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Permanent magnet synchronous machines (PMSMs) drives are attractive and have been used in several applications, because of their noteworthy advantages. In some applications, the continuous operation is necessary, and then the PMSM drive outage is unacceptable or may cause great losses. Thus, several studies have been accomplished in order to detect incipient faults in PMSMs. In this context, the electrical signature analysis (ESA) technique is highlighted, because of the feasibility and non-invasive features. ESA allows the fault detection by only analyzing the electrical machine quantities. This paper proposes a study of ESA for PMSM condition monitoring. The review of some fault patterns is presented as well as the development of a scale model laboratory to simulate faults in a real PMSM in operation. The PMSM is used to drive a fluid pumping system, and different types of fluids are tested, being different load conditions from the PMSM point of view. The presented results are promising, encouraging ESA based methodologies for PMSM fault detection. [ABSTRACT FROM AUTHOR]

This paper presents an innovative concept for the online application of Frequency Response Analysis (FRA). FRA is a well known technique that is applied to detect damage in electric machinery. As an offline technique, the machine under testing has to be removed from service—which may cause loss of production. Experimental adaptations of FRA to online operation are usually based on the use of passive high pass coupling—which, ideally, should provide attenuation to the grid voltage, and at the same time, allow the high frequency FRA signals to be injected at the machine. In practice, however, the passive coupling results in a trade-off between the required attenuation and the useful area obtained at the FRA spectra. This paper proposes the use of an active coupling system, based on power electronics, in order to cancel the grid voltage at the terminals of FRA equipment and allow its safe connection to an energized machine. The paper presents the basic concepts of FRA and the issue of online measurements. It also presents basic concepts about power electronics converters and the operating principles of the Modular Multilevel Converter, which enables the generation of an output voltage with low THD, which is important for tracking the grid voltage with minimum error. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The condition of synchronous generators (SGs) is a matter of great attention, because they can be seen as equipment and also as fundamental elements of power systems. Thus, there is a growing interest in new technologies to improve SG protection and maintenance schemes. In this context, electrical signature analysis (ESA) is a non-invasive technique that has been increasingly applied to the predictive maintenance of rotating electrical machines. However, in general, the works applying ESA to SGs are focused on isolated machines. Thus, this paper presents a study on the condition monitoring of SGs in bulk electric systems by using ESA. The main contribution of this work is the practical results of ESA for fault detection in in-service SGs interconnected to a power system. Two types of faults were detected in an SG at a Brazilian hydroelectric power plant by using ESA, including stator electrical unbalance and mechanical misalignment. This paper also addresses peculiarities in the ESA of wound rotor SGs, including recommendations for signal analysis, how to discriminate rotor faults on fault patterns, and the particularities of two-pole SGs. [ABSTRACT FROM AUTHOR]

The culture of excellence in the area of maintenance combined with the needs of production cost reduction and increased productivity makes the reliability of electric power generation process becomes increasingly important, making room for the emergence of new maintenance techniques, especially predictive techniques that use continuous monitoring equipment systems. Predictive maintenance is the technique that establishes the planned corrective maintenance based on the changing monitored parameters. These monitored parameters may come from continuous condition monitoring system, which are more effective. Within this context, the most ancient and widespread technique is the vibration analysis. However, a relatively new technique and, until so little used, is the electrical signature analysis of generators. This paper presents the development of a predictive system for diagnosing internal combustion engines faults as well excitation and coupling through the electrical signature analysis of voltage and current signals of the generator. The main goal of this system is to obtain the signature of the electrical signals to identify the magnitude and frequency of each individual component allowing the identification of different faults in the generator group. The paper presents some measurements acquired directly through the installation of the developed system in SUAPE II thermal power plant. [ABSTRACT FROM AUTHOR]