delay line with PAV 44 PLO. The presented applications have a potential practical use.
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