Lucia Frosini

Stator Current and Motor Efficiency as Indicators for Different Types of Bearing Faults in Induction Motors

This paper proposes a new approach to use stator current and efficiency of induction motors as indicators of rolling-bearing faults. After a presentation of the state of the art about condition monitoring of vibration and motor current for the diagnostics of bearings, this paper illustrates the experimental results on four different types of bearing defects: crack in the outer race, hole in the outer race, deformation of the seal, and corrosion. The first and third faults have not been previously considered in the literature, with the latter being analyzed in other research works, even if obtained in a different way. Another novelty introduced by this paper is the analysis of the decrease in efficiency of the motor with a double purpose: as alarm of incipient faults and as evaluation of the extent of energy waste resulting from the lasting of the fault condition before the breakdown of the machine.

Electricity Smart Meters Interfacing the Households

The recent worldwide measures for energy savings call for a larger awareness of the household energy consumption, given the relevant contribution of domestic load to the national energy balance. On the other hand, electricity smart meters together with gas, heat, and water meters can be interconnected in a large network offering a potential value to implement energy savings and other energy-related services, as long as an efficient interface with the final user is implemented. Unfortunately, so far, the interface of such devices is mostly designed and addressed at the utilities supervising the system, giving them relevant advantages, while the communication with the household is often underestimated. This paper addresses this topic by proposing the definition of a local interface for smart meters, by looking at the actual European Union and international regulations, at the technological solutions available on the market, and at those implemented in different countries, and, finally, by proposing specific architectures for a proper consumer-oriented implementation of a smart meter network.

Induction Machine Bearing Fault Detection by Means of Statistical Processing of the Stray Flux Measurement

Rolling bearing faults are generally slowly progressive; therefore, the development of an effective diagnostic technique could be worth detecting such faults in their incipient phase and preventing complete failure of the motor. The methods proposed in the literature for this purpose are mainly based on measuring and analyzing vibration and current. Here, a novel technique based on the stray flux measurement in different positions around the electrical machine is proposed. The main advantages of this method are due to the simplicity and the flexibility of the custom flux probe with its amplification and filtering stage. The flux probe can be easily positioned on the machines and adapted to a wide range of power levels. This paper also reports an extensive survey on the stray-flux-based fault detection methods for induction motors, prior to introducing a novel sensor/diagnostic scheme.

Development of a leakage flux measurement system for condition monitoring of electrical drives

The aim of this paper is to investigate the possibility to employ a simple external flux coil to monitor the operating conditions of induction motors of different sizes, supplied at low voltage, from the mains or from power converters. The state of the art of the literature concerning the analysis of the stray flux around induction machines, in different positions and with different types of search coil, is here reported. Then, the flux probe here used is presented, together with several acquisitions of stray flux in three positions around the motor and with different techniques of signal analysis. These acquisitions are also compared with measurements collected by means of a commercial flux sensor. The final purpose is to find the best combination of position, sampling frequency, filter, etc. which can give the more interesting information about the “health” condition of the motor.

Use of the stator current for condition monitoring of bearings in induction motors

The aim of this paper is to verify the effectiveness of the stator current analysis for the detection of bearing problems. The paper reports the experimental results on four different types of bearing faults.

Diagnosis of rolling bearings faults in electric machines through stray magnetic flux monitoring

The most frequent causes of failure in electrical machines are due to bearing related faults. By means of advanced diagnosis methods, it is possible to detect these faults in their incipient phase, before the catastrophic effects of the failures can occur. In this paper, a new bearing fault diagnosis method by means of statistical analysis of the stator current and of the stray flux around an induction motor is presented. The experimental tests were carried out on a three-phase induction motor with three different bearing faults: crack in the outer race, hole in the outer race and deformation of the protective seal.

Detection of stator short circuits in inverter-fed induction motors

In this paper, an experimental investigation about the use of non-invasive instruments, like stator current and external leakage flux analysis, to detect inter-turns short-circuits in stator windings of low voltage induction motors supplied by inverter is reported. The results are encouraging and the technique here proposed can be evaluated as a tool to detect these faults in their early stage in motors which are more stressed with respect to those supplied by the mains, due to the IGBT PWM feeding.

The effect of rotor eccentricity on the radial and tangential electromagnetic stresses in synchronous machines

In this paper radial and tangential electromagnetic stresses acting in synchronous machines are expressed as function of known and measurable parameters. Therefore, their values are estimated in case of salient-poles and smooth-poles generators. Finally, the effect of the rotor eccentricity on open circuit and in load condition is evaluated, in order to obtain a more correct evaluation of the unbalanced magnetic pull

Neural networks for energy flows prediction in facility systems

A procedure for the short-term prediction of the thermal energy consumption of a hospital is shown in this paper. First, linear ARX models are built in order to obtain information on the influence of the input variables on the output of the system. Therefore, nonlinear models based on feedforward neural networks (NNARX) are built using the information provided by the linear estimate. The results obtained from the ARX and NNARX models are compared, concluding that NNARX models provide better results than ARX models, but the analysis of ARX models is necessary to obtain guidelines in the choice of the best regression vector as input for the neural models.

Bearing faults detection in induction machines based on statistical processing of the stray fluxes measurements

Frequent defects of induction machines are due to diverse bearing faults. The detection of such faults in their incipient phase can decisively contribute to the prevention of unplanned breakdowns in industrial plants. In this paper the detection of three types of bearing faults by means of statistical processing of the stray fluxes measurements is detailed. The developed noninvasive method requires only both simple probes and easy computations. Numerous measurements had been performed for all the combinations of bearing faults, loads and stray flux probes taken into study. All the results emphasized the effectiveness of the applied simple fault diagnosis method.