Implementation and Deployment of an Intelligent Industrial Wireless System for Induction Motor Monitoring

Abstract

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.

Assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring

“…The air-gap torque method has been extensively used in the development of real-time efficiency estimation tools for IM [9,10,20,23]. In [9] the variation of the stator resistance with temperature is not considered, which increases the estimation errors. Furthermore, in this case, friction and windage losses are considered based on the size of the motor as shown in Table 3.…”

“…To assess the energy efficiency of IM and to improve the overall performance of industrial systems, it is essential to identify energy losses, to properly apply the MEPS, and to monitoring in real-time the efficiency and load factor [9,10]. However, assessing the energy efficiency and load factor of IM, requires field measurements of the shaft power, which is very intrusive and costly based on current technology, or even by applying the standards IEEE Std-112-2004 [11] and IEC Std-60034-2-1-2007 [12].…”

Design of an Active and Passive Control System of Hand Exoskeleton for Rehabilitation

“…In addition, the rehabilitation exercises in a virtual environment will be more interesting. It will induce the patients to take the exercise more actively [26,27]. The patients will be more desired to take the exercise so the effect of rehabilitation will be better, such as Hand Mentor Pro TM (Motus Nova, Atlanta, GA, USA) [28].…”

An Improved MDS-MAP Localization Algorithm Based on Weighted Clustering and Heuristic Merging for Anisotropic Wireless Networks with Energy Holes

“…Thus it is necessary to report data with geometrical information. Nowadays, localization of sensor nodes in WSN has become a fundamental and essential service which benefits many industrial and civilian cyber-physical system applications, such as environmental monitoring, industrial control and battle fields [Adissi, Lima, Gomes et al (2017); Sundararajan, Redfern, Schneider et al (2005); Perumal, Utharaj and Christo (2014)]. Although localization is crucial in determining the source of triggering events, over complex algorithms are not supported by the light weight process unit in the network.…”