Fabio Immovilli

Diagnosis of Bearing Faults in Induction Machines by Vibration or Current Signals: A Critical Comparison

Early diagnosis of faults in induction machines is an extensively investigated field, for cost and maintenance savings. Mechanical imbalances and bearing faults account for a large majority of faults in a machine, especially for small-medium size machines. Therefore their diagnosis is an intensively investigated field or research. Recently many research activities were focused on the diagnosis of bearing faults by current signal. Stator current components are generated at predictable frequencies related to the electrical supply and mechanical frequencies of bearing faults. However their detection is not always reliable, since the amplitude of fault signatures in the current signal is very low. This paper compares the bearing fault detection capability obtained with vibration and current signals. To this aim a testbed is realized that allows to test vibration and current signal on a machine with healthy or faulty bearings. Signal processing techniques for both cases are reviewed and compared in order to show which procedure is best suited to the different type of bearing faults. The paper contribution is the use of a simple and effective signal processing technique for both current and vibration signals, and a theoretical analysis of the physical link between faults and current components including torque ripple effects. As expected because of the different nature of vibration and current, bearing fault diagnosis is effective only for those fault whose mechanical frequency rate is quite low. Experiments are reported that confirm the proposed approach.

Diagnosis of Bearing Faults of Induction Machines by Vibration or Current Signals: A Critical Comparison

Mechanical imbalances and bearing faults account for a large majority of the faults in a machine, particularly for small-medium size machines. Therefore, their diagnosis is an intensively investigated field of research. Recently, many research activities were focused on the diagnosis of bearing faults by current signals. This paper compares the bearing fault detection capability obtained with the vibration and current signals. The paper contribution is the use of a simple and effective signal processing technique for both current and vibration signals, and a theoretical analysis of the physical link between faults, modeled as a torque disturbance, and current components. The focus of the paper is on the theoretical development of the correlation between torque disturbances and the amplitude of the current components, together with a review of fault models used in the literature. Another contribution is the re-creation of realistic incipient faults and their experimental validation. Radial effects are visible only in case of large failures that result in air-gap variations. Experiments are reported that confirm the proposed approach.

Detection of Generalized-Roughness Bearing Fault by Spectral-Kurtosis Energy of Vibration or Current Signals

Generalized roughness is the most common damage occurring to rolling bearings. It produces a frequency spreading of the characteristic fault frequencies, thus making it difficult to detect with spectral or envelope analysis. A statistical analysis of typical bearing faults is proposed here in order to identify the spreading bandwidth related to specific conditions, relying on current or vibration measurements only. Then, a diagnostic index based on the computation of the energy in the previously defined bandwidth is used to diagnose bearing faults. The proposed method was validated experimentally with vibration signals, with robust and reliable results. The same procedure can be extended to current signals.

Bearing Fault Model for Induction Motor With Externally Induced Vibration

This paper investigates the relationship between vibration and current in induction motors operated under external vibrations. Two approaches are usually available to define this relationship. The former is based on airgap variations, while the latter is based on torque perturbation. This paper is focused on the airgap variation model. The ball bearing fault is modeled by contact mechanics. External vibrations often occur in many industrial applications where externally induced vibrations of suitable amplitude cause cyclic radial loading on the machine shaft. The model is validated by experiments, owing to a dedicated test setup, where an external vibration source (shaker) was employed, together with ball bearing alterations in order to decrease the stiffness of the support along the radial direction. To maximize the effects of externally induced vibrations, the frequency chosen was near the flexural resonance of the rotor (determined by finite-element method analysis). The direction of the external vibration is radial with respect to the axis of the electric machine under test. During tests, both stator phase currents and vibration of the machine were sampled. The test setup allowed one to vary the machine speed and load, vibration amplitude, and bearing stiffness (damage level). Radial effects are usually visible only in the case of large failures that result in significant airgap variations, as confirmed by experiments.

Fault Detection of Linear Bearings in Brushless AC Linear Motors by Vibration Analysis

Electric linear motors are spreading in industrial automation because they allow for direct drive applications with very high dynamic performances, high reliability, and high flexibility in trajectory generation. The moving part of the motor is linked to the fixed part by means of linear bearings. As in many other electric machines, bearings represent one of the most vulnerable parts because they are prone to wear and contamination. In the case of linear roller bearings, this issue is even more critical as the rail cannot be easily fully enclosed and protected from environmental contamination, unlike the radial rotating bearing counterpart. This paper presents a diagnostic method based on vibration analysis to identify which signature is related to a specific fault.

Review of Design Solutions for Internal Permanent-Magnet Machines Cogging Torque Reduction

Internal permanent-magnet synchronous machines are spreading in industrial production. They feature high torque density and extended speed range that are key issues in many fields of applications, however their cogging torque is typically quite high. Many methods and design guidelines for cogging torque reduction exist in literature and this paper compares them. For this purpose, the different design guidelines are applied to a common reference machine in order to assess their effectiveness. Computer finite element analysis (FEA) are carried out for each case in order to compare the cogging torque reduction capability of the different techniques. The side effects of these techniques, such as back-EMF and rated torque profile distortions, will be taken into account. The paper contribution is to compare the various cogging torque reduction techniques and magnetic geometries on a common reference machine to identify the most effective ones.

Evaluation of Combined Reference Frame Transformation for Interturn Fault Detection in Permanent-Magnet Multiphase Machines

This paper focuses on modeling and experimental validation of a diagnostic fault classification procedure for interturn fault detection in permanent-magnet (PM) multiphase machines designed for fault-tolerant electric drives. The diagnostic procedure is based on the symmetrical component theory and relies upon the combined space vector vector D that gathers information from the two original space vectors obtained with different reference frames. The diagnostic index effectiveness and robustness were also investigated against other fault types such as rotor eccentricities and magnet damage to assess its discrimination capability. The proposed procedure was experimentally evaluated for the interturn fault case on a five-phase PM machine. Experiments were carried out at different speed and load levels, with increasing numbers of short-circuited turns. Both simulation and experimental results demonstrated the feasibility of the proposed diagnostic method.

Solar Trigeneration for Residential Applications, a Feasible Alternative to Traditional Micro-Cogeneration and Trigeneration Plants

Trigeneration stands for the combined production of electricity, heat, and cooling (CHCP). This paper reviews and compares CHCP system based on solar energy with respect to traditional CHCP ones. A further comparison is made among the possible technologies for solar CHCP to assess the technical solutions more suited to residential applications. Beyond photovoltaic based systems, two other solutions are proposed: a concentrated sunlight all-thermoacoustic system and an hybrid thermo-photovoltaic system. In a grid-connected energy market, the adoption of CHCP plants may become profitable with respect to traditional systems, where the single energies are produced or purchased separately. Specifically, the onset of solar trigeneration can lead to a substantial improvement, overcoming many of the traditional drawback associated with micro-cogeneration and trigeneration. The result is a trigeneration system based totally on renewable energy. This is especially attractive for the residential demand, provided that a cost-effective technical solution is available.

Diagnosis of mechanical faults by spectral kurtosis energy

Generalized roughness is the most common damage occurring to roller bearing. It produces a frequency spreading of the characteristics fault frequencies, thus being difficult to detect with spectral or envelope analysis. A statistical analysis of typical bearing faults is here proposed in order to identify the spreading bandwidth related to a specific conditions, relying on current measurements only. Then a diagnostic index based on the computation of the energy in the above defined bandwidth is used to diagnose bearing faults. The proposed method was validated experimentally with vibration signals, with robust and reliable results. Subsequently it has been applied to stator currents monitoring.

Active Rectifier With Integrated System Control for Microwind Power Systems

This paper presents simple and effective control strategies for the active rectifier stage (ac/dc stage) of a grid-connected low-power system for microwind applications employing permanent magnet synchronous generator (PMSG). In particular, a novel algorithm for the estimation of the rotor angle of the PMSG, based on flux estimators, was implemented using an adaptive low-pass filter coupled with a feed-forward compensator. This enabled a very smooth start-up operation of the PMSG, obtained by preloading the values of the flux estimator and using a single-voltage transformer (VT) transducer. The solution for the power flow control between the active rectifier and the other(s) power converters connected to the common dc link was implemented without any digital communication between them, in order to obtain a solution suitable for modular architectures (e.g., to be used in conjunction with a grid-connected converter and/or an energy storage system). Simulation and experimental results confirmed the effectiveness of the proposed solutions. The experimental validation was conducted using a grid-connected converter as load for the proposed active rectifier.