The three-phase induction motor (TIM) is present in most industrial processes, being the main responsible for the electromechanical conversion in the sector. The total breakdown of these machines can compromise the production of entire sectors in a manufacturing environment, hence the need for early fault detection. In this context, broken bar failures are the most common on the TIM rotor. The present work analyzes the chaotic behavior of one stator current of a TIM, with different levels of broken rotor bar failures. The characterization of the failure is performed by analyzing the behavior of the chaotic variable called density of maxima. The proposed approach has advantages over classic Motor Current Signature Analysis techniques in that it does not require long acquisition windows (in this work it was possible to perform detection using a range of 0.35 s) and enables fault detection even for motors operating under variable load or with low slip. The technique also has a lower computational cost compared to classical detection methods. The obtained results indicate that the method is also able to identify different severity levels with the TIM under nominal load.

Three-phase induction motors (TIMs) are present in most industrial processes, accounting for more than 60% of the energy consumption in industry. Despite their importance in the productive sector, few motors are properly monitored, mainly due to the high cost of the monitoring equipment and the invasiveness in their installation. This paper presents the implementation and deployment of an industrial wireless sensor network (WSN) to monitor three-phase induction motors. Embedded systems were developed to acquire signals of current and voltage from sensors installed in the motors' terminals, perform local processing to estimate torque and efficiency, and transmit the information through the WSN. The method used to estimate the variables is based on the air-gap torque method. Before the deployment in the industry, experiments were performed to validate the system in laboratory. Finally, the system was employed in a real industrial environment, where different analyses and diagnosis of three motors running were performed. Using the proposed system, the efficiency versus load curves of the motors could be obtained continuously, and an energy loss analysis due to the oversizing of the motors was performed.

Induction motors (IMs) are present in practically all production processes and account for two-thirds of the energy consumption in industrial settings. Therefore, monitoring them is essential to prevent accidents, optimize production, and increase energy efficiency. Monitoring methods found in the literature require a certain level of invasiveness, causing some applications to be unfeasible. In the present study, a new completely non-invasive method implemented in an embedded system performs the embedded processing of the sound signal emitted by an in-service IM to estimate speed, torque, and efficiency. Motor speed is estimated from the analysis in the frequency domain using the Fourier Transform. Torque and efficiency are estimated from the speed and motor nameplate information. To perform the tests and validate the proposed method/system, a workbench with a controllable torque was used. The workbench was also equipped to allow the results to be compared with the airgap torque method. The results indicate a high accuracy for the nominal load (error of approximately 1%) in the measurement of the efficiency and torque, and a mean relative error of 0.2% for the speed.

Este trabalho tem como proposta determinar diferentes concentrações da mistura água-álcool utilizando um campo de temperatura periódico. Para isso, foi construído um dispositivo experimental com princípio de funcionamento no método de Angstrom, o qual faz uso de um fluxo de calor periódico de uma fonte controlada, gerando, assim, um campo de temperatura periódico na amostra de teste. Termopares foram instalados na amostra e num ponto de referência para captar o sinal de temperatura gerado pelo fluxo de calor periódico. A amplitude e a fase desses sinais serão obtidas por meio de um sistema de aquisição de dados. O termopar posicionado na parede do tubo foi adotado como referência em relação ao sinal térmico adquirido pelo termopar da amostra. Foram realizadas simulações computacionais com base no modelo matemático teórico, considerando a condução de calor unidimensional para obter a resposta periódica da temperatura medida no centro do tubo cilíndrico. A Técnica da Transformada Integral Generalizada (TTIG) foi utilizada para resolver o problema de difusão de calor e determinar o campo de temperatura, gerando resultados teóricos. As amostras utilizadas neste trabalho foram preparadas com frações volumétricas de 0,3%, 4,2%, 8,2%, 12,1%, 16,2% e 19,7% m/m de álcool etílico misturadas com água destilada.