The stray flux that is present in the vicinity of an induction motor is a very interesting information source to detect several types of failures in these machines. The analysis of this quantity can be employed, in some cases, as a supportive tool to complement the diagnosis provided by other quantities. In other cases, when no other motor quantities are available, stray flux analysis can become one of the few alternatives to evaluate the motor condition. Its non-invasive nature, low cost and easy implementation makes it a very interesting option that requires further investigation. The aim of this work is to evaluate the suitability of the stray flux analysis under the starting transient as a way to detect certain faults in induction motors (broken rotor bars and misalignments), even when these types of faults coexist in the motor. To this end, advanced signal processing tools will be applied. Several positions of the flux sensors are considered in this study. Also, for the first time, a fault indicator based on the stray flux analysis under the starting is introduced and its sensitivity is compared versus other indicators relying on other quantities. It must be emphasized that, since the capture of the transient and steady-state flux signals can be carried out in the same measurement, the application of the approach presented in this work is straightforward and its derived information may become crucial for the diagnosis of some faults.

Induction motors are essential and widely used components in many industrial processes. Although these machines are very robust, they are prone to fail. Nowadays, it is a paramount task to obtain a reliable and accurate diagnosis of the electric motor health, so that a subsequent reduction of the required time and repairing costs can be achieved. The most common approaches to accomplish this task are based on the analysis of currents, which has some well-known drawbacks that may lead to false diagnosis. With the new developments in the technology of the sensors and signal processing field, the possibility of combining the information obtained from the analysis of different magnitudes should be explored, in order to achieve more reliable diagnostic conclusions, before the fault can develop into an irreversible damage. This paper proposes a smart-sensor that explores the weighted analysis of the axial, radial, and combination of both stray fluxes captured by a low-cost, easy setup, non-invasive, and compact triaxial stray flux sensor during the start-up transient through the short time Fourier transform (STFT) and characterizes specific patterns appearing on them using statistical parameters that feed a feature reduction linear discriminant analysis (LDA) and then a feed-forward neural network (FFNN) for classification purposes, opening the possibility of offering an on-site automatic fault diagnosis scheme. The obtained results show that the proposed smart-sensor is efficient for monitoring and diagnosing early induction motor electromechanical faults. This is validated with a laboratory induction motor test bench for individual and combined broken rotor bars and misalignment faults.

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Advanced analysis of motor currents for the diagnosis of the rotor condition in electric motors operating in mining facilities. IEEE Transactions on Industry Applications. 54(4):3934-3942.

This article consists of a review of the main concepts and paradigms established in the field of biological fuel cells or biofuel cells. The aim is to provide an overview of the current panorama, basic concepts and methodologies used in the field of enzymatic biofuel cells, as well as the applications of these bio-systems in flexible electronics and implantable or portable devices.Finally, the challenges needing to be addressed in the development of biofuel cells capable of supplying power to small size devices with applications in areas related to health and well-being or next generation portable devices are analyzed. The aim of this study is to contribute to biofuel cell technology development; this is a multidisciplinary topic about which review articles related to different scientific areas, from Materials Science to technology applications, can be found. With this article the authors intend to reach a wide readership in order to spread biofuel cell technology for different scientific profiles and boost new contributions and developments to overcome future challenges.

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Sensorless speed estimation has been extensively studied for its use in control schemes. Nevertheless, it is also a key step when applying Motor Current Signature Analysis to induction motor diagnosis: accurate speed estimation is vital to locate fault harmonics, and prevent false positives and false negatives, as shown at the beginning of the paper through a real industrial case. Unfortunately, existing sensorless speed estimation techniques either do not provide enough precision for this purpose or have limited applicability. Currently, this is preventing Industry 4.0 from having a precise and automatic system to monitor the motor condition. Despite its importance, there is no research published reviewing this topic. To fill this gap, this paper investigates, from both theoretical background and an industrial application perspective, the reasons behind these problems. Therefore, the families of sensorless speed estimation techniques, mainly conceived for sensorless control, are here reviewed and thoroughly analyzed from the perspective of their use for diagnosis. Moreover, the algorithms implemented in the two leading commercial diagnostic devices are analyzed using real examples from a database of industrial measurements belonging to 79 induction motors. The analysis and discussion through the paper are synthesized to summarize the lacks and weaknesses of the industry application of these methods, which helps to highlight the open problems, challenges and research prospects, showing the direction in which research efforts have to be made to solve this important problem.

Abstract-Current analysis has been widely employed in academy and industry for the diagnosis of rotor damages in cage induction motors. The conventional approach based on the FFT analysis of steady-state current (MCSA) has been recently complemented with the development of alternative techniques that rely on the time-frequency analysis of transient quantities of the machine. These techniques may bring important advantages that are related to the avoidance of eventual false indications provided by the classical MCSA. Moreover, their application is also suitable for variable speed conditions. However, the application of current-based methodologies to wound rotor induction motors (WRIM) has been much less studied and, hence, their validation in field WRIM is scarce. The present work proposes the application of an integral methodology based on the analysis of both stationary and transient currents for the diagnosis of winding asymmetries in WRIM. The method, based on up to five different fault evidences, is validated in laboratory motors and it is subsequently applied to a large field motor (1,500 kW) that was showing signs of abnormal rotor functioning. The results prove that the method is of interest for the field since it helps to ratify without ambiguity the existence of eventual asymmetries in the rotor windings, with no interference with the machine operation. However, due to the complex constructive nature of the rotor winding as well as the presence of auxiliary systems (slip rings, brushes, contactors, etc…), once the fault presence is detected, it may be interesting the utilization of complementary tools to accurately locate the root cause of the asymmetry.