90 research outputs found

    Transient-Based Rotor Cage Assessment in Induction Motors Operating With Soft Starters

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    [EN] The reliable assessment of the rotor condition in induction motors is a matter of increasing concern in the industry. Although rotor damages are more likely in line-started motors operating under high inertias, some cases of broken rotor bars in motors supplied via soft starters have been also reported in the industry. Motor current signature analysis (MCSA) is the most widely spread approach to diagnose such failures. However, its serious drawbacks in many real industrial applications have encouraged investigation on alternative methods enhancing the reliability of the diagnosis. This paper extends a recently introduced diagnosis methodology relying on the startup current analysis to the case of soft-starter-operated motors. The approach has proven to provide very satisfactory results, even in cases where the classical MCSA does not lead to correct diagnosis conclusions. However, its extension to operation under soft starters was still a pending issue. The experimental results shown in this paper ratify the validity of the proposed diagnosis approach in soft-starteroperated induction motors.This work was supported by the Spanish “Ministerio de Economía y Competitividad” (MINECO) in the framework of the “Proyectos I+D del Subprograma de Generación de Conocimiento, Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia” under Grant DPI2014-52842-PCorral Hernández, JÁ.; Antonino-Daviu, J.; Pons Llinares, J.; Climente Alarcón, V.; Francés-Galiana, V. (2015). Transient-Based Rotor Cage Assessment in Induction Motors Operating With Soft Starters. IEEE Transactions on Industry Applications. 51(5):3734-3742. https://doi.org/10.1109/TIA.2015.2427271S3734374251

    Influence of the start-up system in the diagnosis of faults in the rotor of induction motors using the Discrete Wavelet Transform

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    [EN] In previous articles, both the procedure and the advantages of the use of advanced mathematical tools,(as for example the Discrete Wavelet Transforms (DWT) and the continuous wavelet transforms (CWT)), for the time-frequency analysis of current signals captured in the stator during transients of starting and stopping have been deeply justified. The purpose of this analysis is the detection of rotor asymmetries as well as of possible eccentricities in induction motors. This article aims to analyze, from a qualitative point of view, the influence of the starting system on the results of the diagnosis method based on the analysis of the start-up current by using the DWT. Likewise, emphasis made on the impact and influence in the Wavelet Analysis (either through DWT or CWT) of harmonics introduced by the network, the motor itself and the possible fluctuations in the load torque. The results demonstrate the validity of the method, which presents a great robustness, regardless of the starting method or operating conditions. The theoretical conclusions were supported by actual measurements obtained in laboratory motors.Corral Hernandez, JA.; Antonino Daviu, JA. (2016). Influence of the start-up system in the diagnosis of faults in the rotor of induction motors using the Discrete Wavelet Transform. Procedia Computer Science. 83:807-815. doi:10.1016/j.procs.2016.04.170S8078158

    Advances in the Field of Electrical Machines and Drives

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    Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications

    Remote machine condition monitoring based on power supply measurements

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    The most widely used rotating machines in the industry are three phase alternative current (AC) induction machines. With the advances in variable speed drive (VSD) technology, they have become even more reliable than their direct current (DC) counterpart. However, inevitably these motors soon begin to fail with time due to mechanical, electrical or thermal stress hence the need for condition monitoring (CM). Condition monitoring systems help keep machines running productively by detecting potential equipment failures before it actually fails. Many condition monitoring methods exist on the market including vibration monitoring; acoustic emission monitoring, thermal monitoring, chemical monitoring, current monitoring but most of these methods require additional sensors and expensive data acquisition system on top of a specialise software tool. This all increases the cost of ownership and maintenance. For more efficient monitoring of induction motor drive systems, this research investigates an innovative remote monitoring system using existing data available in AC drives based on AC motor operating process. This research uses standard automation components already present in most automated control systems. A remote data communication platform is developed, allowing access to the control data remotely over a wireless network and internet using PLC and SCADA system. Remote machine condition monitoring is not a new idea but its application to machine monitoring based on power supply parameters indirectly measured by an inverter is new. To evaluate the basic performance of the platform, the monitoring of shaft misalignment, a typical fault in mechanical system is investigated using an in-house gearbox test rig. It has resulted in a model based detection method based on different speed and load settings against the motor current feedback read by the inverter. The results have demonstrated that the platform is reliable and effective. In addition the monitoring method can be employed to detect and diagnose different degrees of misalignment in real time. This dissertation has major contributions to knowledge which includes: Understanding of real life machine condition monitoring problems for this application, including use of wireless sensor, communication over Industrial Ethernet and network security. The use of standard automation components (PLC and SCADA) in machine condition monitoring. MSc Research (Engineering) Thesis x An improved gearbox test rig platform which has the capability of remote control, acquiring and transferring data for monitoring induction machine drive system. The presented work shows that any machine using automated components such as PLC and SCADA and incorporating motor drive systems and other actuators has the potential to use the automated components for control, condition monitoring and reporting but this will require more tests to be done using the proposed platform

    Effective algorithms for real-time wind turbine condition monitoring and fault-detection

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    Reliable condition monitoring (CM) can be an effective means to significantly reduce wind turbine (WT) downtime, operations and maintenance costs and plan preventative maintenance in advance. The WT generator voltage and current output, if sampled at a sufficiently high rate (kHz range), can provide a rich source of data for CM. However, the electrical output of the WT generator is frequently shown to be complex and noisy in nature due to the varying and turbulent nature of the wind. Thus, a fully satisfactory technique that is capable to provide accurate interpretation of the WT electrical output has not been achieved to date. The objective of the research described in this thesis is to develop reliable WT CM using advanced signal processing techniques so that fast analysis of non-stationary current measurements with high diagnostic accuracy is achieved. The diagnostic accuracy and reliability of the proposed techniques have been evaluated using data from a laboratory test rig where experiments are performed under two levels of rotor electrical asymmetry faults. The experimental test rig was run under fixed and variable speed driving conditions to investigate the kind of results expected under such conditions. An effective extended Kalman filter (EKF) based method is proposed to iteratively track the characteristic fault frequencies in WT CM signals as the WT speed varies. The EKF performance was compared with some of the leading WT CM techniques to establish its pros and cons. The reported experimental findings demonstrate clear and significant gains in both the computational efficiency and the diagnostic accuracy using the proposed technique. In addition, a novel frequency tracking technique is proposed in this thesis to analyse the non-stationary current signals by improving the capability of a continuous wavelet transform (CWT). Simulations and experiments have been performed to verify the proposed method for detecting early abnormalities in WT generators. The improved CWT is finally applied for developing a new real-time CM technique dedicated to detect early abnormalities in a commercial WT. The results presented highlight the advantages of the improved CWT over the conventional CWT to identify frequency components of interest and cope with the non-linear and non-stationary fault features in the current signal, and go on to indicate its potential and suitability for WT CM.</div

    Methods to reduce the starting current of an induction motor.

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    Doctoral Degree. University of KwaZulu-Natal, Durban.Power system loads that have high starting currents are a serious source of concern in smaller grids or remote locations on the main grid. This problem is envisaged to be exacerbated by the rollout of smart microgrids. When a high power induction motor is turned on in such a power system, its inrush current can be up to about ten times the full-load current. This transient current can cause problems when attached to weak grids. The increased current is due to the power required to start the load and the increased reactive power demand during the starting process. To protect the grid connection as well as the load, energy storage units can be used to compensate for the increased power requirement. A more pragmatic approach is to reduce the reactive power requirement using tuned compensation capacitors in order to reduce the inrush current. The aim of this research is to address the selection, calculation and switching of the capacitor bank for reactive power compensation. The capacitors are calculated and switched on to compensate the starting transient and disconnected when the machine has run up to speed using a point-on switching approach that reduces the switching transient

    Electrical and magnetic faults diagnosis in permanent magnet synchronous motors

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    Permanent magnet synchronous motors (PMSMs) are an alternative in critical applications where high-speed operation, compactness and high efficiency are required. In these applications it is highly desired to dispose of an on-line, reliable and cost-effective fault diagnosis method. Fault prediction and diagnosis allows increasing electric machines performance and raising their lifespan, thus reducing maintenance costs, while ensuring optimum reliability, safe operation and timely maintenance. Consequently this thesis is dedicated to the diagnosis of magnetic and electrical faults in PMSMs. As a first step, the behavior of a healthy machine is studied, and with this aim a new 2D finite element method (FEM) modelbased system for analyzing surface-mounted PSMSs with skewed rotor magnets is proposed. It is based on generating a geometric equivalent non-skewed permanent magnet distribution which accounts for the skewed distribution of the practical rotor, thus avoiding 3D geometries and greatly reducing the computational burden of the problem. To diagnose demagnetization faults, this thesis proposes an on-line methodology based on monitoring the zero-sequence voltage component (ZSVC). Attributes of the proposed method include simplicity, very low computational burden and high sensibility when compared with the well known stator currents analysis method. A simple expression of the ZSVC is deduced, which can be used as a fault indicator parameter. Furthermore, mechanical effects arising from demagnetization faults are studied. These effects are analyzed by means of FEM simulations and experimental tests based on direct measurements of the shaft trajectory through self-mixing interferometry. For that purpose two perpendicular laser diodes are used to measure displacements in both X and Y axes. Laser measurements proved that demagnetization faults may induce a quantifiable deviation of the rotor trajectory. In the case of electrical faults, this thesis studies the effects of resistive unbalance and stator winding inter-turn short-circuits in PMSMs and compares two methods for detecting and discriminating both faults. These methods are based on monitoring and analyzing the third harmonic component of the stator currents and the first harmonic of the ZSVC. Finally, the Vold-Kalman filtering order tracking algorithm is introduced and applied to extract selected harmonics related to magnetic and electrical faults when the machine operates under variable speed and different load levels. Furthermore, different fault indicators are proposed and their behavior is validated by means of experimental data. Both simulation and experimental results show the potential of the proposed methods to provide helpful and reliable data to carry out a simultaneous diagnosis of resistive unbalance and stator winding inter-turn faults

    Proceedings of the 8th International Conference EEMODS'2013 Energy Efficiency in Motor Driven Systems

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    This book contains the papers presented at the eighth international conference on Energy Efficiency in Motor Driven Systems EEMODS 2013 EEMODS 2013 was organised in Rio de Janeiro, Brasil from 28 to 30 October 2013. This major international conference, which was previously been staged in Lisbon (1996), London (1999), Treviso (2002), Heidelberg (2005), Beijing (2007), Nantes (2009) and Washington DC (2011) has been very successful in attracting an international and distinguished audience, representing a wide variety of stakeholders in policy implementation and development, manufacturing and promotion of energy-efficient motor systems, including key policy makers, equipment manufacturers, academia and end-users. Potential readers who may benefit from this book include researchers, engineers, policymakers, energy agencies, electric utilities, and all those who can influence the design, selection, application, and operation of electrical motor driven systems.JRC.F.7-Renewables and Energy Efficienc
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