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.
Highlights
In industry, fault detection and identification of causes and consequences of failures are performed by operators
In order to correctly identify, in the current spectrum, the correct localized fault frequencies of roller bearings, this paper proposes the use of the envelope analysis of vibration signal as a first step
In line with the new trends related to the condition monitoring of assets in industry 4.0, the internet of things and environment energy harvesting, this paper proposes the implementation of the presented approach in a concept device of a Self-Supplied Wireless Current Transducer (SSWCT)
Summary
Fault detection and identification of causes and consequences of failures are performed by operators. In order to correctly identify, in the current spectrum, the correct localized fault frequencies of roller bearings, this paper proposes the use of the envelope analysis of vibration signal as a first step. This paper proposes, as a first step in the process of monitoring localized roller bearing faults with the MCSA technique, the use of the vibration envelope as an aiding tool for the spectral component identification. The MCSA technique is not the best one for roller bearing fault detection but it has some advantages for long-term monitoring: for example, it allows the concept of the self-supplied wireless current transducer, SSWCT, that is a self-contained module to be installed in motor cables, not being exposed to the motor rough environment. Where fe is the power supply frequency and m is a positive integer referring to the vibration
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