Combination of Noninvasive Approaches for General Assessment of Induction Motors

[EN] There exists no single quantity able to diagnose all possible failures taking place in induction motors. Currents and vibrations monitoring are rather common in the industry, but each of these quantities alone can only detect some specific failures. Moreover, even for the specific faults that a quantity is supposed to detect, many problems may rise. As a consequence, a reliable and general diagnosis system cannot rely on a single quantity. On the other hand, it would be desirable to rely on quantities that can be measured in a noninvasive way, which is a crucial requirement in many industrial applications. This paper proposes a twofold method to detect electromechanical failures in induction motors. The method relies on analysis of currents (steady state + transient) combined with analysis of infrared data captured by using appropriate cameras. Each of these noninvasive techniques may provide complementary information that may be very useful to diagnose an enough wide range of failures. In the present paper, the detection of three illustrative faults is analyzed: broken rotor bars, cooling system problems and bearing failures. The results show the potential of the methodology that may be particularly suitable for large, expensive motors, where the prevention of eventual failures justifies the costs of such system, due to the catastrophic implications that these unexpected faults may have.Picazo-Rodenas, MJ.; Antonino-Daviu, J.; Climente Alarcon, V.; Royo, R.; Mota-Villar, A. (2015). Combination of Noninvasive Approaches for General Assessment of Induction Motors. IEEE Transactions on Industry Applications. 51(3):2172-2180. doi:10.1109/TIA.2014.2382880S2172218051

Detection of Field Winding Faults in Synchronous Motors via Analysis of Transient Stray Fluxes and Currents

(c) 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] The detection of rotor failures in synchronous motors is a matter of primordial interest in many industrial sites where these machines are critical assets. However, due to the particular operation of these motors, most conventional techniques relying on steady-state analysis, commonly used in other electric machines, are not applicable to such motors. In this context, it has been recently proven that the analysis of different quantities under transient operation of the motor and, more specifically, under motor starting can provide crucial information for the diagnosis of many faults. This work proposes the time-frequency analysis of stray fluxes and currents to detect field winding faults in synchronous motors. The potential consequences of this fault can be catastrophic for the motor integrity, so that the detection of its presence in its early stages can be of critical importance for the industry. The results included in this paper prove the usefulness of the transient analysis of such non-invasive quantities not only to detect the presence of the field winding fault but also to set a starting point to determine its severity.This work was supported by the Spanish Ministerio de Ciencia Innovación y Universidades and FEDER program in the framework of the Proyectos de I+D de Generación de Conocimiento del Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema de I+D+i, Subprograma Estatal de Generación de Conocimiento (ref: PGC2018-095747-B-I00).Tian, P.; Antonino Daviu, JA.; Platero, C.; Dunai, L. (2021). Detection of Field Winding Faults in Synchronous Motors via Analysis of Transient Stray Fluxes and Currents. IEEE Transactions on Energy Conversion. 36(3):2330-2338. https://doi.org/10.1109/TEC.2020.3041643S2330233836

Experimental Study of Frequency Oscillations in Islanded Power System

Since the introduction of power electronics to the grid, the power system has quickly changed. Fault detection and removal is performed more accurately and at quicker response time, and non-inertia driven loads have been added. This means stability must continue to be a main topic of concern to maintain a stable synchronized grid. In this thesis a lab was designed, constructed, and tested for the purpose of studying transient stability in power systems. Many different options were considered and researched, but the focus of this paper is to describe the options chosen. The lab must be safe to operate and work around, have flexibility to perform many different type of experiments, and accurately simulate a power system. The created lab was then tested to observe the impact of PSS on an unsynchronized generator connected to a static load. The lab performed as designed, which allows for the introduction of more machines to create the IEEE 14 Bus grid

Detection of nonadjacent rotor faults in induction motors via spectral subtraction and autocorrelation of stray flux signals

(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] In this paper, statistical signal processing techniques are applied to electromotive force signals captured in external coil sensors for adjacent and nonadjacent broken bars detection in induction motors. An algorithm based on spectral subtraction analysis is applied for broken bar identification, independent of the relative position of the bar breakages. Moreover, power spectrum analyses enable the discrimination between healthy and faulty conditions. The results obtained with experimental data prove that the proposed approach provides good results for fault detectability. Moreover, the identification of the faults, and the signal correlation indicator to prove the results are also presented for different positions of the flux sensor.This work was supported in part by MEC under Project MTM 2016-7963-P and in part by the Spanish 'Ministerio de Ciencia Innovacion y Universidades' and FEDER program in the framework of the 'Proyectos de I+D de Generacion de Conocimiento del Programa Estatal de Generacion de Conocimiento y Fortalecimiento Cientifico y Tecnologico del Sistema de I+D+i, Subprograma Estatal de Generacion de Conocimiento' (ref: PGC2018-095747-B-I00).Iglesias-Martínez, ME.; Fernández De Córdoba, P.; Antonino Daviu, JA.; Conejero, JA. (2019). Detection of nonadjacent rotor faults in induction motors via spectral subtraction and autocorrelation of stray flux signals. IEEE Transactions on Industry Applications. 55(5):4585-4594. https://doi.org/10.1109/TIA.2019.2917861S4585459455

Performance of Induction Machines

Induction machines are one of the most important technical applications for both the industrial world and private use. Since their invention (achievements of Galileo Ferraris, Nikola Tesla, and Michal Doliwo-Dobrowolski), they have been widely used in different electrical drives and as generators, thanks to their features such as reliability, durability, low price, high efficiency, and resistance to failure. The methods for designing and using induction machines are similar to the methods used in other electric machines but have their own specificity. Many issues discussed here are based on the fundamental achievements of authors such as Nasar, Boldea, Yamamura, Tegopoulos, and Kriezis, who laid the foundations for the development of induction machines, which are still relevant today. The control algorithms are based on the achievements of Blaschke (field vector-oriented control) and Depenbrock or Takahashi (direct torque control), who created standards for the control of induction machines. Today’s induction machines must meet very stringent requirements of reliability, high efficiency, and performance. Thanks to the application of highly efficient numerical algorithms, it is possible to design induction machines faster and at a lower cost. At the same time, progress in materials science and technology enables the development of new machine topologies. The main objective of this book is to contribute to the development of induction machines in all areas of their applications

Broken rotor bar detection in induction machines with transient operating speeds

Previous work on condition monitoring of induction machines has focused on steady-state speed operation. Here, a new concept is introduced based on an analysis of transient machine currents. The technique centers around the extraction and removal of the fundamental component of the current and analyzing the residual current using wavelets. Test results of induction machines operating both as a motor and a generator shows the ability of the algorithm to detect broken rotor bars

Fault detection methods for vapor-compression air conditioners using electrical measurements

Includes bibliographical references (p. 409-424).Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Architecture, 2008.(cont.) This method was experimentally tested and validated on a commercially available air handler and duct system. In the second class of faults studied, liquid refrigerant, rather than vapor, enters the cylinder of a reciprocating compressor during operation. Since the higher cylinder pressures that result can cause substantial damage and are difficult to measure directly, a method for detecting this fault is proposed that only uses observations of the compressor voltage and current. The performance of this fault detection method was also experimentally validated with electrical and mechanical measurements on a semi-hermetic compressor. The final diagnostic method detects refrigerant leakage in a residential air conditioning system by identifying changes in the system's cycling behavior. This method also uses measurements of the compressor's electrical power, as well as a small set of temperature measurements, to determine the presence of the fault. This fault detection method was developed and tested on an occupied residence.This thesis proposes novel methods that use measurements of electrical terminal variables to identify common mechanical faults in vapor-compression air-conditioners. The importance of air-conditioning in many applications and the current cost of energy both provide powerful incentives for developing fault detection methods, as faults can have a significant impact on the system's functionality and efficiency. While many extant fault detection and diagnostic (FDD) methods depend upon arrays of mechanical sensors, concerns about sensor reliability and the overall complexity of these methods motivated this research into electrically-based FDD methods, which typically incorporate smaller numbers of more reliable sensors. These electrically-based methods use models of the electromechanical energy conversion process to correlate observed changes in the electrical variables to changes caused by faults in the mechanical load. Such an approach allows both electrical and mechanical faults to be identified via the same sensor apparatus, and makes it possible to identify faults that manifest themselves on a wide range of timescales.FDD methods for three different classes of common faults are studied in this research. The first diagnostic method identifies blockage or leakage in a duct via electrical measurements made at the fan motor terminals. The estimates of the motor's speed and torque developed at the operating point are used in tandem with a fan curve to directly estimate the airflow through a duct system without any additional mechanical measurements.by Christopher Reed Laughman.Ph.D

An educational tool to assist the design process of switched reluctance machines

The design of electric machines is a hot topic in the syllabuses of several undergraduate and graduate courses. With the development of hybrid and electrical vehicles, this subject is gaining more popularity, especially in electrical engineering courses. This paper presents a computeraided educational tool to guide engineering students in the design process of a switched reluctance machine (SRM). A step-by-step design procedure is detailed and a user guide interface (GUI) programmed in the Matlab® environment developed for this purpose is shown. This GUI has been proved a useful tool to help the students to validate the results obtained in their lecture assignments, while aiding to achieve a better understanding of the design process of electric machines. A validation of the educational tool is done by means of finite element method (FEM) simulations.Postprint (author's final draft

Modelling and Detecting Faults of Permanent Magnet Synchronous Motors in Dynamic Operations

Paper VI is excluded from the dissertation until the article will be published.Permanent magnet synchronous motors (PMSMs) have played a key role in commercial and industrial applications, i.e. electric vehicles and wind turbines. They are popular due to their high efficiency, control simplification and large torque-to-size ratio although they are expensive. A fault will eventually occur in an operating PMSM, either by improper maintenance or wear from thermal and mechanical stresses. The most frequent PMSM faults are bearing faults, short-circuit and eccentricity. PMSM may also suffer from demagnetisation, which is unique in permanent magnet machines. Condition monitoring or fault diagnosis schemes are necessary for detecting and identifying these faults early in their incipient state, e.g. partial demagnetisation and inter-turn short circuit. Successful fault classification will ensure safe operations, speed up the maintenance process and decrease unexpected downtime and cost. The research in recent years is drawn towards fault analysis under dynamic operating conditions, i.e. variable load and speed. Most of these techniques have focused on the use of voltage, current and torque, while magnetic flux density in the air-gap or the proximity of the motor has not yet been fully capitalised. This dissertation focuses on two main research topics in modelling and diagnosis of faulty PMSM in dynamic operations. The first problem is to decrease the computational burden of modelling and analysis techniques. The first contributions are new and faster methods for computing the permeance network model and quadratic time-frequency distributions. Reducing their computational burden makes them more attractive in analysis or fault diagnosis. The second contribution is to expand the model description of a simpler model. This can be achieved through a field reconstruction model with a magnet library and a description of both magnet defects and inter-turn short circuits. The second research topic is to simplify the installation and complexity of fault diagnosis schemes in PMSM. The aim is to reduce required sensors of fault diagnosis schemes, regardless of operation profiles. Conventional methods often rely on either steady-state or predefined operation profiles, e.g. start-up. A fault diagnosis scheme robust to any speed changes is desirable since a fault can be detected regardless of operations. The final contribution is the implementation of reinforcement learning in an active learning scheme to address the imbalance dataset problem. Samples from a faulty PMSM are often initially unavailable and expensive to acquire. Reinforcement learning with a weighted reward function might balance the dataset to enhance the trained fault classifier’s performance.publishedVersio

Induction Motors

AC motors play a major role in modern industrial applications. Squirrel-cage induction motors (SCIMs) are probably the most frequently used when compared to other AC motors because of their low cost, ruggedness, and low maintenance. The material presented in this book is organized into four sections, covering the applications and structural properties of induction motors (IMs), fault detection and diagnostics, control strategies, and the more recently developed topology based on the multiphase (more than three phases) induction motors. This material should be of specific interest to engineers and researchers who are engaged in the modeling, design, and implementation of control algorithms applied to induction motors and, more generally, to readers broadly interested in nonlinear control, health condition monitoring, and fault diagnosis