Evaluation of Current Signature in Bearing Defects by Envelope Analysis of the Vibration in Induction Motors

Isac Antônio dos Santos Areias, Luiz Eduardo Borges da Silva, Erik Leandro Bonaldi, Levy Ely de Lacerda de Oliveira, Germano Lambert-Torres and Vitor Almeida Bernardes
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Isac Antônio dos Santos Areias: Institute of System Engineering and Information Technology, Itajuba Federal University, Itajuba 37500-903, Brazil
Luiz Eduardo Borges da Silva: Institute of System Engineering and Information Technology, Itajuba Federal University, Itajuba 37500-903, Brazil
Erik Leandro Bonaldi: Gnarus Institute, Itajuba 37500-052, Brazil
Levy Ely de Lacerda de Oliveira: Gnarus Institute, Itajuba 37500-052, Brazil
Germano Lambert-Torres: Gnarus Institute, Itajuba 37500-052, Brazil
Vitor Almeida Bernardes: Norte Energia, Altamira 70760-776, Brazil

Energies, 2019, vol. 12, issue 21, 1-15

Abstract: Motor current signature analysis (MCSA) enables non-invasive monitoring, without interruption of machine operation in a remote and online way, allowing the identification of various types of faults of electrical and mechanical nature without the need of accessing the motor itself, but only its supply cables. Despite its advantages, it has limitations in accurately diagnosing incipient roller bearing faults. For the detection of incipient roller bearing faults, envelope analysis of vibration signals is a well-known and stablished technique used by motor condition monitoring experts for a long time, overcoming MCSA for that purpose. Thus, it is proposed in this paper, that the fault characteristic frequencies of roller bearings are identified in the current spectrum with the aid of envelope analysis on the bearing vibration signal. After this aided identification, the fault related spectral components in the current spectrum can be correctly tracked over time for trending evaluation and decision-making. This approach can represent a significant economic value in a motor condition monitoring program, since vibration envelope analysis is performed only at a first step and, after that, its results can be applied for the MCSA monitoring of all same-model motor drivers in an industrial site. This approach is even more valuable considering the concept of the Self-Supplied Wireless Current Transducer (SSWCT) also proposed in this paper. The SSWCT is an Industrial Internet of Things (IIOT) device for MCSA application in an Industry 4.0 environment. This proposed device has wireless communication interface and wireless/battery less power supply, being supplied by the energy harvested from the magnetic field of the same currents it is transducing. So, it is a completely galvanic isolated monitoring device, without batteries and without any electric connections to the industry electric system, easily installable to the motor cables, not using precious space in the electric panels of the motor control centers and not having any physical contact to the monitored asset.

Keywords: condition monitoring; self-supplied wireless current transducer; motor current signature analysis; predictive maintenance; induction motors (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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