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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.

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This paper describes a method for increasing the accuracy and precision of temperature measurements of a liquid based on the central limit theorem. A thermometer immersed in a liquid exhibits a response with determined accuracy and precision. This measurement is integrated with an instrumentation and control system that imposes the behavioral conditions of the central limit theorem (CLT). The oversampling method exhibited an increasing measurement resolution. Through periodic sampling of large groups, an increase in the accuracy and formula of the increase in precision is developed. A measurement group sequencing algorithm and experimental system were developed to obtain the results of this system. Hundreds of thousands of experimental results are obtained and seem to demonstrate the proposed idea’s validity.