The Harmonic Order Tracking Analysis Method for the Fault Diagnosis in Induction Motors Under Time-Varying Conditions

Abstract

This paper introduces a new approach for improving the fault diagnosis in induction motors under timevarying conditions. A significant amount of published approaches in this field rely on representing the stator current in the time-frequency domain, and identifying the characteristic signatures that each type of fault generates in this domain. However, time-frequency transforms produce three-dimensional representations, very costly in terms of storage and processing resources. Moreover, the identification and evaluation of the fault components in the time-frequency plane requires a skilled staff or advanced pattern detection algorithms. The proposed methodology solves these problem by transforming the complex 3D spectrograms supplied by timefrequency tools into simplegraphs, similar to conventional Fourier spectra. These graphs display a unique pattern for each type of fault, even under supply or load time-varying conditions, making easy and reliable the diagnostic decision even for non-skilled staff. Moreover, the resulting patterns can be condensed in a very small dataset, reducing greatly the storage or transmission requirements regarding to conventional spectrograms. The proposed method is an extension to nonstationary conditions of the harmonic order tracking approach (HOTA). It is introduced theoretically and validated experimentally using commercial induction motors feed through electronic converters.

Automatic Fault Diagnostic System for Induction Motors under Transient Regime Optimized with Expert Systems

“…A recent development in fault diagnosis of IMs allows to apply the same tool for analyzing the spectral content of the motor current in both regimes. This technique, known as harmonic order tracking analysis (HOTA) [4,5,18] allows to design a unique expert system for both regimes. Therefore, it is chosen as the basis of the diagnostic system generator proposed in this paper.…”

“…In this section, the HOTA method, introduced in [4,5,18], is briefly described. Unlike other methods where the frequency position of fault features (obtained from the current or its envelope) depend on other variables, in the HOTA method the fault frequencies are normalized to an integer, harmonic k-order scale, which is independent of the motor supply frequency and of the motor slip.…”

“…HOTA method for transient state is a method based on reducing the 2D time-frequency content of the fault harmonics of the motor current to a much simpler 1D harmonic k-order domain. As explained in [5], this simplification process is implemented using a Gaussian window and a short time Fourier transform (STFT), by iteratively moving the Gaussian window along the time domain and performing the frequency axis re-scaling at each step (see an example in Figure 1). An alternative option is to replace the STFT transform in HOTA by the short-frequency Fourier transform (SFFT), as in [6].…”

“…Therefore, fault diagnosis of IMs has become an important area of condition-based maintenance (CBM) programs, to avoid the high economic losses generated by unexpected breakdowns of IMs and sudden stoppages of the production lines that they drive. Specifically, fault diagnosis techniques based on the analysis of the MCSA [1][2][3][4][5][6] have gained a wide industrial deployment, due to their simplicity, low requirements of hardware and software, and capability for on-line simultaneous detection of a wide range of machine faults. Despite its advantages, industrial application of MCSA in harsh industrial environments, under real working conditions, is challenging.…”

A Survey of Condition Monitoring and Fault Diagnosis toward Integrated O&M for Wind Turbines

“…Vibration signal is divided by instantaneous speed to get the order signal, which successfully solves bearing fault diagnosis. The highlight of literature [78][79][80] is that, for the first time, the concept of order tracking was introduced into the current signal, and the SNR was successfully improved by converting the current to the rotor side. The unsteady state fault diagnosis based on OT is also the focus of future research.…”