This paper investigates diagnostic techniques for electrical machines with special reference to induction machines and to papers published in the last ten years. A comprehensive list of references is reported and examined, and research activities classified into four main topics: 1) electrical faults; 2) mechanical faults; 3) signal processing for analysis and monitoring; and 4) artificial intelligence and decision-making techniques.

Advances in Diagnostic Techniques for Induction Machines

Although it has long been argued that electronic power converters can help improve system controllability, reliability, size, and efficiency, their penetration in power systems is still quite low. The often-cited barriers of higher cost and lower reliability of the power converters are quite high if power electronics is used as direct, one-to-one, replacement for the existing electromechanical equipment. However, if the whole power distribution system were designed as a system of controllable converters, the overall system cost and reliability could actually improve, as is currently the case at low power levels within computer and telecom equipment. Starting from the example of a computer power system, the paper contemplates possible future ac and dc electronic power distribution system architectures, especially in the presence of renewable energy sources. The proposed nanogrid-microgrid-…-grid structure achieves hierarchical dynamic decoupling of generation, distribution, and consumption by using bidirectional converters as energy control centers. This is illustrated by the description and simulation of static and dynamic operation of a dc nanogrid in a hypothetical future sustainable home. Several ideas for modeling, analysis, and system-level design of such systems, including power flow control, protection, stability, and subsystem interactions, are presented.

Future electronic power distribution systems a contemplative view

Medium-voltage (MV) induction motors are widely used in the industry and are essential to industrial processes. The breakdown of these MV motors not only leads to high repair expenses but also causes extraordinary financial losses due to unexpected downtime. To provide reliable condition monitoring and protection for MV motors, this paper presents a comprehensive survey of the existing condition monitoring and protection methods in the following five areas: thermal protection and temperature estimation, stator insulation monitoring and fault detection, bearing fault detection, broken rotor bar/end-ring detection, and air gap eccentricity detection. For each category, the related features of MV motors are discussed; the effectiveness of the existing methods are discussed in terms of their robustness, accuracy, and implementation complexity. Recommendations for the future research in these areas are also presented.

A Survey of Condition Monitoring and Protection Methods for Medium-Voltage Induction Motors

The fault diagnosis of rotating electrical machines has received an intense amount of research interest during the last 30 years. Reducing maintenance costs and preventing unscheduled downtimes, which result in losses of production and financial incomes, are the priorities of electrical drives manufacturers and operators. In fact, both correct diagnosis and early detection of incipient faults lead to fast unscheduled maintenance and short downtime for the process under consideration. They also prevent the harmful and sometimes devastating consequences of faults and failures. This topic has become far more attractive and critical as the population of electric machines has greatly increased in recent years. The total number of operating electrical machines in the world was around 16.1 billion in 2011, with a growth rate of about 50% in the last five years [1].

/pdf/trends-in-fault-diagnosis-for-electrical-machines-a-review-47iy1hp1hg.pdf

Trends in Fault Diagnosis for Electrical Machines: A Review of Diagnostic Techniques

The virtual impedance concept is increasingly used for the control of power electronic systems. Generally, the virtual impedance loop can either be embedded as an additional degree of freedom for active stabilization and disturbance rejection, or be employed as a command reference generator for the converters to provide ancillary services. This paper presents an overview of the virtual-impedance-based control strategies for voltage-source and current-source converters. The control output impedance shaping attained by the virtual impedances is generalized first using the impedance-based models. Different virtual impedances and their implementation issues are then discussed. A number of practical examples are demonstrated to illustrate the feasibility of virtual impedances. Emerging applications and future trends of virtual impedances in power electronic systems conclude this paper.

Virtual-Impedance-Based Control for Voltage-Source and Current-Source Converters

The latest advances in electric and electronic aircraft technologies from the point of view of an "all-electric" aircraft are presented herein. Specifically, we describe the concept of a "more electric aircraft" (MEA), which involves removing the need for on-engine hydraulic power generation and bleed air off-takes, and the increasing use of power electronics in the starter/generation system of the main engine. Removal of the engine hydraulic pumps requires fully-operative electrical power actuators and mastery of the flight control architecture. The paper presents a general overview of the electrical power generation system and electric drives for the MEA, with special regard to the flight controls. Some discussion regarding the interconnection of nodes and safety of buses and protocols in distributed systems is also presented

/pdf/moving-towards-a-more-electric-aircraft-yt1pxk9bb6.pdf

Moving towards a more electric aircraft

Motor-current-signature analysis has been successfully used in induction machines for fault diagnosis. The method, however, does not always achieve good results when the speed or the load torque is not constant, because this causes variations on the motor-slip and fast Fourier transform problems appear due to a nonstationary signal. This paper proposes a new method for motor fault detection, which analyzes the spectrogram based on a short-time Fourier transform and a further combination of wavelet and power-spectral-density (PSD) techniques, which consume a smaller amount of processing power. The proposed algorithms have been applied to detect broken rotor bars as well as shorted turns. Besides, a merit factor based on PSD is introduced as a novel approach for condition monitoring, and a further implementation of the algorithm is proposed. Theoretical development and experimental results are provided to support the research.

Fault Detection in Induction Machines Using Power Spectral Density in Wavelet Decomposition

This paper presents a novel method to diagnose demagnetization in permanent-magnet synchronous motor (PMSM). Simulations have been performed by 2-D finite-element analysis in order to determine the current spectrum and the magnetic flux distribution due to this failure. The diagnostic just based on motor current signature analysis can be confused by eccentricity failure because the harmonic content is the same. Moreover, it can only be applied under stationary conditions. In order to overcome these drawbacks, a novel method is used based upon the Hilbert-Huang transform. It represents time-dependent series in a 2-D time-frequency domain by extracting instantaneous frequency components through an empirical-mode decomposition process. This tool is applied by running the motor under nonstationary conditions of velocity. The experimental results show the reliability and feasibility of the methodology in order to diagnose the demagnetization of a PMSM.

/pdf/fault-detection-by-means-of-hilbert-huang-transform-of-the-3aqwvgpcxw.pdf

Fault Detection by Means of Hilbert–Huang Transform of the Stator Current in a PMSM With Demagnetization

This paper presents the results of our study of the permanent-magnet synchronous motor (PMSM) running under demagnetization. We examined the effect of demagnetization on the current spectrum of PMSMs with the aim of developing an effective condition-monitoring scheme. Harmonics of the stator currents induced by the fault conditions are examined. Simulation by means of a two-dimensional finite-element analysis (FEA) software package and experimental results are presented to substantiate the successful application of the proposed method over a wide range of motor operation conditions. Methods based on continuous wavelet transform (CWT) and discrete wavelet transform (DWT) have been successfully applied to detect and to discriminate demagnetization faults in PMSM motors under nonstationary conditions. Additionally, a reduced set of easy-to-compute discriminating features for both CWT and DWT methods has been defined. We have shown the effectiveness of the proposed method by means of experimental results.

Detection of Demagnetization Faults in Permanent-Magnet Synchronous Motors Under Nonstationary Conditions

This paper presents and analyzes a method for short-circuit fault detection in a permanent-magnet synchronous motor (PMSM). The study includes steady-state condition and speed transients in motor operation. The stator current is decomposed by empirical mode decomposition (EMD), which generates a set of intrinsic mode functions (IMFs). Quadratic time-frequency (TF) distributions such as smoothed pseudo-Wigner-Ville and Zhao-Atlas-Marks are applied on the more significant IMFs for fault detection. Simulations and experimental laboratory tests validate the algorithms and demonstrate that this kind of TF analysis can be applied to detect and identify short-circuit failures in PMSM.

Javier A. Rosero

Papers

Moving towards a more electric aircraft

Fault Detection in Induction Machines Using Power Spectral Density in Wavelet Decomposition

Fault Detection by Means of Hilbert–Huang Transform of the Stator Current in a PMSM With Demagnetization

Detection of Demagnetization Faults in Permanent-Magnet Synchronous Motors Under Nonstationary Conditions

Short-Circuit Detection by Means of Empirical Mode Decomposition and Wigner–Ville Distribution for PMSM Running Under Dynamic Condition