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

Recently, research concerning electrical machines and drives condition monitoring and fault diagnosis has experienced extraordinarily dynamic activity. The increasing importance of these energy conversion devices and their widespread use in uncountable applications have motivated significant research efforts. This paper presents an analysis of the state of the art in this field. The analyzed contributions were published in most relevant journals and magazines or presented in either specific conferences in the area or more broadly scoped events.

/pdf/advances-in-electrical-machine-power-electronic-and-drive-4jt41t4f8x.pdf

Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art

There is a constant need for the reduction of operational and maintenance costs of Wind Energy Conversion Systems (WECSs). The most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the degeneration of the generator health, facilitating a proactive response, minimizing downtime, and maximizing productivity. Wind generators are also inaccessible since they are situated on extremely high towers, which are normally 20 m or more in height. There are also plans to increase the number of offshore sites increasing the need for a remote means of WECS monitoring that eliminates some of the difficulties faced due to accessibility problems. Therefore and due to the importance of condition monitoring and fault diagnosis in WECS (blades, drive trains, and generators), and keeping in mind the need for future research, this paper is intended as a brief status describing different types of faults, their generated signatures, and their diagnostic schemes.

https://hal.archives-ouvertes.fr/hal-00525370/document

A Brief Status on Condition Monitoring and Fault Diagnosis in Wind Energy Conversion Systems

Cost-effective wind turbine (WT) condition monitoring assumes more importance as turbine sizes increase and they are placed in more remote locations, for example, offshore. Conventional condition monitoring techniques, such as vibration, lubrication oil, and generator current signal analysis, require the deployment of a variety of sensors and computationally intensive analysis techniques. This paper describes a WT condition monitoring technique that uses the generator output power and rotational speed to derive a fault detection signal. The detection algorithm uses a continuous-wavelet-transform-based adaptive filter to track the energy in the prescribed time-varying fault-related frequency bands in the power signal. The central frequency of the filter is controlled by the generator speed, and the filter bandwidth is adapted to the speed fluctuation. Using this technique, fault features can be extracted, with low calculation times, from direct- or indirect-drive fixed- or variable-speed WTs. The proposed technique has been validated experimentally on a WT drive train test rig. A synchronous or induction generator was successively installed on the test rig, and both mechanical and electrical fault like perturbations were successfully detected when applied to the test rig.

/pdf/cost-effective-condition-monitoring-for-wind-turbines-1k1sap7pf9.pdf

Cost-Effective Condition Monitoring for Wind Turbines

This paper introduces an advanced monitoring and diagnosis system for the detection of incipient electrical faults in doubly fed induction generators used in wind turbines. In this application, the rotor is supplied by a static converter for the control of active and reactive power flows from the generator to the electrical grid. A new diagnostic method based on the frequency analysis of the rotor modulating signals is proposed. Simulation and experimental results confirm that a convenient frequency analysis of these signals and a simple interpretation lead to an effective diagnostic procedure. The proposed system is suitable to be easily embedded in the power-converter digital control system at very low cost.

Doubly Fed Induction Machines Diagnosis Based on Signature Analysis of Rotor Modulating Signals

Motor current signature analysis is the reference method for the diagnosis of induction machines' rotor faults; however, in time-varying conditions, it fails as slip and speed vary, and, thus, sideband components are spread in a bandwidth that is proportional to the variation. Variable speed drive applications are common in the aerospace, appliance, railway, and automotive industries and also in electric generators for wind turbines. In this paper, a simple and effective method is presented that allows the diagnosis of rotor faults for induction machine drives in time-varying conditions. It is tailored to direct rotor flux field-oriented controlled drives, where the control system provides suitable signals that are exploited for the demodulation to a constant frequency of time-varying signatures related to the rotor faults. Simulations and experiments are reported to validate the proposed method on a critical speed transient.

Diagnosis of Induction Machines' Rotor Faults in Time-Varying Conditions

Nowadays Permanent Magnet Synchronous Motor (PMSM) are an attractive alternative to induction machines for a variety of applications due to their higher efficiency, power density and wide constant power speed range. In this context the condition monitoring of magnets status is receiving more and more attention since is critical for industrial applications. This paper presents a characterization of rotor faults for such a motor due to local and uniform demagnetization by means of two dimensional (2-D) Finite Element Analysis (FEA) and proposes a new non-invasive method for their detection by means of a Fourier transform of the back-EMF. The proposed approach is then validated for three Permanent Magnet Synchronous Motors with different winding configurations.

Magnets faults characterization for Permanent Magnet Synchronous Motors

Experimental validation of doubly fed induction machine electrical faults diagnosis under time-varying conditions

The paper introduces an advanced monitoring and diagnosis system for the detection of incipient electrical faults in Doubly Fed Induction Generators (DFIGs) used in wind generator systems. In this application the rotor power is supplied by a converter for the control of active and reactive power flow from the generator to the mains. The paper deals with a new diagnostic method based on the analysis of the rotor modulating signals. Simulation and experimental results confirm that the analysis of the spectra of rotor input modulating signals leads to an effective diagnostic procedure. The system is suitable to be easily embedded in the drive control system.

A. Stefani

Papers

Doubly Fed Induction Machines Diagnosis Based on Signature Analysis of Rotor Modulating Signals

Diagnosis of Induction Machines' Rotor Faults in Time-Varying Conditions

Magnets faults characterization for Permanent Magnet Synchronous Motors

Experimental validation of doubly fed induction machine electrical faults diagnosis under time-varying conditions

Diagnostic Technique based on Rotor Modulating Signals Signature Analysis for Doubly Fed Induction Machines in Wind Generator Systems