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Technical Brief

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

[+] Author and Article Information
Marcéu O. Adissi

Professor
Nautical Coordination,
Federal Institute of Paraíba,
Cabedelo Centro 58100-263, Paraíba, Brazil
e-mail: marceu.adissi@ifpb.edu.br

Abel C. Lima Filho

Professor
Department of Mechanical Engineering,
Federal University of Paraíba,
João Pessoa 58051-900, Paraíba, Brazil
e-mail: abel@les.ufpb.br

Ruan D. Gomes

Professor
Informatics Coordination,
Federal Institute of Paraíba,
Guarabira 58200-000, Paraíba, Brazil
e-mail: ruan.gomes@ifpb.edu.br

Diógenes M. G. B. Silva

Alternative and Renewable Energy Center,
Federal University of Paraíba,
João Pessoa 58051-900, Paraíba, Brazil
e-mail: diogenesmgbs@gmail.com

Francisco A. Belo

Professor
Department of Electrical Engineering,
Federal University of Paraíba,
João Pessoa 58051-900, Paraíba, Brazil
e-mail: belo@pq.cnpq.br

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received July 18, 2016; final manuscript received June 21, 2017; published online August 9, 2017. Assoc. Editor: Heikki Handroos.

J. Dyn. Sys., Meas., Control 139(12), 124502 (Aug 09, 2017) (8 pages) Paper No: DS-16-1354; doi: 10.1115/1.4037167 History: Received July 18, 2016; Revised June 21, 2017

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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Figures

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Fig. 1

Wireless sensor network proposed

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Fig. 2

Block diagram of the embedded system

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Fig. 3

Embedded system: (a) Closed, (b) sensors, and (c) ADPU

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Fig. 4

Fluxogram of the embedded software

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Fig. 5

Workbench for experiments in laboratory

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Fig. 6

Industry where the WSN was employed

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Fig. 7

Connections of the CTs and PTs

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Fig. 8

Measured and estimated values of torque and efficiency for the tests in the workbench: (a) with constant load and (b) with dynamic variation

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Fig. 9

Monitoring of motors: (a) M1, (b) M2, and (c) M3

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Fig. 10

Efficiency versus load curve of motor M2

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