Maciej Sułowicz

This paper compares the accuracy of the multi-frequency stator phase current spectrum estimation. This is as a development of considerations made in [1]. In this paper, the authors added to previous results for the classic Discrete Fourier Transform method and the two-point interpolated DFT method (IpDFT ), new results obtained by three-point IpDFT method’s algorithm. The analysis was made for slip spectrum component which is used for cage damage detection. To minimize the spectrum leakage effect, the selected Rife-Vincent Class I windows (RVCI ) were used. The article focuses on the effectiveness of spectral component estimation in function of the used method, type of time window and measurement time. Values of errors of frequency and amplitude estimations are presented on graphs. The authors compared theoretical considerations with the case of real stator current of an asynchronous motor with a broken cage. This article can be used as a base for further studies on the diagnosis of induction motors.

Technical condition assessment of induction motor can be done with stator current analysis. This analysis can be done in steady state with FFT transform. Starting current analysis with wavelet transform is a very good method of cage condition assessment. The advantage of this method is that we can observe how characteristic components vary in time. Characteristic fault symptoms can be observed when the machine is working with alternating load which causes rotor’s angular speed and slip change. Transient states when the load changes, occur very often increases the application of thism method. This paper presents the results of application wavelet transform in motor fault diagnostics in transient states.

The following paper presents possibilities for the application of selected time-frequency analysis methods in the fault detection of cage induction machines in transient states. The starting phase current of the machine was chosen as a diagnostic signal. Selected faults were eccentricities – static and dynamic. In order to increase the selectivity of the obtained signal transformations, a notch filter was used to remove the base harmonic of the phase current. Two approaches of fault detection were compared. In the first approach, the characteristic feature of fault was extracted using DWT analysis. Next, TMCSA methodology was applied in which characteristic harmonics related to faults were shown on a time-frequency plane. In this case, applied methods were a Gabor transformation, STFT, CWT and Wigner–Ville’s transformation. In the analysis, a phase current signal approximated by DWT was used. DWT approximation was applied to filter higher harmonics which improves the resolution of the obtained transformations.

The article presents the possibility of using axial flux signals in the fault diagnosis of low-power induction machines working under varying load conditions. The study involved cases of asymmetrical rotors and stators in steady state and transient conditions during start-up. The laboratory measurements were performed on a modified induction motor, which was equipped with a special coil built into the bearing shield allowing the measurement of the voltage proportional to the motor axial flux. Examples of the obtained waveforms and numerical data were supplemented by conclusions and a review of current knowledge concerning the application of the axial flux signal for the purpose of the fault diagnosis of squirrel cage induction motors. 

The subject of the study is to analyze the effectiveness of early detection of damage to the stator winding with two parallel branches in the cage induction motor, by evaluating changes in the waveforms of branch currents in steady state operation. Harmonic components of the Fourier spectrum of circulating current, defined as the difference between the transient values of currents in the branches of the winding, were adopted as the indicators of branch current change evaluation. For a given low-power motor, several cases of a section short- circuiting in one of the winding branches were examined, for both symmetric and asymmetric air gap and for resistive symmetry and asymmetry of the rotor cage. The studies show a greater influence of damages on the changes in the amplitudes of selected harmonics of the circulating current, in comparison to changes of the stator phase current corresponding harmonics.

In this paper, the possibilities of rolling bearing diagnostics, according to the PN and ISO standards, utilising the dimensionless discriminants of vibroacoustic processes, CPB frequency analysis and envelope detection methods are presented. The test bench, the measuring system, as well as the obtained results are described in detail. The authors’ own algorithm for the course of action during the process of detecting damage torolling bearings, involving the multi-criterion diagnostic utilising the afore methods is also described.

This article presents the idea of asynchronous motor’s non-stationary stator starting current, filtration methods, in the non-invasive diagnosis of the rotor cage. The mathematical description of the selected analysis forms is omitted in favor of an indication of the practical aspects of the method application and the obtaining of sample analysis results. The object of the study was the single cage induction motor with exchangeable rotors for different faults, machine’s load was a generator with field current control system, which was used to control the load torque.

This paper presents the results of an analysis of signals recorded in different inter-turn short- circuit states in the stator windings of a squirrel-cage motor operating under a constant load. The analysis was carried out in a time-frequency domain using a simple orthonormal wavelet base that can be used in a real system without the need to acquire specialist software. The choice of analytical was associated with the existence of a periodic energy flow between adjacent frequency bands, thus making it difficult to diagnose the Fourier analysis. The aim of the study was to gather data necessary for the development of a real-time diagnostic system. Magnetic axial flux, the zero voltage signal, the short- circuit current, vibration acceleration, sound pressure, electromechanical torque, currents and phase voltages were tested as diagnostic criteria. The paper presents the main results of the analyses of magnetic axial flux signal and conclusions.

The study of the interaction between faults of different natures is a crucial step for the development of effective systems for fault detection. The analysis of the electrical signals using the actual motor current signature analysis (MCSA) techniques may lead to different results and, as a consequence, an incorrect diagnosis of the fault due to the fact that the non-linear interactions between both faults are difficult to predict with high precision. The relationship between the electrical and mechanical components has been extensively studied in the past, but despite the progress made, the introduction of new control systems or the nonlinearities presented in the electrical machine, still makes it hard to diagnose faults. The study below attempts to show the evolution of the induction motor signatures when electrical and mechanical faults occur simultaneously. The Fourier analysis of the signatures presented in this paper indicates that the typical analysis carried out to diagnose the state of the electrical machine may be interpreted as an indicator of a different type of fault.